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iUTAH Data Manager

iUTAH | Data Manager

Subject Areas: Hydrology, Hydroinformatics, Cyberinfrastrucutre, Water Quality, Water Resources Management, Data Management, Social Water Science Data,

 Recent activity

ABSTRACT:

The results included are based on the HSPF model simulations developed for the Jordan River watersehds. The base model used to simulate was developed by a consultant (STANTEC in 2010/2011) and employed by the Salt Lake County, Utah. The model was calibrated and statistical results were checked only for the Big Cottonwood Canyons at the Canyons Mouth and other several location in the Jordan River. The model was applied to study climate and land use change in March 2017. The historical time periods considered are Jan1 1995 to Dec 31,2004. The calibration time period considered for the streamflow is Jan1,2005 to Dec 31,2006 (it varies for other water quality parameters considering the data availability). Future simulations include 2035 to 2044 and 2085 to 2094. The model results were simulated in an hourly time steps and this resource has the daily results. The results included are only for the climate change scenarios as the canyons have negligible effects of the land use and land cover changes. The three scenarios considered are based on the RCP6 climate scenario that was dynamically downscaled using the Weather Research & Forecasting (WRF) model and statistically downscaled two climate scenarios corresponding to the mean of the driest and wettest quartiles of the statistically downscaled CMIP5 database at https://gdo-dcp.ucllnl.org/downscaled_cmip_projections/dcpInterface.html .

For each streamflow tab in the file, the Observed column indicates results forcing the model with station observations. Future simulation columns labeled Min_* provide results for the mean of the driest quartile of CMIP5 simulations, RCP_* provide results for the WRF simulation of RCP 6.0, and Max_* provide results for the mean of the wettest quartile of CMIP5 simulations. The second tab in the file provides sample results from the HSPF standard calibration procedure.

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ABSTRACT:

In order to assess the impacts on stakeholder decisions and actions linked to iUTAH's social and engineering science and research efforts, interviews were conducted in 2017 with 17 researchers and 13 external partners (who were identified by researchers as having been involved in collaborative efforts). Interviews were recorded, transcribed and analyzed thematically for reporting. For 16 participants (8 researchers and 8 external partners), a revised informed consent process was conducted in which they all agreed to be identified in project reporting on 4 case studies. All other participants remain confidential per the original informed consent process. We have included the interview protocols (questions) for researchers and partners (as questions asked to the researchers and partners differed slightly) as well as a summary report of findings.

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ABSTRACT:

This project is a compilation and synthesis of publications by researchers on the iUTAH project (innovative Urban Transitions and Aridregion Hydro-sustainability) who were focused on social and engineering water science (referred to as Research Focus Area 2 or RFA2). Data are represented in a spreadsheet coded for various attributes, including each paper's objective, core finding, summary contribution, unit of analysis, geographic focus, and connection to iUTAH's iSAW conceptual framework (Hale et al. 2015). A codebook for variables is provided in a separate file. Ultimately, a manuscript will be written based on a synthesis of these data.

Hale RL, A Armstrong, MA Baker, S Bedingfield, D Betts‎, C Buahin, M Buchert, T Crowl, RR Dupont‎, JR Ehleringer, J Endter-Wada, C Flint, J Grant, S Hinners, JS Horsburgh, D Jackson-Smith, AS Jones, C Licon‎, SE Null, A Odame, DE Pataki, D Rosenberg, M Runburg‎, P Stoker, C Strong. 2015. iSAW: Integrating structure, actors, and water to study socio-hydro-ecological systems. Earth’s Future. 3(3): 110-132. https://doi.org/10.1002/2014EF000295.

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ABSTRACT:

This project involved 20 semi-structured interviews with iUTAH researchers to ask questions pertaining to teamwork processes inherent in large scale interdisciplinary projects. Additionally, questions pertaining to project success and project evaluation were asked. Interviews were conducted either in-person with researchers who were located in the state, and over the phone with researchers who were located out of the state. Interviews were recorded and transcribed and analyzed for the aforementioned themes. Interviews may not be shared in order to protect the identify of participants. At the completion of the project, a masters thesis will be made publicly available describing the methods and findings from this project.

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ABSTRACT:

Freshwater habitats comprise some of the most altered ecosystems on Earth, primarily due to anthropogenic disturbances in hydrology and nutrient cycling. Many freshwater systems in North America are limited by nitrogen and phosphorus, and their addition from anthropogenic sources (from agricultural and residential runoff or atmospheric deposition from air pollution) can cause eutrophication. Changes in abiotic and biotic factors due to eutrophication often result in reduced water quality and ecosystem services such as water filtration. Projected shifts in regional precipitation and temperature as a component of global climate change will further alter the functioning of freshwater ecosystems. Alterations in precipitation, coupled with shifts in land-use, are projected to increase sediment loading in freshwater systems. Sediment loading in freshwater ecosystems can result in changes to community structure, biomass, and primary productivity. In addition, sedimentation can reduce net photosynthesis rates by smothering periphyton, the photosynthetic protists that exist in the biofilm that forms on surfaces. Sediment can be cleared in freshwater systems through several routes, including consumption of sediments by animals and bioturbation (biological activity that influences sediment transport, deposition, and accrual). Larval amphibians (primarily tadpoles) may play an important role in sediment accrual and nutrient recycling rates through both sediment consumption and bioturbation. Bioturbation by larval amphibians, as any other behavior, may be affected by environmental stressors. Nitrogen, in the form of nitrate or nitrite, may influence tadpole activity rate. Although we have an understanding of the effects of nutrient and sediment loading on aquatic systems, we do not understand how organisms such as larval amphibians might mediate the effects of these two stressors on primary producers in aquatic systems. Bioturbation and grazing by amphibians could affect growth of primary producers in three ways: 1) tadpoles could increase the amount of nitrogen suspended in the water column; 2) tadpoles can clear sediment from surfaces, thereby increasing light available for periphyton photosynthesis; 3) tadpole grazing on primary producers (phytoplankton and periphyton) could reduce biomass of these primary producers. Sedimentation and nutrient loading are issues negatively affecting Utah’s water quality.
Our work focuses on two areas of the southern region where nitrogen inputs and sedimentation are important regional stressors. We will first sample natural sedimentation rates and nitrogen levels in ponds at the Canyonlands Research Center (near Moab, UT) and sites in and near Cedar City, UT, and then experimentally manipulate nitrate addition, macrophyte presence, sedimentation, and tadpole presence to test the effects of nitrogen and sedimentation on tadpole behavior and primary production. Our work will begin to identify potential community linkages in consumers and primary producers in the presence of two abiotic stressors. Understanding the connections among species and how those connections influence the response of functional groups in the community (i.e. primary producers) is increasingly important in the face of local and global environmental changes.

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 Contact

Resources
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Survey of Stormwater Managers in Utah
Created: June 28, 2016, 5:44 p.m.
Authors: Andrea Armstrong

ABSTRACT:

This is a final report that summarizes the findings of a survey of stormwater managers in Utah conducted by Andrea Armstrong (Sociology, USU) in partnership with the Utah Stormwater Advisory Committee (USWAC). The final report includes an overview of methods, descriptive findings, and an executive summary.

The purpose of this effort was to collect statewide data, in partnership with the Utah Storm Water Advisory Committee, on stormwater managers attitudes, perceptions, and behaviors surrounding various aspects of stormwater management, including document updates, use of low impact development infrastructure, monitoring activities, water quality condition perceptions, changes in landscape and climate patterns, partnerships with irrigation organizations, information uses, program challenges, important dimensions of program activities, and water quality monitoring activities.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on the Knowlton Fork tributary to Red Butte Creek (RB_KF_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This resource contains the results of an experiment to test the effects of nutrients on stream biofilms at montane and urban sites in the Logan River, Red Butte Creek, and Middle Provo River watersheds located in northern Utah. We tested the effects of individual nitrogen and phosphorus additions and combined nitrogen and phosphorus additions at a series of concentrations on biofilm biomass using nutrient diffusing substrates (NDS). The Word document "methods_NDS" describes the methods used to construct the NDS and treatments included in our experiment.

At the end of the deployment period, biofilms grown on NDS were frozen. We measured chlorophyll a on half of the replicates and measured ash-free dry mass on the other half. The CSV file “biomass_nutrients_NDS” contains summary statistics (mean, standard deviation, count) of chlorophyll a concentrations and ash-free dry mass of biofilms on each nutrient treatment at our study sites. The Word document “methods_NDS” describes the analytical methods used to measure chlorophyll and ash-free dry mass.

We collected water column samples at each site for total and dissolved nutrient analyses. The CSV file “biomass_nutrients_NDS” contains total nitrogen, total phosphorus, ammonium, nitrate, and soluble reactive phosphorus concentrations at each site. The Word document “methods_NDS” describes the analytical methods used to measure nutrient concentrations.

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Utah Board of Water Resources Database
Created: July 13, 2016, 12:18 a.m.
Authors: Andrea Armstrong · Douglas Jackson-Smith

ABSTRACT:

This dataset consists of information on water infrastructure projects that were funded by the Utah Board of Water Resources within the Division of Water Resources, between March 1998 and June 2013. The database consists of three types of files: 1) pdf files of the publically available Board of Water Resources reports, which describe proposed and funded projects, 2) an Access database, in which researchers at Utah State University coded these reports across 341 variables, and 3) a geospatial database within which select infrastructure projects were digitized and spatially referenced. The geodatabase consists of line and point shapefiles, which represent a portion of the irrigation and municipal infrastructure projects financially supported by the Utah BWR.

Data were compiled from the 'board folders,' or summary reports of the Utah Board of Water Resources meetings. USU researchers developed a codebook (see the Access Database Variable Names document) to standardize the coding and categorization of information within board folders. Based on the coded information, projects were selected for digitization and creation of a shapefile (located within the geodatabase). Projects were hand-digitized using the National Hydrography Dataset and aerial imagery that corresponded with the time of project implementation.

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ABSTRACT:

The purpose of this effort is to track longitudinal changes in stormwater organizations’ plans and activities, as represented on annual reports submitted to the Utah Division of Water Quality. There are two datasets available in this effort: the pdf files of annual reports, and a dataset that organizes key information extracted from the reports in a table format.

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Water News Media Analysis
Created: July 14, 2016, 10:13 p.m.
Authors: Courtney Flint · Charles Mascher

ABSTRACT:

This dataset contains coded information from an analysis of articles about water gathered from two newspapers in Utah. Articles from the Salt Lake Tribune were assessed from 2012 through 2015 and articles from the Logan Herald Journal were assessed from 2012 through 2016). Articles were gathered by searching on line newspaper databases for articles using the keyword "water". After being sorted for relevance, articles with primary focus on water were coded for content and journalistic parameters using an online survey template developed within Qualtrics software. Intercoder reliability was established among the coding team.

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Red Butte Creek discharge, temperature, and conductivity dataset
Created: July 14, 2016, 10:34 p.m.
Authors: Michelle Barnes · Trinity Stout · Hyrum Tennant · Bethany Neilson

ABSTRACT:

This dataset contains discharge, temperature, and conductivity observations collected longitudinally along Red Butte Creek. Data was collected at approximately 38 sites intermittently dispersed from the Foothill Drive Aquatic Station to the Knowltons Fork Aquatic Station, including tributaries. Periodic data collection began in June of 2014 and continued through the summer of 2015. Measurements were made at each of the sites to capture pre/post snowmelt, summer (high ET) and fall (low ET) conditions. Discharge was measured either using a SonTek Flow Tracker (velocity-area method) or a dilution gaging method (using the YSI 600 OMS and a salt tracer). Temperature and conductivity were measured at each discharge site using the YSI 600 OMS. GPS coordinates for each discharge site were recorded using a Garmin® GPSMAP 64. The purpose for these measurements is to determine areas of significant groundwater-surface water interaction.

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Logan River discharge, temperature, conductivity, and chemistry datasets
Created: July 14, 2016, 11:01 p.m.
Authors: Bethany Neilson · Michelle Barnes · Trinity Stout · Hyrum Tennant

ABSTRACT:

This dataset contains discharge, temperature, conductivity, and ion concentration observations collected longitudinally along the Logan River. Data was collected at approximately 38 sites intermittently dispersed from the Mendon Road Aquatic Station to the Tony Grove Aquatic Station, including tributaries. Periodic data collection began in June of 2014 and continued through the summer of 2018. Measurements were made at each of the sites to capture pre/post snowmelt, summer (high ET), fall (low ET), and winter (Low ET) conditions. Discharge was measured using a SonTek Flow Tracker (velocity-area method). Temperature and conductivity were measured at each discharge site using the YSI 600 OMS. Ion samples were immediately filtered using either 0.7 um Whatman GF/F or 0.45 um Whatman Nylon Filters into acid-washed LDPE bottles and frozen (Chloride, Sulfate, Phosphate, Nitrate, Fluoride) or acidified with nitric acid (Sodium, Magnesium, Calcium, Potassium, Ammonium). All samples were transported via cooler to the lab where they were frozen until analysis. Samples were measured by ion chromatography on a Metrohm Compact IC. Standard curves were calibrated using independent NIST-traceable standards, and standards were run as unknowns to check analytical precision. GPS coordinates for each discharge site were recorded using a Garmin® GPSMAP 64. The purpose for these measurements is to determine areas of significant groundwater-surface water interaction.

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Provo River discharge, temperature, and conductivity dataset
Created: July 14, 2016, 11:24 p.m.
Authors: Michelle Barnes · Trinity Stout · Hyrum Tennant · Bethany Neilson

ABSTRACT:

This dataset contains discharge, temperature, and conductivity observations collected longitudinally along middle section of the Prove River. Data was collected at approximately 23 sites intermittently dispersed from the Charleston Aquatic Station to the USGS gaging station just below Jordanelle Dam, including tributaries. Periodic data collection began in June of 2014 and continued through August 2014. Measurements were made at each of the sites to capture pre/post snowmelt, summer (high ET) and fall (low ET) conditions. Discharge was measured using a SonTek Flow Tracker (velocity-area method). Temperature and conductivity were measured at each discharge site using the YSI 600 OMS. GPS coordinates for each discharge site were recorded using a Garmin® GPSMAP 64. The purpose for these measurements is to determine areas of significant groundwater-surface water interaction.

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ABSTRACT:

This review of literature compiles modeling effort that were undertaken for the Cache Valley, Utah, USA in groundwater (head and concentration), surface water, water quality (temperature, sediments, and chemical contaminants), and climate. In other words, this work is a compilation of the studies that included a modeling framework to model any of the above mentioned systems.

Most of the literature pertaining to the aquifer characterization models in Cache Valley were either obtained from government reports or unpublished work. The review of the literature points to the lack of the use of computer models that are available in the field to model the aquifer. The current models characterizing the aquifer in Cache Valley indicates the need for revising both the conceptual and computer models. The primary reason being differences in the characterization by different workers. However, there has been a steady buildup of conceptual models characterizing the aquifer.

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Water Management Adaptation to Climate Change in Utah
Created: July 15, 2016, 12:07 a.m.
Authors: Morey Burnham · Zhao Ma · Joanna Endter-Wada · Tim Bardsley

ABSTRACT:

This dataset contains interview data collected from policy makers and water managers in Utah. Interviews were conducted in 2013. Questions focused on water management challenges related to drought preparedness, climate change, population growth, urbanization, and water transfers, as well as water managers' modeling and information needs. Due to privacy concerns, interview transcripts are not provided. More details on the results of the interviews may be found here:

Burnham, Morey, Zhao Ma, Joanna Endter-Wada, and Tim Bardsley, 2016. Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk. Journal of the American Water Resources Association (JAWRA) 52(6):1366-1384. DOI: 10.1111/1752-1688.12459

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ABSTRACT:

This report summarizes results from my first year’s iUTAH fellowship (2012-13), which involved exploratory, qualitative research on local water management in the Wasatch Regional Metropolitan Area, specifically focusing on Cache Valley, Heber Valley, and the Red Butte Watershed of Salt Lake City, Utah. Data collection consisted of two types of activities: meeting observations and semi-structured interviews. I reviewed meeting notes and synthetic notes for prevailing themes, and distinguished between patterns that emerged both within and across the three study areas.

The structure of water management in the WRMA crosses macro-institutional, meso-watershed, and micro-individual scales. The focus of my research has been at the meso-scale, within which many local water management organizations (LWMOs) make critical decisions surrounding water quality and quantity. In this first phase of my work, I identify five types of key organization decisions made by LWMOs: operational, maintenance, water supply, infrastructure change, and enforcement. I then describe four types of linkages among WRMA water actors and provide examples of how these linkages impact LWMOs’ decisions. I then describe and analyze the ways in which LWMOs are making adaptive decisions in the face of key changes in urbanization and water availability. Two common adaptive processes are: (a) improving infrastructure efficiency, and (b) engaging in organizational partnerships. The report concludes with directions for future research. The LWMO interview instrument is included in the appendix.

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ABSTRACT:

The purpose of this research is to understand the experiences of and challenges faced within local water management. Data were collected using in-person and telephone interview methods. Interview participants consisted of stormwater managers in municipalities, irrigation companies, and private firms throughout Utah. Participants were selected based upon the types of management arrangements in place surrounding stormwater conveyance. In total, 30 municipal representatives, 10 irrigation company representatives, and 3 private sector representatives participated. Detailed findings and preliminary analyses are included in this report.

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T.W. Daniels Sapflux Aspen
Created: July 15, 2016, 9:26 p.m.
Authors: Allison Chan · David Bowling

ABSTRACT:

This data set contains 15-min sapflux data from 12 aspens at the T.W. Daniels Experimental Forest in Logan Canyon, along with meteorological and soil temperature and moisture measurements. The sapflux data are presented as raw data as well as processed data. Filtering steps were done to remove bad data- the intermediate filtering steps are also included for clarity. Sapflux data collection commenced on 13 May 2014 and continued until 12 July 2015. A complete description of the methods can be found in: AM Chan, (2015), "Tree Transpiration from Two Forests in the Wasatch Mountains, Utah", MS Thesis, Dept of Biology, University of Utah.

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Knowlton Fork Sapflux
Created: July 15, 2016, 10:17 p.m.
Authors: Allison Chan · David Bowling

ABSTRACT:

This is a complete data set that includes sapflux data from 12 aspens and 12 white firs at Knowlton Fork in Red Butte Canyon. Raw 15-min sapflux data for each tree along with processed data are included as well as met data for the site. The sapflux data are presented as raw data as well as processed data. Filtering steps were done to remove bad data- the intermediate filtering steps are also included for clarity. Sapflux data collection began on 23 August 2013 and continued until 5 December 2013 and was then re-started on 20 February 2014 and continued until 5 July 2015. A complete description of the methods can be found in: AM Chan, (2015), "Tree Transpiration from Two Forests in the Wasatch Mountains, Utah", MS Thesis, Dept of Biology, University of Utah.

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T.W. Daniels Sapflux Subalpine Fir
Created: July 16, 2016, 3:49 p.m.
Authors: Allison Chan · David Bowling

ABSTRACT:

This data set contains 15-min sapflux data from 12 subalpine firs at the T.W. Daniels Experimental Forest in Logan Canyon, along with meteorological and soil temperature and moisture measurements. The sapflux data are presented as raw data as well as processed data. Filtering steps were done to remove bad data- the intermediate filtering steps are also included for clarity. Sapflux data collection commenced on 24 March 2014 and continued until 12 July 2015. A complete description of the methods can be found in: AM Chan, (2015), "Tree Transpiration from Two Forests in the Wasatch Mountains, Utah", MS Thesis, Dept of Biology, University of Utah.

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RFA 3 Model Inventory
Created: July 16, 2016, 4:11 p.m.
Authors: David Rosenberg

ABSTRACT:

This dataset contains raw data, scripts, and plots used to analyze responses to the iUTAH Research Focus Area (RFA) 3 model inventory. The inventory was conducted via a Google Survey Form among RFA3 researchers on the RFA email list from August 2015 to October 2015. The purpose of the survey/inventory was to overview iUTAH RFA3 team's modeling efforts, map current efforts onto iSAW conceptual model (doi:10.1002/2014EF000295), and identify further opportunities to couple models as part of the RFA3 team's mission. Results herein are intended to help visualize results from the survey and productively encourage further discussion + coupling work.

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ABSTRACT:

This dataset reports the nitrogen isotope composition of leaves from 11 common riparian plant species collected from streams across the three iUTAH watersheds in October 2013 and July-August 2014. In addition, algae and moss samples were collected at many of the same sites on the Salt Lake Valley streams in September 2014. See the attached abstract and methods for more details.

Leaf samples were collected at 255 sites. Sites consisted of a ~ 30 m transect parallel to the stream, including both sides of the stream when possible. We sampled leaves from up to 11 species representative of the local flora when present (see spreadsheet for species names). Plants were only sampled if they were in close proximity (< 2 m) of the perennial channel or were visibly rooted in the stream. At each site, we collected 5 – 15 leaves from each species, including a mixture of mature sun and shade leaves from all parts of the plant. Where multiple individuals of the same species were present at the same site, we sampled leaves from up to five individuals, which were then composited by species. We sampled Salt Lake Valley sites during late September / early October 2013, and Cache and Heber Valley sites in late July 2014.

Please approach the algae/moss carbon isotope data with caution as carbonates were not removed prior to analysis; however, samples were thoroughly rinsed in deionized water to remove associated sediment.

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Effects of nutrient and pharmaceutical additions on stream biofilm biomass, function, and community composition
Created: July 16, 2016, 5:54 p.m.
Authors: Elizabeth Ogata · Donald Long · Michelle Baker · Zachary Aanderud · Emma Rosi · Trevor Smart

ABSTRACT:

This resource contains the results of an experiment to test the effects of nutrients and pharmaceuticals on stream biofilms at montane and urban sites in the Logan River, Red Butte Creek, and Middle Provo River watersheds located in northern Utah. We constructed contaminant exposure substrates (CES) by filling 1-oz plastic cups with agar amended with individual and combined additions of nutrients (nitrogen, phosphorus, iron) and pharmaceuticals (caffeine, diphenhydramine). The CSV file “treatments_CES” lists the contaminant treatments included in the CES experiment. We capped the agar with an inorganic (fritted glass disc) or organic (cellulose sponge) substrate to select for biofilm assemblages dominated by autotrophic and heterotrophic microbes, respectively, and then deployed CES in the river at each site for 18 - 26 days.

At the end of the deployment period, we used biofilms grown on CES to perform a series of in-stream incubations. We measured respiration and productivity using a modified light-dark bottle incubation method and nitrogen fixation using an acetylene reduction assay. We measured biofilm biomass (chlorophyll a, ash-free dry mass) and calculated Autotrophic Index values (calculated as chlorophyll a concentration divided by ash-free dry mass). The CSV file “biomass_function_CES” contains summary statistics (mean, standard deviation, count) of respiration rates, gross primary production rates, nitrogen fixation rates, chlorophyll a concentrations, ash-free dry mass, and Autotrophic Index values of biofilms on each contaminant treatment and substrate type at our study sites. The Word document “methods_CES” describes the analytical methods used to measure chlorophyll and ash-free dry mass.

To examine microbial community composition of biofilms grown on CES, were used target metagenomics of the 16S rRNA and 18S rRNA genes to identify bacterial and eukaryotic taxa, respectively. The Word document "methods_CES" describes our sequence analysis methods. The CSV files “bacteria_otu_CES” and “eukaryotes_otu_CES” list the number of sequences of each bacterial and eukaryotic OTU, respectively, in contaminant treatments. The CSV files “bacteria_tax_CES” and “eukaryotes_tax_CES” contain taxonomic classification information for bacterial and eukaryotic OTUs, respectively.

We characterized light availability, water temperature, and nutrient concentrations at each study site. The Word document "methods_CES" describes our methods for measuring these site characteristics and the analytical methods used to measure nutrient concentrations. The CSV file “site_characteristics_CES” contains percent canopy openness, transmitted incoming PAR, transmitted solar shortwave radiation, degree days, total nitrogen, total phosphorus, ammonium, nitrate, soluble reactive phosphorus, total dissolved iron, and total ferrous iron concentrations at each site.

We examined water column pharmaceutical concentrations at one site on each river using Polar Organic Contaminant Integrative Samplers (POCIS). POCIS were deployed for 20-26 days during low- and high-flow periods. The masses of 16 pharmaceuticals which had sorbed onto the POCIS were measured using high performance liquid chromatography combined with tandem mass spectrometry. We used the resulting pharmaceutical masses and uptake rates reported in the literature to calculate the time-weighted average concentration of each pharmaceutical. Average daily discharge was calculated using time series discharge data collected by the iUTAH project. The CSV file “POCIS_CES” contains time-weighted average concentrations of 16 pharmaceuticals and average daily discharge at each site during low- and high-flow periods.

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Red Butte Canyon meadow and lawn soil biogeochemical data
Created: July 16, 2016, 9:06 p.m.
Authors: Steven Hall

ABSTRACT:

Here we report biogeochemical data from two sites in the Red Butte Creek watershed, Todd's Meadow in Red Butte Canyon, and Sage Pt. lawn on the U of Utah Canyon. GPS coordinates (WGS 84) for these sites are: 40.789, -111.796462 and 40.763, -111.830, respectively. Data were collected from 2013 - 14 in the context of a snow manipulation at both sites. See the attached document for details. Data include: surface soil moisture, temperature, and oxygen mixing ratios, extractable nitrogen (N) pools, total soil N, N in soil lysimeters, HCl-extractable soil iron, nitrate isotope composition, soil potential denitrification rates. A manuscript describing methods in detail is included.

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Discharge Rating Curve at Red Butte Creek near Red Butte Gate Basic Aquatic Site (RB_RBG_BA)
Created: July 19, 2016, 8:10 p.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Red Butte Creek near Red Butte Gate Basic Aquatic Site (RB_RBG_BA). Discharge measurements were collected by a SonTek FlowTracker. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 12/31/2015. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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Red Butte Creek stream and groundwater ion concentrations
Created: July 18, 2016, 8:11 p.m.
Authors: Steven Hall

ABSTRACT:

Stream and groundwater samples were collected irregularly from August 2013 to November 2014 for analysis of major ions by ion chromatography. Sites included the Red Butte Creek GAMUT stations. Please see the published manuscript in Environmental Science & Technology for further details on sampling methods and analyses of these data.

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Utah Water Watch Evaluation Survey
Created: July 18, 2016, 8:29 p.m.
Authors: Brian T. Greene · Andrea Armstrong · Nancy Mesner

ABSTRACT:

We evaluated volunteers' opinions of the Utah Water Watch program to see if there are ways that Utah Water Watch can improve. We assessed volunteers' knowledge and attitudes about water quality and science, and how these may have changed based upon their participation in the program.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site near Todd's Meadow (RB_TM_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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Knowlton Fork, RBC, soil nitrogen data
Created: July 18, 2016, 8:40 p.m.
Authors: Samantha R Weintraub

ABSTRACT:

This dataset includes measurements of soil nitrogen pools and fluxes from two vegetation types (forest and herbaceous) and two landscape positions (upper and lower slopes) in the Knowlton Fork sub-catchment of Red Butte Creek watershed. Sites are located near the iUtah Knowlton Fork Climate Station, and measurements were made during June, August, and October of 2015. The dataset includes concentrations of inorganic nitrogen, soil nitrate isotope values, bulk concentrations and stable isotope values of soil organic carbon and nitrogen, concentrations of soil microbial biomass carbon and nitrogen, and nitrate leachate from below the rooting zone. Also included are carbon and nitrogen concentrations and isotope values from leaves.

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Utah Water Voices
Created: July 18, 2016, 8:59 p.m.
Authors: Courtney Flint · Charles Mascher

ABSTRACT:

A series of interviews were conducted during the summer of 2015 by a team led by Courtney Flint, working for Utah State University, funded by the iUTAH water project.

The purpose of the interviews was to get a general idea of public views and opinions of issues surrounding water.

The participants were asked a series of questions in a semi-structured conversational style. These conversations were recorded and then analyzed.

The interviews were conducted at various parks in Logan and Salt Lake City. They were selected via a public intercept method, where the interviewers selected park visitors at random and approached them to do interviews.

Afterwards, the interviewees filled out a short form with demographic information and consent to release. Demographic information is not being released with this dataset due to privacy issues.

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Development of a 'Water-Relevant Typology' of Urban Neighborhoods
Created: July 18, 2016, 9:35 p.m.
Authors: Douglas Jackson-Smith · Martin Buchert · Philip Stoker

ABSTRACT:

This dataset and technical report summarizes the methodology and results of a project to develop a water-relevant typology of urban neighborhoods for the greater Wasatch Range Metropolitan Area in northern Utah.

The technical report provides details about the original sources of data and analytic methodology deployed to create the typology. The work is also summarized in a peer-reviewed open-access article published in Cities and the Environment (Available at: http://digitalcommons.lmu.edu/cate/vol9/iss1/5 and copied below).

For users who wish to see copies of the underlying datasets (all aggregated at the census block group scale) for the study area, we have included a text file codebook and files in various formats (.csv, .xlsx, and .sav) for public use.

The effort was supported by the NSF-funded iUTAH project, and has been used to guide the design and implementation of an urban water observatory that captures social, built, and natural system characteristics.

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Discharge Rating Curve at Red Butte Creek near Foothill Drive Advanced Aquatic Site (RB_FD_AA)
Created: July 19, 2016, 10:03 p.m.
Authors: iUTAH GAMUT Working Group

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Red Butte Creek near the Foothill Drive Bridge (RB_FD_AA). Discharge measurements were collected by a SonTek FlowTracker. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 12/31/2015. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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Discharge Rating Curve at Red Butte Creek near Cottams Grove Basic Aquatic Site (RB_CG_BA)
Created: July 19, 2016, 10:26 p.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Red Butte Creek near Cottams Grove (RB_CG_BA). Discharge measurements were collected by a SonTek FlowTracker. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 12/31/2015. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site above Red Butte Reservoir (RB_ARBR_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on Red Butte Creek above Red Butte Reservoir (RB_ARBR_AA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Charleston Climate Site (PR_CH_C)
Created: July 20, 2016, 10:11 p.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site near Charleston (PR_CH_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Trial Lake Climate Site (PR_TL_C)
Created: July 20, 2016, 8:19 p.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site near Trial Lake (PR_TL_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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Discharge Rating Curve at Provo River near Soapstone Basin Aquatic Site (PR_ST_BA)
Created: July 20, 2016, 8:58 p.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Provo River near Soapstone Basin Aquatic Site (PR_ST_BA). Discharge measurements were collected by a HACH FH950 and Marsh McBirney Flo-Mate. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FH950 instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 9/28/2016. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on the Provo River near lower Midway (PR_LM_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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Discharge Rating Curve at Logan River near Tony Grove Basic Aquatic Site (LR_TG_BA)
Created: July 22, 2016, 1:07 a.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Logan River near Tony Grove Basic Aquatic Site (LR_TG_BA). Discharge measurements were collected by a SonTek FlowTracker or Marsh McBirney FlowMate 2000. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 6/30/2018. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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iUTAH GAMUT Network Raw Data at Spring Creek Storm Drain (LR_SC_SD)
Created: July 22, 2016, 1:18 a.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Logan River Network storm drain site near Spring Creek Storm Drain (LR_SC_SD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on the Logan River at the Main Street Highway 89/91 bridge (LR_MainStreet_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on the Logan River at Mendon Road/600 South (LR_Mendon_AA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Golf Course Climate Site (LR_GC_C)
Created: July 22, 2016, 6:38 p.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site near the Logan River Golf Course (LR_GC_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site near Franklin Basin (LR_FB_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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Discharge Rating Curve at Logan River near Franklin Basin Basic Aquatic Site (LR_FB_BA)
Created: July 22, 2016, 7:53 p.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Logan River near Franklin Basin Basic Aquatic Site (LR_FB_BA). Discharge measurements were collected by a SonTek FlowTracker and a Marsh McBirney Flo-Mate 2000. Measured stage and discharge and the curve are contained in the RatingCurve_LR_FBA_V3 . Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 6/30/2018. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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Social Vulnerability at the Census Place level
Created: July 22, 2016, 8:03 p.m.
Authors: Matthew Wheelwright

ABSTRACT:

This dataset uses Census Data following published social vulnerability index literature to provide an index at the Place level.

The Corps of Engineers has chosen SoVI as the “foundational SVA (Social Vulnerability Analysis) method for characterizing social vulnerability….” (Dunning and Durden 2013) The University of South Carolina has provided extensive and historic data for this methodology. Susan Cutter and her team have published their methodology and continue to maintain their database. Thus it was chosen as the “primary tool for [Army] Corps SVA applications.” (ibid) The downside is that this method is complex and hard to communicate and understand at times. (S. Cutter, Boruff, and Shirley 2003) The Social Vulnerability Index (SoVI) for this study was constructed at the U.S. Census Place level for the state of Utah. We utilized the conventions put forth by Cutter (2011) as closely as possible using the five-year American Community Survey (ACS) data from 2008 to 2012. The ACS collects a different, more expansive set of variables than the Census Long Form utilized in Cutter et al. (2003), which required some deviation in variable selection from the original method. However, Holand and Lujala (2013) demonstrated that the SoVI could be constructed using regional contextually appropriate variables rather than the specific variables presented by Cutter et al. (2003). Where possible, variables were selected which matched with the Cutter et al. (2003) work. The Principle Components Analysis was conducted using the statistical software R version 3.2.3 (R 2015) and the prcomp function. Using the Cutter (2011) conventions for component selection, we chose to use the first ten principle components which explained 76% of the variance in the data. Once the components were selected, we assessed the correlation coefficients for each component and determined the tendency (how it increases or decreases) of each component for calculating the final index values. With the component tendencies assessed, we created an arithmetic function to calculate the final index scores in ESRI’s ArcGIS software (ESRI 2014). The scores were then classified using an equal interval classification in ArcGIS to produce five classes of vulnerability, ranging from very low to very high. The SoVI constructed for our study is largely consistent with previous indices published by Susan Cutter at a macro scale, which were used as a crude validation for the analysis. The pattern of vulnerability in the state is clustered, with the lowest vulnerability in the most densely populated area of the state, centered on Salt Lake City (see Figure [UT_SoVI.png]). Most of the state falls in the moderate vulnerability class, which is to be expected.

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Utah's Counties: Sensitivity to Water Hazards
Created: July 22, 2016, 8:17 p.m.
Authors: Matthew Wheelwright

ABSTRACT:

This dataset contains important categories (per an extensive literature review) in relation to vulnerability to water hazards within Utah at the County level. Although social and physical vulnerability to water hazards (i.e. flooding) data has been collected extensively in many coastal areas, this is a costly problem in Utah and many other non-coastal areas. The variables shown here are categorized by type and collection method. 1. General data is shown for all Counties in Utah. These are taken from the 2010 Census. 2. Literature suggests that there are various approaches which local governments take to mitigate the impacts of flood events. Indicators of these approaches are captured in the section entitled Web Survey. A web survey was conducted of each County. The data includes evaluations of content including water hazard education, land use restrictions described in the code, freeboard requirements, and emergency operations plan implementations. 3. A social vulnerability index as created by the University of South Carolina is shown here. More information can be found at their website. 4. Event data is summarized for number of events and estimated monetary damages. This NOAA dataset helps us understand the nature of past experience and physical exposure to water hazards. Utah's Hazard Mitigation Plan 2014 includes a flood vulnerability score. It is included here for reference but is not critiqued as part of this dataset. 5. Fema has modeling software known as HAZUS which can be used to estimate damages for certain hazards including flooding. A county level summary is included here with estimated of building damage and exposure. 6. Dams are a man-made structure which play a part on flood management and can also create additional exposure. 7. Much of social vulnerability and disaster management should consider those with special needs. Census and the Division of Hazard Mitigation of Utah help us understand more of this important context.

Together these data paint a picture of Utah's vulnerabilities to flood hazards and potential exposure to other natural hazard events. Place level statistics were also collected and add insight at that spatial scale. they can be found here: http://repository.iutahepscor.org/dataset/hazard-mitigation-and-capacity-in-utah-census-places. The variables are different as prescribed in the readme file there.

Further details of the data collection methods can be found in the data dictionary within the spreadsheet workbook or in the ReadMe file included as a resource here.

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ABSTRACT:

This dataset contains important categories (per an extensive literature review) in relation to vulnerability to water hazards within Utah at the Census Place level (i.e. cities). Although social and physical vulnerability to water hazards (i.e. flooding) data has been collected extensively in many coastal areas, this is a costly problem in Utah and many other non-coastal regions. The variables shown here are categorized by type and collection method. 1. General data is shown for all Census Places in Utah including County, Geocode, and Total Population. These are taken from the 2010 Census. 2. Literature suggests that there are various approaches which local governments take to mitigate the impacts of flood events. Indicators of these approaches are captured in the section entitled Web Survey. A web survey was conducted of each and every census place in Utah. The data includes evaluations of content including water hazard education, land use restrictions described in the code, freeboard requirements, and emergency operations plan implementations. 3. Information about the local government including their planning and building inspector staff was collected using a phone survey along with emails and website investigations. 4. FEMA data was consolidated from FEMA's website showing census places with current insurance premium discounts achieved by demonstrating compliance with certain federal requirements. It also includes data on policies and losses. 5. A social vulnerability index was created by our team for this project and details can be found here: http://repository.iutahepscor.org/dataset/social-vulnerability-at-the-census-place-level. This dataset includes summary findings from the SoVI index. 6. As housing is recognized in the literature as a contributer to natural hazard vulnerability, important housing statistics were defined and created from Census data. These include housing age, median value, and renter occupied statistics. A standardized rating of building code effectiveness is also included from a recent Utah Hazard Mitigation Report. 7. Event data is summarized for number of events and estimated monetary damages from another of our team's datasets found here: http://repository.iutahepscor.org/dataset/noaa-storm-events. This NOAA dataset helps us understand the nature of past experience and physical exposure to water hazards. 8. As this dataset is focused on water hazard exposure, two measurements were calculated for each census place reflecting the percentage area of the city included in the defined special flood hazard area.

Together these data paint a picture of Utah's vulnerabilities to flood hazards and potential exposure to other natural hazard events. County level statistics were also collected and add insight at that spatial scale. they can be found here: http://repository.iutahepscor.org/dataset/utah-s-counties-sensitivity-to-water-hazards. The variables are different as prescribed in the readme file there.

Further details of the data collection methods can be found in the data dictionary within the spreadsheet workbook or in the ReadMe file included as a resource here.

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NOAA Flood Events
Created: July 22, 2016, 10:11 p.m.
Authors: Matthew Wheelwright

ABSTRACT:

This dataset contains event history for floods in Utah based on the NOAA weather database. It has been dis-aggregated to census place for alignment with other compatible databases in order to analyze local history and experience. The readme file elaborates on the methods of disaggregation. It includes data from 1997-2014, but more reliable data is separated for 2010-2014 after a change in NWS procedure and event recognition.

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Changes of Agricultural Land Use in WRMA
Created: July 22, 2016, 10:25 p.m.
Authors: Enjie Li

ABSTRACT:

This dataset documents the historical agricultural land use changes in WRMA from 1986 to 2014. We extracted agricultural land uses from the Water Related Land Use Dataset. Agricultural land uses include non-irrigated agricultural land (NI), irrigated agricultural land (IR), and sub-irrigated agricultural land (SubIR).

This dataset includes five years' GIS layers of agricultural land use in WRMA, namely, 1986, 1992, 2003, 2009, and 2014. Also, a statistical summary of the historical agricultural land use is provided.

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Future WRMA's Land Use Dataset
Created: July 22, 2016, 10:41 p.m.
Authors: Enjie Li

ABSTRACT:

This dataset contains the urban growth simulation results of future land use in 2040 of the Wasatch Range Metropolitan Area (WRMA) .In this study, we defined the WRMA as a broad, ten-county region that surrounds the Wasatch Mountain Range east of the Great Salt Lake and Salt Lake City in Utah. This region encompasses four Wasatch Front counties west of the mountain range (Weber County, Davis County, Salt Lake County, and Utah County), three Wasatch Back counties east of the mountain range (Morgan County, Summit County, and Wasatch County), and three counties neighboring the Wasatch Front (Cache County, Box Elder County, and Tooele County).

SLEUTH-3r urban growth simulation model is used to generate this dataset. Detailed SLEUTH model protocol can be found at: http://www.ncgia.ucsb.edu/projects/gig/index.html. The data used to run the SLEUTH-3r model include National Land Cover Database 2001, 2006, and 2011, US Census TIGER/Line shapefile for 2000 and 2011, United States Geological Survey 7.5 min elevation model, and Utah Landownership map from Utah Automated Geographic Reference Center.

Three alternative scenarios were developed to explore how conserving Utah’s agriculturale land and maintaining healthy watersheds would affect the patterns and trajectories of urban development:
1) The first scenario is a “Business as Usual” scenario. In this scenario, federal, state, and local parks, conservation easement areas, and surface water bodies, were completely excluded (value = 100) from development, and all the remaining lands are were naively assumed as developable (value = 0). This is the same excluded layer that was also used during model calibration. Under this scenario, we hypothesized that future urban grow will occur following the historical growth behaviors and trajectories and no changes in land designation or policies to restrict future growth will be implemented.
2) The second scenario is an “Agricultural Conservation” scenario. Within the developable areas that we identified earlier, we then identified places that are classified by the United States Department of Agriculture (USDA) as prime farmland, unique farmland, farmland of statewide importance, farmland of local importance, prime farmland if irrigated, and prime farmland if irrigated and drained. Each of these classes were assigned with an exclusion value from urban development of 100, 80, 70, 60, 50, and 40 respectively. These exclusion values reflect the relative importance of each farmland classification and preservation priorities. By doing so, the model discourages but does not totally eliminate growth from occurring on agricultural lands, which reflects a general policy position to conserve agricultural landscapes while respecting landowners’ rights to sell private property.
3) A “Healthy Watershed” scenario aims to direct urban growth away from areas prone to flooding and areas critical for maintaining healthy watersheds. First, we made a 200-meter buffer around existing surface water bodies and wetlands and assigned these areas an exclusion value of 100 to keep growth from occurring there. In addition, we assigned areas that have frequent, occasional, rare and no-recorded flooding events with exclusion values of 100, 70, 40 and 0 accordingly. We also incorporated the critical watershed restoration areas identified by the Watershed Restoration Initiative of Utah Division of Wildlife Resources (https://wri.utah.gov/wri/) into this scenario. These watershed restoration areas are priority places for improving water quality and yield, reducing catastrophic wildfires, restoring the structure and function of watersheds following wildfire, and increasing habitat for wildlife populations and forage for sustainable agriculture. However, there are not yet legal provisions for protecting them from urbanization, so we assigned these areas a value of 70 to explore the potential urban expansion outcomes if growth were encouraged elsewhere.

Future land use projections of 2040 are in GIF format, which can be reprojected and georeferenced in ArcGIS or QGIS, or be read directly as a picture.

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Swaps and Persistence of WRMA's 30 years' Land Use Changes
Created: July 23, 2016, 2:36 p.m.
Authors: Enjie Li

ABSTRACT:

The most traditional way to examine land use change is to use a cross-tabulation matrix to identify the most important categorical land use transition from time 1 to time 2. However, such method does not necessarily capture or indicate the real changes on the landscape. For example, assuming that from 1986 to 2015, Utah’s total agricultural land loss (aka, net change) is 200 square miles, but this does not mean that only 200 square miles of agricultural land have experienced land use change in the last 30 years. It is highly possible that a given quantity of agricultural land loss at one location can be accompanied by another quantity of agricultural land gain at another location (aka, swapping). Thus, by purely using net change, we might fail to capture the swapping component of change, and fail to capture the intricate transitions of landscape. This dataset analyzed important categorical land use change while account for persistence and swaps. It provides additional information concerning what happened on the landscape.

This dataset includes a statistical table and a GIS raster file. The table summarizes the persistence and swaps, as well as gross gain and gross loss in the Wasatch Range Metropolitan Area (WRMA). The GIS file is the compiled spatial layer that represents the gain, loss, persistence, and swaps on the landscape. We used Water Related Land Use data of Year 1986 to Year 2015 for this analysis. Land use categories used in this dataset include urban (URB), irrigated agricultural land (IR), and non-irrigated agricultural land (NI), sub-irrigated agricultural land (SubIR), riparian (RIP), water, (WATER), and other (OTHER). We then examined the categorical land use changes with a transition matrix.

A categorical land use gain is determined as the conversion from other sources to this particular categorical land use, and a categorical land use loss is defined as conversion from this particular categorical land use to other uses. For example, the gain of irrigated agricultural (IR) land use will be the sum of areas of urban to IR, non-irrigated agricultural land to IR, sub-irrigated agricultural land to IR, riparian to IR, water to IR, and other to IR. The total change is calculated as the sum of gain and loss. The net change equals to |Gain|-|Loss|. The Swap =2* MIN(Gain,Loss).

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Important categorical land use changes from 2001-2011
Created: July 25, 2016, 5:01 p.m.
Authors: Enjie Li

ABSTRACT:

This dataset documents the important categorical land use changes from 2001 to 2011 for the basins in the Wasatch Range Metropolitan Area (WRMA). Four cross-tabulation matrixes are provided, to summarize the changes of categorical land uses at Bear River Basin, Weber River Basin, Utah Lake Basin and Jordan River Basin.

These matrixes are useful to compare two maps of land use from different times, and to understand the categorical land use transitions over the time. By breaking down the whole WRMA into four sub-regions, these matrixes also help to compare the different patterns and processes of land use change among the four river basins.

We used year 2001 and 2011 National Land Use and Land Cover Dataset (NLCD) to produce these matrixes. Land use categories used in this dataset include: Water, Development/Open Space, Development/Low Density, Development/ Medium Density, Development /High Density, Barren, Forest, Scrubland, Grassland, Pasture, Cultivated Crops, and Wetland.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on Red Butte Creek near the gate (RB_RBG_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on the Logan River near Tony Grove (LR_TG_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on the Logan River near Franklin Basin (LR_FB_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset includes nitrogen content (% dry mass) and stable isotopic composition of several lichen species within and surrounding the Salt Lake City metropolitan area.

This study focused on the nitrogen content and stable nitrogen isotope ratio of lichens on an elevational gradient along Red Butte Creek and Grandeur Peak to determine if lichens hold a record of inversion-based nitrogen deposition. After plotting the nitrogen content of the various samples it was determined that lichens do not hold a record of inversion-based nitrogen deposition.

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ABSTRACT:

Researchers at Utah State University created a short survey instrument to gather information about the views and concerns of Utah residents related to water issues. This survey was designed to give the public a chance to share their perceptions and concerns about water supply, water quality, and other related issues. While finding out what the ‘average citizen’ feels about key water issues was one goal of the project, the most interesting and important results are found in exploring ways in which perspectives about water vary across the population based on where people live and their demographic background (gender, age, education, etc.). This survey helps bring a voice to groups of citizens typically not represented in water policy debates. The findings have been and continue to be shared with water managers and decision makers who are planning for local and state water system sustainability.

This survey effort is also a key outreach and education component of the iUTAH project. High school groups, college and university classes, and others are invited to collaborate with iUTAH faculty to conduct public intercept surveys. Co-collection and analysis of survey data provides a hands-on learning opportunity about the principles of social science research. This effort helps increase awareness about the complexity of water issues in Utah, and the methods through which scientists learn about the public’s thoughts and concerns. Between July 2014 and April 2016, the survey has been implemented with collaborating students and faculty from the University of Utah, Utah Valley University, Weber State University, Salt Lake Community College, Southern Utah University, Dixie State University, and Snow College.

The survey involved using a structured protocol to randomly approach adults entering grocery stores in communities across the state, and inviting them to complete a 3-minute questionnaire about thier perceptions and concerns about water issues in Utah. The survey was self-administered on an iPad tablet and uploaded to a web server using the Qualtrics Offline App.

The project generated responses from over 7,000 adults, with a response rate of just over 42% . Comparisons of the respondents with census data suggest that they are largely representative of the communities where data were collected and of the state's adult population.

The data are anonymous and are available as a public dataset here. The data also served as the basis for the development of an open-source web-based survey data viewer that can be found at: http://data.iutahepscor.org/surveys/ and were also reported in Jones et al. (2016). We encourage users to use the viewer to explore the survey results.

The files below include a document describing in detail the method/protocol used in the study, and copies of field materials we used to implement the project. We also include copies of the full dataset and a codebook in various formats.

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Discharge Rating Curve at Logan River near Main Street Bridge Basic Aquatic Site (LR_MS_BA)
Created: July 25, 2016, 10:38 p.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Logan River near Main Street Bridge Basic Aquatic Site (LR_MS_BA). Discharge measurements were collected by a SonTek FlowTracker. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 6/30/2018. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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Discharge Rating Curve at Logan River near Water Research Laboratory Advanced Aquatic Site (LR_WL_AA)
Created: July 25, 2016, 10:54 p.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Logan River near Water Research Laboratory West Bridge Advanced Aquatic Site (LR_WL_AA). Discharge measurements were collected by a SonTek FlowTracker. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 6/30/2018. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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Discharge Rating Curve at Logan River near Mendon Road Advanced Aquatic Site (LR_MR_AA)
Created: July 25, 2016, 11:12 p.m.
Authors: iUTAH Cyberinfrastructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site on Logan River near Mendon Road Advanced Aquatic Site (LR_MR_AA). Discharge measurements were collected by a SonTek FlowTracker. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 9/30/2016. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network aquatic site on Red Butte Creek near the Foothill Drive Bridge (RB_FD_AA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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FPOM and DOM isotope values
Created: July 26, 2016, 7:13 p.m.
Authors: Julie Kelso · Michelle Baker

ABSTRACT:

This dataset contains Carbon, Nitrogen, and Deuterium isotope values for Fine Particulate Organic Matter, Dissolved Organic Matter, Dissolved Inorganic Carbon, Dissolved Nitrate, and water for 4 watersheds in Utah. Samples were collected in September and November of 2014 and November and December of 2015. Eight sites in the Provo River, Logan River, and Red Butte Creek and 9 sites on the Jordan River were sampled.

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Wasatch Mountain Voices
Created: July 26, 2016, 7:23 p.m.
Authors: Courtney Flint · Brett Miller · Kent Taylor Dean

ABSTRACT:

The Wasatch Mountain Voices Project seeks to assess perceptions of values and vulnerabilities associated with the Wasatch Mountains. The connection to iUTAH research focuses on the degree to which water is mentioned by key informants interviewed for this project. A team of undergraduate research assistants assisted with this project and conducted interviews. It should be noted that this effort was a learning experience for students and a few inherent limitations are found in the flow of the interviews as a result of students in early stages of climbing the interview learning curve. We acknowledge some leading aspects in interview questions. However, a standard set of questions was asked in all interviews.

Interviews were conducted with representatives of the following categories:

1. City Planners
2. Emergency Managers
3. Natural Resource Managers (state or federal)
4. Representatives from environmental interest groups or organizations
5. Representatives of recreational interests
6. Representatives of Real Estate, Commercial/Economic or Development Interests

We used web-based information and existing contacts in the region to identify people in the categories to sample from for interviews. Interviews were largely held in person, but sometimes by phone. Key informant interviews followed a semi-structured format and lasted from 30 to 60 minutes.

While 90 people were originally interviewed, 2 were not audio recorded and 7 were people who declined to share their anonymous transcript. Thus this dataset contains 81 complete interview transcripts. Interviews were conducted with people from five different regions: Northen Wasatch, Central Wasatch, Wasatch Front, Wasatch Back, and Southern Wasatch. Interviews were held at a location convenient to the participant.

At the outset of the interviews, participants were presented with a letter of information describing informed consent procedures. When consent was given, interviews were audio recorded. Participants were given the opportunity to choose whether or not they want to be identified in project reporting. For those choosing not to be identified, any identifying information was redacted from transcripts.

Transcripts made from audio files used an ID system for identification and were created using NVivo software. Though initially planned to be shared, audio interview files were deleted upon the request by USU IRB.

The questions guiding the interviews were as follows:

1. How do the Wasatch Mountains influence the wellbeing in this area? In other words, what are some of the values or benefits of living in the Wasatch Mountain Region?
2. Are there any disadvantages or particular vulnerabilities related to the Wasatch Mountains that compromise or decrease wellbeing in this area?
3. What do you think are the key issues regarding the future sustainability and wellbeing of the Wasatch Mountain Region?
4. Are you aware of any efforts underway to help sustain or improve the wellbeing of the Wasatch Mountain Region in the future? Are you – or is your organization - involved in these efforts? Can you talk more about these efforts?

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Groundwater Quality Data from Private Wells in Cache Valley
Created: July 26, 2016, 7:32 p.m.
Authors: Joshua Gathro · William Fullmer

ABSTRACT:

This dataset contains data on water samples collected from 9 private wells in Cache Valley. All of the samples were taken in May and June of 2015. The sampled wells were either under pressure and required only a release of lever/knob for water to flow, or had a pump that brought water to the surface. The depth of wells varied from 50 feet to 300+ feet. Sample locations were limited to the areas within or directly surrounding Logan, Mendon, Clarkston, and Smithfield. The water samples were analyzed for pH, DO, As (III), As (V), Fe (II), Sulfide, Anions, Total Metals, and Organic Carbon.

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Snow Chemistry Data
Created: July 26, 2016, 8:08 p.m.
Authors: Greg Carling · Dylan Dastrup

ABSTRACT:

This dataset includes chemistry data from snowpack samples collected across the iUTAH watersheds during spring 2014 and 2015. The field sampling was a collaborative effort by the iUTAH Snow Sampling Team. The chemistry data include stable water isotope ratios (d18O and dD), trace and major element concentrations, and 87Sr/86Sr ratios for selected samples.

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Water Use Data by Municipality, 2010
Created: July 26, 2016, 10:18 p.m.
Authors: Douglas Jackson-Smith

ABSTRACT:

These data reflect estimates of the water use for various purposes for each of Utah's public water systems. The data were originally collected by the Utah Division of Water Rights in their annual surveys of public water systems, then cleaned and checked by staff at the Utah Division of Water Resources. Estimates are made for residential, commercial, industrial, and institutional users, and separates water used from domestic/potable water sources and secondary irrigation water supplies. The data were obtained from UDWR staff and compiled by Douglas Jackson-Smith and his students in 2014 and 2015.

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ABSTRACT:

These data reflect results of a household survey implemented in the summer of 2014. The survey randomly sampled households from 23 neighborhoods (census block groups) across 12 cities and 3 counties. Neighborhoods were purposively selected to represent different configurations of social, built, and natural environmental characteristics using the "iUTAH Urban Typology" (https://www.hydroshare.org/resource/84f00a1d8ae641a8af2d994a74f4ccfb/). Data were collected using a drop-off/pick-up methodology, and produced an overall response rate of over 62% (~2,400 respondents). The questionnaire included detailed questions related to household water use and landscaping behaviors, perceptions of water supply and quality, participation in water based recreation, concerns about water issues, and preferences for a range of local and state water policies.

Here we are making public an anonymized version of the large household survey dataset. To protect the identity of respondents, we have removed a few variables and truncated other variables.

Files included here:
englishsurveys and spanishsurveys: These folders contain the survey questionnaires used specific to each neighborhood.
Codebook in various formats: Tables (xls and csv files) with a list and definition of questions/variables, which correspond to the columns in the data files, and the encoding of the responses.
Dataset in various formats: Tables (csv, xls, sas, sav, dta files) containing numeric responses to each question. Each participant's responses correspond to a row of data. Each question corresponds to a column of data. Interpretation of the coded responses is found in the data codebook.
Maps: maps of the neighborhoods surveyed.
SummaryReports: Summaries of the results that compare across three counties, summary reports for each county, highlight reports for each city.

Summary reports are also available at http://data.iutahepscor.org/mdf/Data/household_survey/ including an overall report that provides comparisons of how these vary across the three counties where we collected data (Cache, Salt Lake, and Wasatch) as well as summary reports for each county and highlights reports for each city.

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ABSTRACT:

This dataset includes sub-watershed delineations created for ~66 stream sites across the three iUTAH GAMUT watersheds, Logan River, Red Butte Creek, and Provo River (including GAMUT Aquatic stations: gamut.iutahepscor.org ), where monthly water quality samples were collected 2013-2014. Sub-watershed delineations will allow for analysis of the landscape contributing to these sites, which can then be used in models of water quality for the stream sites. This will contribute to the iUTAH goal of modeling the impact of land-use changes on in-stream water quality.

Delineations were generated from 10 m DEMs (Utah GIS portal) using ArcMap tools: mosiac, fill, flow direction, flow accumulation, snap pour point, watershed and raster to polygon. Default settings were used for all tools.

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Attitudes towards Water on a University Campus--Qualitative Data
Created: July 26, 2016, 10:55 p.m.
Authors: Carla Trentelman · Daniel Bedford · Carla Trentelman

ABSTRACT:

This dataset contains qualitative social science data collected at Weber State University, as part of the social science research focus area of iUTAH. Data were collected through nine focus groups and seven face-to-face interviews, all conducted with diverse WSU stakeholders. The dataset is comprised of summary reports from the focus groups and interviews.

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ABSTRACT:

This dataset contains biomass, nutrient and metal concentrations for soils at the Green Meadows Subdivision's Bioretention Field Site. This study assessed increase of pollutant concentrations from stormwater accumulation. Data begin in 2011 and continue through 2014. No data was collected in 2015.

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ABSTRACT:

This dataset contains various water quality variables for stormwater runoff samples collected at the Green Meadows Subdivision Bioretention Field Site, to assess pollutant . Data begin in 2011 and continue through 2015. Data were collected manually or with an ISCO automatic sampler (2013 only).

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ABSTRACT:

This dataset contains biomass, nutrient and metal uptake variables for plants grown at the Green Meadows Subdivision Bioretention Field Site. The purpose of this study was to assess the accumulation potential of pollutant of interest from stormwater runoff and how this differs among the three macrophyte species. Data begin in 2011 and continue through 2015. Plants were harvested mid season (June-July) and/or at the end of season (Sept-Oct).

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Aquatic GAMUT Bacterial Community Target Metagenomics-454 Pyro
Created: July 27, 2016, 12:36 a.m.
Authors: Erin Jones · Zach Aanderud

ABSTRACT:

This data was collected as part of a study to understand the connectivity and diversity of stream bacteria communities in streams flowing from high to low elevation through different types of urbanization and in different seasons. The dataset contains OTU (operational taxonomic units, the bacterial surrogate for species) abundance for bacteria at iUTAH aquatic GAMUT sites (http://data.iutahepscor.org/mdf/Data/Gamut_Network/) in three watersheds in September 2014. Briefly, water column samples were filtered onto 0.2 um membrane filters, which were dissolved and processed with MOBIO Power Soil DNA extraction kits. We sequenced bacterial DNA (PCR-amplified using V4-region specific primers) using 454-pyrosequencing (an older sequencing method with more limitations). We cleaned, clustered (using 97% OTU similarity cut-off) and aligned sequences using the Schloss 2011 protocol, and classified OTUs to taxonomy based on the SILVA bacteria database. Code used for analysis is available at https://github.com/erinfjones/mothurcode.
There are three files; site and sample metadata (e.g. date sampled) is included in the file stream_design.txt, observed OTU counts by sample are in the .shared file, and the taxonomic classification of OTUs is in the .taxonomy file.

Schloss PD, Gevers D, Westcott SL. (2011). Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies. PloS ONE. 6:e27310.

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Green Roof Evapotranspiration
Created: July 27, 2016, 1:31 a.m.
Authors: Youcan Feng · Steven Burian

ABSTRACT:

The dataset records the observed evapotranspiration time series from the green roof of the Marriott Library on the University of Utah's campus for the year 2014. Three weighing lysimeters were set up to represent three types of the surface cover including non-vegetated medium, sedum, and bluegrass. Daily values (mm/day) were recorded. The data collection was primarily funded by the Sustainable Campus Initiative Fund from the Office of Sustainability at the University of Utah, the Graduate Student Research Funding from the Global Change and Sustainability Center at the University of Utah, and iUTAH.

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ABSTRACT:

This dataset consists of .kml and .kmz files identifying locations of green infrastructure projects implemented on the University of Utah campus. The locations are current as of 2013 and may be updated.

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Precipitation chemistry along an elevation gradient in Red Butte Canyon, Utah
Created: Aug. 3, 2016, 11:07 p.m.
Authors: Dasch Houdeshel

ABSTRACT:

Precipitation samples were collected at five elevations between 4880 m and 6255 m for three storm events in the winter of 2014 to observe changes in inorganic nitrogen concentrations in the precipitation for different elevations of Red Butte Canyon.

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ABSTRACT:

Ion concentrations and precipitation amount were measured at 14 sites in the Salt Lake and Cache Valleys from December 2013 to February 2014. Sample collection was sporadic at several sites. The goal of this study was to identify land use impacts on nitrogen deposition to the iUTAH watersheds.

A subset of samples was analyzed for 15N and 18O of NO3 and 15N of NH4.

Methods and findings are described in the associated JGR-B manuscript

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Red Butte Creek Network site near 900 W (1300 South) Basic Aquatic Site (RB_900W_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Flood Canal (PR_Flood_canal)
Created: Aug. 4, 2016, 1:18 a.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Provo River Network flood canal site adjacent to the Sage Creek Canal. Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Provo River Network site at Sage Creek Canal (PR_SageCreek_canal). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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GAMUT Water Chemistry Data
Created: Aug. 5, 2016, 4:16 p.m.
Authors: Greg Carling · Dylan Dastrup · Timothy Goodsell

ABSTRACT:

This dataset contains water chemistry data from samples collected at GAMUT sites and other locations in Logan, Red Butte, and Provo River watersheds during 2014-2015. Chemistry includes field parameters, stable water isotopes, 87Sr/86Sr ratios, major ions, and trace element concentrations.

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GIRF moisture data
Created: Aug. 5, 2016, 4:09 p.m.
Authors: Pratibha Sapkota

ABSTRACT:

The dataset contains soil moisture data in three GIRF bioretention cells at different depths (10cm, 20cm, and 50cm). Soil moisture was measured using CS616-L soil moisture sensors (Campbell Scientific, Logan, UT). The data loggers were placed at the center of each bioretention at 10 cm, 20 cm, and 50 cm depth in upland and control cells. In the wetland, the data loggers were placed at 25cm and 50cm. Data was collected every 15 minutes and were averaged over a day. Data were recorded from Jan 2012 to May 2015. The unit is in percentage.

Details on GIRF bioretention and schematic is attached.

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Analysis of bioretention area at 300 East in Logan UT
Created: Aug. 5, 2016, 5:18 p.m.
Authors: Trixie Rife

ABSTRACT:

This dataset contains nutrient loads from storm events near a bioswale along a street in Logan UT. The purpose of this study was to analyze the nutrient and pollutant load in stormwater that is entering the bioretention area. Samples were collected from the gutter along the street and from in the biorentention basin. Road samples were collected using syringes and Nalgene sample bottles. The basin samples were collected using suction cup water samplers installed in the ground to collect pore water. Weather data is also included in the dataset. The weather data was collected using HOBOware instruments for wind direction and speed, temperature, relative humidity, and rain. All data was collected on a datalogger. The soil pore water was analyzed to determine movement through the soil of the nutrients and pollutants. Water samples were analyzed at the Utah Water Research Lab for nutrients, metals (copper, zinc, lead, arsenic, cadmium, selenium), and dissolved organic carbon.

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Measuring Transpiration of Irrigated Landscape Trees in a Semi-arid Urban Environment
Created: Aug. 5, 2016, 5:06 p.m.
Authors: Michael Bunnell

ABSTRACT:

The Heber Valley (Wasatch County, Utah) is a developing landscape where populations are projected to grow 90% by 2030 (Utah, 2014). I expect that afforestation will accompany population growth and urban expansion in this region, placing greater demand on the valley’s water resources. My study is aimed at understanding the influence of afforestation on water use in a built environment where water resources are limiting. I am currently collecting sap flux measurements on mature trees within this system with the following questions in mind: (1) Are there quantifiable species-specific differences in transpiration based on evolutionary lineage, where angiosperm and gymnosperm species have functionally distinct wood anatomy? Additionally, are there differences between native and introduced species as a function of local adaptation? (2) What impact does the transition from a rural to urban landscape, and the accompanying planting choices, have on water resource use? These questions have practical management applications in terms of tree selection and determining how much water should be allocated to irrigating urban landscapes.

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Green roof invertebrate biodiversity
Created: Aug. 5, 2016, 5:50 p.m.
Authors: Jacqualine Grant · Youcan Feng · Wallace, Hailey M. · Steven Burian · Weeg, Matthew S.

ABSTRACT:

Green roofs were designed by civil engineers to insulate buildings, protect buildings from ultraviolet light, and slow stormwater runoff. However, from a biologist’s perspective they are an untapped resource for growing crops and native plants that support pollinators. Two basic assumptions about green roofs are (1) that they provide more habitat for invertebrates than normal roofs, and (2) that approach the same level of biodiversity as ground level sites. The first assumption is so basic that it has rarely been tested. We compared biodiversity on a green roof composed of plants from a commonly used genus in the green roof industry, sedums, with biodiversity on an asphalt tile roof. To test the second assumption we compared biodiversity on a green roof of plants that contained a mix of native and nonnative plants to ground level sites in the immediate vicinity. Surprisingly, invertebrate biodiversity on a sedum roof was not different from that of an asphalt tile roof containing no vegetation. Biodiversity on the mixed native plant green roof did, however, approach similar levels of biodiversity to nearby ground level sites. We conclude that for green roofs to be functional from both engineering and biological perspectives, they must include a diverse array of plants. We are now testing a variety of native plants from Utah to determine their suitability for green roof installations. The data are limited to 2014 and include two separate sites: the greenroof-asphalt roof paired sites at Southern Utah University in Cedar City, Iron County, Utah, and the greenroof-ground level paired sites at the University of Utah, Salt Lake City, Salt Lake County, Utah.

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TN-TC change in bioretention cells at GIRF
Created: Aug. 6, 2016, 12:16 a.m.
Authors: Pratibha Sapkota

ABSTRACT:

This dataset contains Total Nitrogen and Total Carbon in nine bioretention cells over a period of three years. Composite soil samples from each garden were collected once every year in October.
Total Nitrogen/Carbon was determined by the combustion method based on Dumas method(1). The instrument used for analyzing is Elementar Vario Max Cube.
Units are in percentage which is the percent of the total mass.

Details on GIRF bioretention and schematic is attached.

1. Total Nitrogen and Carbon by Combustion In Soil, Plant and Water Reference Methods for the Western Region (WREP 25). 2005. 3rd Edition. R. Gavlak, D. Horneck, R. O. Miller. pp. 116-117.

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Soil pH at GIRF
Created: Aug. 6, 2016, 12:25 a.m.
Authors: Pratibha Sapkota

ABSTRACT:

Soil pH was measured on a 1:5 (v/v) soil water suspension with a digital pH meter (Mettler Toledo FG-2 FiveGo Portable pH Meter). The dataset contains soil pH over a three years period from August 30, 2013, to December 6, 2015. We decommissioned three older treatments and three newer (upland, control, and wetland- 1-6) in May 2015. Therefore, we only have data from three bioretention cells from May onwards.

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PLFA/NLFA in bioretention systems at GIRF
Created: Aug. 6, 2016, 12:33 a.m.
Authors: Pratibha Sapkota

ABSTRACT:

The dataset contains different types of bacteria and fungi present in soils of GIRF bioretention. Two sets of samples were taken for the study. We took first set of samples in Oct 2013, and the second set of samples in May 2015. Phospholipid Fatty Acid (PLFA) reflects the occurrence of mainly living organisms or recently dead organisms. Neutral Lipid Fatty Acid(NLFA) indicates the energy stored. Phospholipid fatty acid (PLFA) analysis was performed using an Agilent 7890A gas chromatograph with an Agilent 5975C series mass selective detector. All units are in nmol/gm of soil.

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C & N in plants biomass in bioretention systems at GIRF
Created: Aug. 6, 2016, 12:40 a.m.
Authors: Pratibha Sapkota

ABSTRACT:

The dataset contains isotopic carbon, nitrogen, %C and %N in plants in GIRF bioretention. Plants in bioretention systems were harvested in May 2015 and analyzed by Oct 2015. % C and % N were analyzed in root and shoot samples. Upland contains native Utah’s vegetation, and wetland systems have wetland vegetation dominant in wetland systems. To determine C and N in plant biomass, each plant was divided into roots and shoots and dried in an oven to the constant mass at 40oC for 48 hours. CN samples were run on Thermo-Electron Delta IRMS configured through Thermo/Finnigan CONFLO III. d15N & d13C was analyzed using a Carlo Erba NC2100 elemental analyzer. Wetland 7 and Upland 8 does not have root data as the plants in these bioretention units were not harvested.

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TN & TP in influent and effluent from bioretention systems at GIRF
Created: Aug. 6, 2016, 12:52 a.m.
Authors: Pratibha Sapkota

ABSTRACT:

This dataset contains Total Nitrogen and Total Phosphorous in influent and effluent water samples from GIRF bioretention. Synthetic storms were run in each bioretention (Houdeshel et al.,2013) which represents storms in Salt Lake City. When synthetic storms were run in bioretention every month, water effluent from the bioretention passed through tipping buckets and autosamplers. Composite water samples from autosampler were collected using 10mL vials, and water samples were analyzed in the laboratory for TP, and TN using Astoria Pacific Autoanalyzer. “in” in dataset represents synthetic storm coming from synthetic storm tank to bioretention and “out” represents effluent coming out of each bioretention cell.

Details on GIRF bioretention and schematic is attached.

Houdeshel, C. Dasch, Christine A. Pomeroy, and Kevin R. Hultine. 2012. “Bioretention Design for Xeric Climates Based on Ecological Principles 1.” JAWRA Journal of the American Water Resources Association 48(6)

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Amenity Index
Created: Aug. 6, 2016, 4:22 p.m.
Authors: Matthew Wheelwright

ABSTRACT:

This dataset contains an amenity index for all Utah Census Places. Using Census data and other available datasets, an index for 'amenityness' was created. Following Ganning and Flint's previous research note, the index is calculated using physical amenities as well as socio-economic indicators (See: Ganning, Joanna Paulson, and Courtney G. Flint. “Constructing a Community-Level Amenity Index.” Society & Natural Resources 23, no. 12 (November 2, 2010): 1253–58. doi:10.1080/08941920903030132).

This index adds context to any study where an understanding of local, natural amenities is valued. It contains the following physical amenity variables: 1. Open Land 2. Open Water 3. Kapos Classification 4. Number of Recreation sites

It also includes key indicators which come from Census Data. 1. Employment Diversity 2. Median Household Income 3. Seasonal Housing 4. Population Growth 5. In-migration from out of state 6. In-migration from out of county 7. College education 8. New Housing Built 9. Housing Valued over $175,000 10. Median Rent 11. Median Housing Value 12. Employment in arts, entertainment, recreation, accommodation, and food services.

For more information on the calculations and variables, please read Ganning & Flint's research note and the ReadMe file linked to this dataset or the data dictionary within the excel spreadsheet as Tab 2.

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ABSTRACT:

In collaboration with the Salt Lake City Parks and Public Lands Department, researchers at Utah State University created a tablet-based survey instrument to gather feedback from community members about a proposed green infrastructure project in the Glendale neighborhood at the "Three Creeks Confluence". The Confluence is where three urban creeks, Red Butte, Emigration, and Parleys, empty in to the Jordan River in pipes underground of the city. In addition to information about that specific project, this survey also gathered some broader community opinions regarding local parks along the Jordan River corridor. The survey was designed specifically for residents in the neighborhood surrounding the Jordan River and was implemented using iPads and a public-intercept convenience sampling methodology in publicly accessible spaces and public events including local parks, shopping areas, libraries, and community festivals. The Survey results are accessible for visualization at http://data.iutahepscor.org/surveys/survey/3Creeks.

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Stream biofilm 13C-hemicellulose DNA stable isotope probing experiment
Created: Aug. 6, 2016, 4:43 p.m.
Authors: Elizabeth Ogata · Sandra Udy · Michelle Baker · Zachary Aanderud

ABSTRACT:

This resource contains the results of a 13C-hemicellulose DNA stable isotope probing (DNA-SIP) experiment that tested how nutrients and light exposure influence hemicellulose decomposition and hemicellulose-degrading bacterial populations. We conducted our experiment with stream biofilms grown on nutrient diffusing substrates (NDS) in the Middle Provo River (Utah), at a site below Jordanelle Reservoir (June 1, 2016 - June 20, 2016). To construct the nutrient diffusing substrates, we filled 1-oz plastic cups with unamended agar and then capped the agar with a fritted glass disc, which served as a platform for biofilm colonization. To assess potential nutrient limitation of the stream biofilms grown for our hemicellulose DNA-SIP experiment, we also deployed NDS containing agar amended with either no nutrients (control), nitrogen (N; 0.5 M NH4-N), phosphorus (P; 0.5 M PO4-P), or N and P (N+P) and measured biomass (chlorophyll a, ash-free dry mass) and calculated Autotrophic Index values. The CSV file “hemicellulose DNA-SIP nutrient limitation” contains summary statistics (mean, standard deviation, count) of chlorophyll, ash-free dry mass, and Autotrophic Index values on each nutrient treatment. The Word document “hemicellulose DNA-SIP analytical methods” describes the analytical methods used to measure chlorophyll and ash-free dry mass. To characterize conditions at the site, we collected water column samples for total and dissolved nutrient analyses and calculated degree days from time series water temperature data collected as part of the NSF-funded iUTAH project (Award number 1208732). The CSV file “hemicellulose DNA-SIP site characteristics” reports degree days and water column concentrations of total nitrogen (TN), total phosphorus (TP), ammonium (NH4-N), nitrate (NO3-N + NO2-N), and soluble reactive phosphorus (SRP-P) (nutrient concentrations are mean of 3 replicates). The Word document “hemicellulose DNA-SIP analytical methods” describes the analytical methods used to measure nutrient concentrations.

Biofilms grown on unamended NDS were used to perform the hemicellulose DNA-SIP experiment. Biofilm-colonized discs were placed in clear glass jars containing filter-sterilized river water amended with 13C-hemicellulose (approximately 540 µmol C L-1). We tested eight combinations of nutrient (control, N, P, N+P) and light exposure (light, dark) treatments. Nutrient treatments were applied by adding N (2.5 mg NH4-N L-1) and/or P (0.36 mg PO4-P L-1) to the appropriate jars. To apply the light exposure treatments, we wrapped dark treatment jars in aluminum foil and left the light treatment jars unwrapped. We incubated jars for 10 days on a shaker table (50 rpm) in a growth chamber held at a temperature of 12°C set to a 15-hour photoperiod, which was illuminated using cool white fluorescent bulbs (4200 K color temperature, Sylvania Supersaver, Osram Sylvania Products Inc.). The average photosynthetically active radiation, measured with a LI-COR LI-190 quantum sensor, was 27.3 µE m-2 sec-1. We collected biofilms and water samples from each treatment on day 0 and day 10. Biofilms were frozen for DNA-SIP analyses. Water samples were collected for dissolved organic carbon (DOC) concentration and dissolved organic matter (DOM) fluorescence characterization analyses. We used DOC and DOM data to calculate Fluorescence Index (FI), Freshness Index (BIX), Humification Index (HIX) and specific ultraviolet absorbance (SUVA254; calculated by dividing the absorbance at 254 nm by the DOC concentration). The CSV file “hemicellulose DNA-SIP DOC and DOM” contains summary statistics of DOC and DOM data in each hemicellulose incubation treatment. The Word document “hemicellulose DNA-SIP analytical methods” describes the analytical methods used to measure DOC and DOM.

DNA-SIP analyses were conducted by first extracting genomic DNA from each biofilm-colonized disc. We next separated the DNA in each sample by density using ultracentrifugation (58,000 rpm, 20°C, at least 72 hours). We collected 28 density fractions from the resulting gradient with a fraction recovery system and pooled the low density fractions containing unlabeled DNA and high density fractions containing 13C labeled DNA in each sample. We then composited the low and high density fractions from all samples within each hemicellulose incubation treatment. We performed target metagenomics of the 16S rRNA gene. The Word document “hemicellulose DNA-SIP analytical methods” describes the DNA-SIP community composition analysis methods. The CSV file “hemicellulose DNA-SIP shared OTU” lists the number of sequences for each OTU in the low and high density fractions of each hemicellulose incubation treatment. The CSV file “hemicellulose DNA-SIP taxonomy” contains OTU classification information.

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GIRF Mineralization data
Created: Aug. 6, 2016, 4:54 p.m.
Authors: Pratibha Sapkota

ABSTRACT:

The data shows Net Nitrogen Mineralization occurring in GIRF bioretention from August 2013 to October 30, 2014. Net nitrogen mineralization is calculated as the difference in inorganic N content (NO3-N, NO2-N, NH4-N) between incubated (soil samples inside PVC pipes) soil samples and non-incubated soil samples every two weeks. Hach kits (TNT 835 Low Range (accurate between 0.23-13.5 mg/L), TNT 839 Low Range (accurate between 0.015-0.6 mg/L), and TNT 830 Ultra Low Range (accurate between 0.015-2 mg/L)) were used for measuring inorganic content in the soil. TN was measured using HachTM persulfate digestion method 10208 (accurate between 1 mg/l-16 mg/l) every two weeks. Then, N concentration in all samples was quantified using a Hach 6500 spectrometer (HachTM Company, Loveland, CO).

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site near the Provo River at Woodland Basic Aquatic (PR_WD_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network climate site near Red Butte Creek at 1300 East Aquatic (RB_1300E_A). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for the site and the variable and method of each column.

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Dust chemistry and mineralogy
Created: Sept. 9, 2016, 1:59 a.m.
Authors: Greg Carling · Dylan Dastrup

ABSTRACT:

This dataset contains chemistry and mineralogy data for dust samples collected across northern Utah and Great Basin National Park (Nevada) as part of Dylan Dastrup's thesis project.

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Rating Curve Analysis Template - Jupyter Notebook
Created: Sept. 14, 2016, 5:07 p.m.
Authors: Chris Cox

ABSTRACT:

A template Jupyter Python (3) Notebook for analyzing discharge rating curve data. Data is imported from an excel file and analyzed following Herschy 2009. After an initial analysis, a least squares regression, is performed on the input data. Eventually it would be nice to implement a weighted regression based on uncertainties.

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Discharge Rating Curve at Blacksmith Fork above confluence with Logan River (LR_BSF_BA)
Created: Oct. 20, 2016, 8:13 p.m.
Authors: iUTAH Cyberinfrasructure Team

ABSTRACT:

This dataset contains a stage-discharge relationship developed for the iUTAH GAMUT Network aquatic site at Blacksmith Fork above confluence with Logan River (LR_BSF_BA). Discharge measurements were collected by a SonTek FlowTracker. Measured stage and discharge and the curve are contained in the Rating Curve file. Information on the site conditions and any issues with discharge measurements are documented in the README file. Files associated with each measurement (e.g., output by the FlowTracker instrument) are contained in the .zip directory. This rating curve was used to generate discharge data through 6/30/2018. New versions of these files may be loaded when new flow measurements are taken. Resulting discharge data is published in the iUTAH GAMUT operational databases and may be accessed via http://data.iutahepscor.org/tsa.

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iUTAH GAMUT Water Quality Grab Sampling Results
Created: Nov. 3, 2016, 5:54 p.m.
Authors: iUTAH GAMUT Working Group

ABSTRACT:

This dataset contains the results of water quality sampling efforts in the iUTAH GAMUT watersheds (Logan River, Red Butte Creek, and Provo River). There were two separate sampling and analysis efforts:
1. A "synoptic" effort that involved sample collection every month at a number of sites in 2013-2014. For this effort, samples were analyzed for total phosphorus and total nitrogen, total coliform, E.coli, and water isotopes.
2. A "biweekly" effort that involved sample collection every two weeks and a smaller number of sites (mostly at GAMUT aquatic stations) in 2014-2016. For this effort, samples were analyzed for species of nitrogen and phosphorus, dissolved organic carbon, suspended and volatile solids, total coliform and E.coli, chlorophyll-a, and fluorescence indices.

In all cases, grab samples were collected from the thalweg of the channel. For the biweekly effort, samples were filtered for analyses of dissolved species, and filters were retained for TSS and VSS analysis. Nutrient, organic matter, and chlorophyll-a analyses were performed at the Aquatic Biogeochemistry Laboratory at Utah State University. Isotope analyses were performed at the Stable Isotope Ratio Facility for Environmental Research at the University of Utah. Bacterial analyses were performed either at the Aanderud Laboratory at Brigham Young University or by technicians in the field. Detailed collection and analyses methods are described in the files.

The current Excel files are organized with worksheets corresponding to People and Organizations, Dataset Citation, Methods, Variables, Sites, Specimens, Processing Levels, Units, and Analysis_Results. The Specimens sheet includes detailed metadata on the collection of the specimens, including the date and time. The Analysis_Results tab includes detailed metadata on the analyses of the specimens and the numeric results. These two are linked via the Sampling Feature Code.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Climate Station at Franklin Basin (LR_FB_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Logan River at Mendon Road (600 South) (LR_Mendon_AA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Soapstone Climate (PR_ST_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Provo River at Charleston Advanced Aquatic (PR_CH_AA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Red Butte Gate Basic Aquatic (RB_RBG_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Knowlton Fork Climate (RB_KF_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Logan River at the Utah Water Research Laboratory west bridge (LR_WaterLab_AA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Climate Station at Logan River Golf Course (LR_GC_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Lower Knowlton Fork Aquatic (RB_LKF_A). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Climate Station at TW Daniels Experimental Forest (LR_TWDEF_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network 1300 East Aquatic (RB_1300E_A). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Knowlton Fork Basic Aquatic (RB_KF_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Todds Meadow Climate (RB_TM_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Trial Lake Climate (PR_TL_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Provo River Below Jordanelle Reservoir Advanced Aquatic (PR_BJ_AA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Charleston Climate (PR_CH_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Blacksmith Fork above confluence with Logan River (BSF_CONF_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Climate Station at Tony Grove (LR_TG_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Logan River near Tony Grove (LR_TG_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Provo River near Soapstone Basic Aquatic (PR_ST_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Foothill Drive Advanced Aquatic (RB_FD_AA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Green Infrastructure Climate (RB_GIRF_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network 900 W (1300 South) Basic Aquatic (RB_900W_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Above Red Butte Reservoir Advanced Aquatic (RB_ARBR_AA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Logan River at Main Street (Highway 89/91) Bridge (LR_MainStreet_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Logan River near Franklin Basin (LR_FB_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Cottams Grove Basic Aquatic (RB_CG_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Provo River at Lower Midway (PR_LM_BA). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Above Red Butte Reservoir Climate (RB_ARBR_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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ABSTRACT:

This dataset contains quality control level 1 (QC1) data for all of the variables measured for the iUTAH GAMUT Network Beaver Divide Climate (PR_BD_C). Each file contains all available QC1 data for a specific variable. Files will be updated as new data become available, but no more than once daily. These data have passed QA/QC procedures such as sensor calibration and visual inspection and removal of obvious errors. These data are approved by Technicians as the best available version of the data. See published script for correction steps specific to this data series. Each file header contains detailed metadata for site information, variable and method information, source information, and qualifiers referenced in the data.

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Test Resource
Created: Jan. 19, 2017, 1:28 p.m.
Authors: Amber Jones · Jeffery S. Horsburgh · Aanderud, Zach ·

ABSTRACT:

This is a test resource created to demonstrate HydroShare functionality.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network USGS Gage 10172200 above Red Butte Reservoir (RB_ARBR_USGS). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Kamas Base Station (PR_KM_B)
Created: Jan. 20, 2017, 9:37 p.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Kamas Base Station (PR_KM_B). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Provo River at Charleston Central Utah Water Conservancy District Gage (PR_CH_CUWCD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Yellow Lake Repeater (PR_YL_R)
Created: Jan. 20, 2017, 9:37 p.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Yellow Lake Repeater (PR_YL_R). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Provo River Below Jordanelle Reservoir Central Utah Water Conservancy District Reservoir Release (PR_BJ_CUWCD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Timpanogos Canal below Jordanelle Reservoir (PR_TC_CUWCD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Red Butte Reservoir (RB_RBR_CUWCD)
Created: Jan. 23, 2017, 9:29 p.m.
Authors:

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Red Butte Reservoir (RB_RBR_CUWCD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Harbor Drive Advanced Aquatic (PR_HD_AA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network USGS Gage 10163000 Provo River at Provo, UT (PR_HD_USGS). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH Research Data Policy
Created: Jan. 26, 2017, midnight
Authors: Jeffery S. Horsburgh · Amber Jones

ABSTRACT:

iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) is a collaborative research and training program in Utah. As part of project requirements, iUTAH developed a data policy that seeks to maximize the impact and broad use of datasets collected within iUTAH facilities and by iUTAH research teams. This policy document focuses on assisting iUTAH investigators in creating and sharing high-quality data. The policy defines the data types generated as part of iUTAH and clarifies timelines for associated data publication. It specifies the requirements for submittal of a data collection plan, the creation of metadata, and the publication of datasets. It clarifies requirements for cases involving human subjects as well as raw data and analytical products. The Policy includes guidelines for data and metadata standards, storage and archival, curation, and data use and citation. Agreements for data publishers and data use are also included as appendices.

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iUTAH GAMUT Network Raw Data at Soapstone Climate (PR_ST_C)
Created: May 15, 2017, 10:34 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Soapstone Climate (PR_ST_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Provo River at Charleston Advanced Aquatic (PR_CH_AA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Knowlton Fork Climate (RB_KF_C)
Created: May 15, 2017, 10:34 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Knowlton Fork Climate (RB_KF_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Wilkins Repeater (LR_Wilkins_R)
Created: May 15, 2017, 10:34 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Wilkins Repeater (LR_Wilkins_R). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Dentistry Building Storm Drain (RB_Dent_SD)
Created: May 15, 2017, 10:34 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Dentistry Building Storm Drain (RB_Dent_SD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Blacksmith Fork above confluence with Logan River (BSF_CONF_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Fort Douglas Storm Drain (RB_FortD_SD)
Created: May 15, 2017, 10:34 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Fort Douglas Storm Drain (RB_FortD_SD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Provo River at Upper Midway Central Utah Water Conservancy District Gage (PR_UM_CUWCD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Lower Knowlton Fork Aquatic (RB_LKF_A)
Created: May 16, 2017, 2:44 a.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Lower Knowlton Fork Aquatic (RB_LKF_A). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network River Heights Bridge Storm Drain (LR_RH_SD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Beaver Divide Climate (PR_BD_C)
Created: May 16, 2017, 2:44 a.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Beaver Divide Climate (PR_BD_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Cottams Grove Basic Aquatic (RB_CG_BA)
Created: May 16, 2017, 2:44 a.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Cottams Grove Basic Aquatic (RB_CG_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Connor Road Storm Drain (RB_CR_SD)
Created: May 17, 2017, 12:48 a.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Connor Road Storm Drain (RB_CR_SD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Logan River at the Utah Water Research Laboratory west bridge (LR_WaterLab_AA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Climate Station at TW Daniels Experimental Forest (LR_TWDEF_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Provo River near Soapstone Basic Aquatic (PR_ST_BA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at GIRF Storm Drain (RB_GIRF_SD)
Created: May 17, 2017, 7:46 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network GIRF Storm Drain (RB_GIRF_SD). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network USGS Gage 10154200 Provo River near Woodland, UT (PR_WD_USGS). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Climate Station at Tony Grove (LR_TG_C)
Created: May 17, 2017, 7:46 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Climate Station at Tony Grove (LR_TG_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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iUTAH GAMUT Network Raw Data at Green Infrastructure Climate (RB_GIRF_C)
Created: May 22, 2017, 8:22 p.m.
Authors: None

ABSTRACT:

This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Green Infrastructure Climate (RB_GIRF_C). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Provo River at Riverwoods Aquatic (PR_RW_A). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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Assessment of ecosystem ‘health’ traditionally uses structural indicators (e.g., biotic community composition) but often neglects indicators of ecosystem processes (e.g., decomposition rates), providing an incomplete picture of overall ecosystem condition. Efforts to establish a framework identifying thresholds of organic matter decomposition expected in relatively intact, moderately degraded, and severely degraded ecosystems have been stymied by limited geographic scope and variation in organic matter composition that preclude general use of the framework. The goal of the CELLulose Decomposition ExXperiment (CELLDEX) project is to compare riparian and in-stream organic matter decomposition rates (i.e., loss of tensile strength per unit time) across all of the Earth's major biomes using a standardized cotton strip assay. Using a ‘crowdsourcing’ approach with researchers from over 40 countries, CELLDEX involves the deployment of a standardized substrate assay in approximately 400 streams and their riparian zones, representing each of Earth’s major biomes, and spanning 140 degrees of latitude. Each partner is responsible for incubating standardized cotton strips in four reference streams for ~ 30 days near their home institutions and provide ancillary data on water temperature and chemistry. This simple, inexpensive assay omits intrinsic differences in organic matter (i.e., variation in chemical composition and physical structure), thus allowing the influence of extrinsic environmental factors (e.g., temperature, water chemistry, flow or precipitation regimes) to be better assessed. This assay also is sensitive to differences in environmental conditions at regional and watershed scales, including those associated with environmental degradation. Cellulose strips were deployed for approximately 30 days from mid-October to mid-November in four streams and adjacent riparian zones in central Utah, USA to measure rates of decomposition. Data in this resources reflect only data from the state of Utah, USA.

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This dataset contains raw data for all of the variables measured for the iUTAH GAMUT Network Provo River Below Jordanelle Reservoir Advanced Aquatic (PR_BJ_AA). Each file contains a calendar year of data. The file for the current year is updated on a daily basis. The data values were collected by a variety of sensors at 15 minute intervals. The file header contains detailed metadata for site and the variable and method of each column.

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This data set contains measurements for discharge in cfs and cms, stream temperature in °C , dissolved oxygen (DO) in mg/L and %/L, total dissolved solids (TDS) in µs/cm, pebble count, and geomorphic condition, at sites in the Weber River Basin and Bear River Basin. Discharge was measured using a Marsh McBurney hand-held flowmeter. DO, TDS, and stream temperature were measured using a YSI Pro 2030 water quality probe. Pebble count was conducted using a modified Wolman procedure where a random pebble is picked up every step diagonally across a stream in a zig-zag pattern until at least 100 pebbles are measured. The pebble is then measured to obtain size and recorded. Geomorphic condition was assessed visually by taking note of conditions such as stream complexity (presence or lack of pools, riffles, meandering thalweg etc.), percent shade on stream, flow and depth variability, bank stability, access to floodplain, wood recruitment, unnatural barriers and condition and quantity of riparian vegetation. Based on the these conditions, a classification of excellent, good, moderate, or poor was assigned. Atmospheric pressure, wind speed and air temperature were measured with a Kestrel handheld weather meter, cloud cover was assessed visually. A site key in addition to the date, time and location (latitude/longitude and UTM) is included. Not all sites have values for discharge and pebble count due to hazardous conditions.

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Logan GAMUT field operations database
Created: July 20, 2017, 6:50 p.m.
Authors: Chris Cox

ABSTRACT:

A SQLite database containing all field notes generated during the operation and management of the Logan GAMUT monitoring network, a component of the iUTAH project.
The database can be used as a reference when assessing GAMUT data. Alternatively, the database can be used as a template for other monitoring projects needing to create a system for managing field notes and tracking equipment location and maintenance.

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Concentrations of bacteria in storm water runoff
Created: July 24, 2017, 4:56 a.m.
Authors: Chase Beyer · R Ryan Dupont

ABSTRACT:

The introduction of pollutants into storm water runoff can be concerning since it can act as a vector for environmental pollution or even household contamination. This study will assess the microbial contamination of storm water runoff from various sources including a metal roof, a photocell, and dry wells collecting roof and parking lot runoff on the USU campus. The microbes being tested for are total coliforms, E. coli, and enterococcus. ISCO auto samplers and grab samples were used to gather storm water samples. Simulations were ran using off-gassed tap water on the metal roof a photovoltaic cell. The concentrations of the three microbes in the samples were determined using the IDEXX Quanti-tray 2000 system. It was found that samples taken from the dry wells had greater concentrations of total coliform and E. coli than surface samples. It was also found that the metal roof on the pump house had greater concentrations of all three indicator bacteria than the photovoltaic cell atop the roof.

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Soil Description for GAMUT Weather Stations
Created: July 26, 2017, 6:44 p.m.
Authors: Kshitij Parajuli · Scott B. Jones · John Lawley

ABSTRACT:

Soil properties are important for understanding soil and modeling process taking place throughout the soil profile. This dataset provides a detailed description of the soil profile including the soil texture, color, structure and root density within the soil pit excavated at each GAMUT weather station within the iUTAH network. In addition to soil information, the slope, aspect, vegetation, surface stone and rock content etc. for each station is also presented.​

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Salt Lake Valley tap water isotope ratio dataset
Created: July 27, 2017, 5:36 p.m.
Authors: Yusuf Jameel

ABSTRACT:

This data set contains stable isotope values of tap water collected in the Salt Lake Valley (SLV) from 2013 to 2016.

The proposed goals for the project was to:
1. Characterize tap water isoscapes across SLV to develop isotope budgets for tap water systems.
2. Use the budgets and infrastructure data to infer the most important contributing regions to different municipal systems and evaporative water loss from these systems.
3. Combine management data, isotope characterization of environmental waters, and tap water isotope data to develop isotopic fingerprints for contrasting water management practice

Data Collection Methods: Collected tap water from different municipal districts across the SLV in a series of bi-annual hydrological surveys. The samples are collected from local businesses, homes and offices in April and September/October every year since 2013.The survey was designed in hydrologically contrasting seasons to capture potential seasonal differences in the tap water isotopes.

Location of Data Collection: We have collected data from approximately 140 sites every survey so far. The sites are located within the Salt Lake county, Utah. So far we have collected more than 800 samples. Each site is assigned a unique site ID (for example: SLV-WS-049 which stands for Salt lake valley water site number 049). The metadata includes the complete address and geographic location of the sites.

Timing of Data Collection:
April (04/25/2013) and October 2013 (10/02/2013)
April (04/29/2014) and September 2014 (09/25/2014)
April (04/28/2015) and September 2015 (09/28/2015)
April (04/27/2016) and October 2016 (10/01/2016)

Data Analysis: For each site, samples were obtained by running the tap water for ~15 seconds before filling, capping and sealing (with parafilm) a clean 4 ml glass vial. Samples were analyzed for their isotopic composition within a few weeks of their collection at the Stable Isotope Ratios for Environmental Research (SIRFER), University of Utah, on Picarro L2130-i Cavity Ring Down Spectroscopy (CRDS) analyzer. All the sample values are reported using the δ notation, where δ=Rsample/Rstandard -1, R= 2H/1H and 18O/16O. Four injections of each sample were measured and corrected for memory effects, through-run drift, and calibrated to the VSMOW-VSLAP scale, using a suite of three laboratory reference waters (PZ: 16.9‰, 1.65‰; PT: -45.6‰, -7.23‰; UT: -123.1‰, -16.52‰; for δ2H and δ18O, respectively).

We published the results in Water resources research ( DOI: 10.1002/2016WR019104)

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Logan GAMUT Nitrate Bias Correction
Created: July 27, 2017, 8:47 p.m.
Authors: Chris Cox

ABSTRACT:

Jupyter notebooks detailing methods used to determine bias correction for Nitrate data at Waterlab and Mendon Road monitoring sites. The correction was utilized as part of data quality control and is included in quality control level 1 datasets.

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ABSTRACT:

Wastewater treatment plants significantly reduce the microbe levels in water. However, the remaining microbes may regrow in the nutrient-rich wastewater effluent.
Therefore, using this reclaimed effluent as a secondary water source can potentially contaminate crops. For this study, an agricultural field was irrigated using reclaimed wastewater from the Hyrum Wastewater Treatment Plant. The water was tested before and after irrigation to determine the microbial load applied to the crops. Then, daily plant samples were collected to determine both the initial microbial contamination level and the die-off after the irrigation event. All samples were tested on IDEXX’s Colilert and Enterolert trays. These trays contain large and small wells that each give positive/negative results. The different sized wells act like different dilutions to help quantify bacteria concentrations. Positive wells are counted and an IDEXX table used to convert the well counts into MPN counts for coliforms, E. coli, and Enterococcus, all found in high levels in wastewater influent. Test results demonstrated microbial regrowth in the reclaimed wastewater system. Additionally, the reclaimed water contaminated the irrigated plants and the contamination level was reduced significantly in the first 48 hours after wastewater application.

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Aquatic GAMUT Eukaryote Metagenomics
Created: July 31, 2017, 6:10 p.m.
Authors: Erin Jones · Zach Aanderud

ABSTRACT:

This dataset contains a .biom file of OTU (operational taxonomic units) classifications for eukaryotes at iUTAH GAMUT sites in three watersheds in May of 2015. Briefly, water column samples were filtered on 0.2 um membrane filters, which were dissolved and processed with MOBIO Power Soil DNA extraction kits. We sequenced 18S region amplicons using Illumina Hi-Seq and then a modified MOTHUR protocol (Silva v. 132 reference file, command codes in mothureukaryotes.txt) to generate OTU classifications. Sample metadata (including site information and sample chemistry from grab samples or sensor data) is in design.csv.

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Aquatic GAMUT Bacterial Community Target Metagenomics-HiSeq
Created: July 31, 2017, 6:30 p.m.
Authors: Erin Jones · Zach Aanderud

ABSTRACT:

This data was collected as part of a study to understand the connectivity and diversity of stream bacteria communities in streams flowing from high to low elevation through different types of urbanization and in different seasons. The dataset contains OTU (operational taxonomic units, the bacterial surrogate for species) abundance for bacteria at iUTAH aquatic GAMUT sites (http://data.iutahepscor.org/mdf/Data/Gamut_Network/) in three watersheds at 3 time points (November 2014, February 2015, and May 2015). Briefly, we filtered water column samples onto 0.2 um membrane filters, which were dissolved and processed with MOBIO Power Soil DNA extraction kits (alternate low protocol yield using phenol chloroform). We sequenced bacterial DNA (PCR-amplified using V4 region specific primers) using Illumina Hi-Seq. We cleaned, clustered (using 97% OTU similarity cut-off) and aligned sequences using the Kozich et al. 2013 protocol, and classified OTUs to taxonomy based on the SILVA bacteria database. Code used for processing is available at https://github.com/erinfjones/mothurcode.

There are three files; site and sample metadata (e.g. date sampled) is included in the file stream_design.txt, observed OTU counts by sample are in the .shared file, and the taxonomic classification of OTUs is in the .taxonomy file.

Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. (2013): Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Applied and Environmental Microbiology. 79(17):5112-20.

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JVWCD service area tap water isotope ratio
Created: Aug. 11, 2017, 11:10 p.m.
Authors: Yusuf Jameel

ABSTRACT:

Introduction: Stable isotopes of water have extensively been used to understand hydrological cycle in natural environment, however their application in highly managed urban water systems have been limited. Recent research have shown that water isotopes reflect urban water management practices and have potential application in understanding urban water supply network dynamics, evaluating effect of climate variability on water resources, geolocation and water monitoring and regulation.

Jameel and colleagues ( WRR, 2016) attributed the strong and structured spatiotemporal variation in tap water isotope ratios of Salt Lake Valley (SLV) to complex distribution systems, varying water management practices and multiple sources used across the valley. Building on their result, we collaborated with the largest water supply company in SLV, Jordan Valley Water Conservancy District (JVWCD) and expanded our project which now includes predicting the source (or sources) contributing to a given supply area. The different sources supplying JVWCD (such as Provo River system, Wasatch Creeks and groundwater wells) have similar yet distinct isotope ratios, providing an excellent opportunity to test the robustness of water isotopes in monitoring distribution pattern of the sources in the supply system. For this project, we collected more than 100 samples/month (between April 2015-May 2016), from different water sources (creeks, streams and groundwater wells), water treatment plants (WTP), storage reservoirs and delivery locations along the supply lines across the water distribution area , measured their isotopic ratio and developed isotopic mixing models using Hierarchical Bayesian (HB) framework to understand the flow of water in an urban supply system and connect tap water at a specific location to its respective sources.

Data Collection Methods: Water samples collected from source, reservoirs, and different locations within the JVWCD service area.

Location of Data Collection: we collect approximately 100 samples per month. From May 2015 to April 2016, for each month, we sampled different sources supplying water to the JVWCD service area and at numerous locations on the JVWCD distribution line (subsequently referred to as supply sites). Source water samples were collected as effluent from the WTPs and from groundwater wells and supply sites samples were collected from monitoring taps positioned on the distribution line. Source and supply sites were sampled 1-3 times per month.

Data Analysis: For each site, samples were obtained by running the tap water for ~15 seconds before filling, capping and sealing (with parafilm) a clean 4 ml glass vial. Samples were analyzed for their isotopic composition within a few weeks of their collection at the Stable Isotope Ratios for Environmental Research (SIRFER), University of Utah, on Picarro L2130-i Cavity Ring Down Spectroscopy (CRDS) analyzer. All the sample values are reported using the δ notation, where δ=Rsample/Rstandard -1, R= 2H/1H and 18O/16O. Four injections of each sample were measured and corrected for memory effects, through-run drift, and calibrated to the VSMOW-VSLAP scale, using a suite of three laboratory reference waters (PZ: 16.9‰, 1.65‰; PT: -45.6‰, -7.23‰; UT: -123.1‰, -16.52‰; for δ2H and δ18O, respectively).

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This data is a collection of soil gas, soil chemistry, and soil microbiology data starting in December 2016 and goes through December 2017. We are measuring soil CO2 concentration, oxygen, moisture, and temperature. Vaisala CO2 GMP220-series probes are placed at two depths (5 and 20 cm) to measure CO2 concentration and Acclima SDI-12 Interface sensors to measure soil moisture and temperature, as well as Apogee SO-110 soil oxygen sensors. Besides evaluating soil respiration sensitivity (i.e., CO2 evolved per unit change in moisture or temperature), we are evaluating the legacy effects of natural rainfall and snowfall on the structure of soil microbial communities using target metagenomics of 16s rDNA. Quality control was done on all data before analysis. Power at the sites can go out temporarily, creating gaps in sensor readings. Blank cells in the data represent times when the power to the site went out, or when a sensor died and had to be replaced. Logan River data begins in January 2017, rather than December 2016. All samples were stored in Whirl Pac soil sample bags and kept on ice while in the field and stored at 4C in the lab until analysis. A subset of each sample was taken in the field and kept in liquid nitrogen until they were stored in the lab at -80C, these were used for metagenomic analysis.

This dataset includes a year of sensor data and monthly soil analysis data and microbial analysis data.

Description of sensor data:
Column headers in the data refer to the site location and depth of the sensor. The first row indicates what watershed the sensor is located in, the second row indicates the site and sensor type and depth.
ST-Soapstone, CH-Charleston, KF-Knowlton Fork, GIRF- Green Infrastructure Research Facility, FB-Franklin Basin, GC-Golf Course. CO2 data is given in ppm and O2 data is %.

Description of soil chemistry data:
The soil chemistry data folder consists of a Soil chemistry_CN spreadsheet that included almost all chemical analysis performed on each sample. Each sample is listed, along with the watershed abbreviations as described above and site, depth, sample month, and sample day. Samples were collected between 7 am and 7 pm on day of sampling. Site "B" refers to the blank samples run with each set of samples. Non-purgeable organic carbon (NPOC) and Total Nitrogen (TN) were measured using a SHIMADZU TOC analyzer. Gravimetric water content was measured using the soil wet weight and dry weight after being dried for 48 hours at 105 C. %N and %C were measured on a LECO CN analyzer. Nitrate and Ammonium were determined using an OI Analytical Flow Solution IV analyzer. The uM results for Nitrate and Ammonium are included, as well as the modified results after accounting for soil moisture, they are given in mg N-Nitrate or N-Ammonium/kg dry soil.
Additionally, we used as Aqualog Benchtop Fluorometer to measure the Excitation-Emission Matrix for each sample. Data is still being processed and will be uploaded once the analysis is complete.

Description of microbial analysis data:
Samples were collected on a monthly basis at two depths (0-10, 15-25cm) from each sampling location. We sequenced the 16s v4 region for prokaryotes using both DNA and RNA and we sequenced the 18s v9 region for eukaryotes. We used a modified MOTHUR pipeline and a 97% OTU similarity cutoff. There are three files for each type of microbial data set; site and sample metadata (e.g. date sampled) is included in the file ***_design.csv, observed OTU counts by sample name are in the .shared file, and the taxonomic classification of OTUs is in the .taxonomy file. Sample names indicate the type of sample (R=RNA, D=DNA, EUD=eukaryote DNA), the sample number, initials, project name, watershed (P=Provo, R=Red Butte, L=Logan), the site (C=Charleston, S=Soaptstone, GIRF, K=Knowlton Fork, GC=Golf Course, F=Franklin Basin), A represents 0-10, and B represents 15-25, and the number represents the sample month. For example, R101KRSGPCA7 is from a sample that we extracted RNA, sample 101, Provo River, Charleston, 0-10cm and collected in July.
Eukaryote data is not available but will be uploaded once it has been processed.

Description of sampling locations:
Franklin Basin is located near the headwaters of the Logan River in Cache County, Utah. The elevation is 2109.52 m and at N 4156’59.334” W -11134’52.8666”.
Logan River Golf Course is located in a mixed urban and agriculture environment in Cache Valley at an elevation of 1364.89 m and N 41 42’20.3148” W -11151’15.3648”.
Knowlton Fork sits at an elevation of 2178.1008 m, N 40 48’ 36.4386” W -11146’1.0194”.
GIRF is the Green infrastructure climate station located on the University of Utah campus at N 4045’38.88” W -11149’49.7058”.
Soapstone Basin is the closest site to Trial Lake, the origin of the Provo River. The location is N 40° 34' 26.1408" W -111° 2' 36.5994".
Charleston location is at N 40° 29' 4.9812" W -111° 27' 45.1794".

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Sediment cores were collected (GPS coordinates taken) at three transects, one at the north end of Utah Lake and two within a kilometer of the Lake on the Jordan River. The cores were sub-sampled at 5 cm resolution for sediment grain size, C and N stable isotope and C/N ratio, and lead-210 analyses. All sampling was standardized. Sampling data is one time data (summer field collection). Carbon and nitrogen stable isotope compositions show a 4 per mil and a 2 per mil positive shift, respectively, as a depth of 55cm. C/N ratios show large variations (9-18) at depths shallower that 55cm, but are more stable (11-14) with greater depth. These results indicate a shift in organic matter sources to Utah Lake at a depth of 55cm, which likely represents the boundary between pre- and post-pioneer settlement in the valley around 1847. At depths greater than 55cm, the major contribution of soil organic matter was likely terrestrial C3 and autochthonous native C4 plants, whereas at depths shallower than 55cm terrestrial vegetation, manure/sewage-derived matter, and lake algae were the major lake organic matter sources. From this information, we approximate the post-settlement sedimentation rate in the lake to be 3.3mm/yr. Students and leads were responsible for data collection, data analysis, and data interpretation of the project.

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This study focused on the geomorphological, ecological, and sedimentological impacts of the Jordanelle Dam Provo River, Utah. This particular study site provides a unique opportunity because the Jordanelle dam was put in place in 1992 and a large scale restoration project was completed in 2008, allowing for high resolution imagery and observations prior to dam placement and restoration. To monitor these effects, we established cross section study sites along the Provo River, with 5 above the dam and 5 below the dam. At each cross section, we measured baseline channel morphology characteristics via surveying and sediment size distribution via sediment collection and lab grain size analysis processing. We also inventoried vegetation characteristics along the river to monitor differences upstream and downstream of the dam. This data, combined with analysis of historical imagery and current high resolution imagery, enables us to identify geomorphic changes over time and evaluate the impacts of those changes on the post-engineered river system as it applies to current and future watershed management. Post-impoundment, we find that channels downstream of the dam have become more stable, allowing for vegetation colonization, as exhibited in land cover changes from bare soil to grass. This results in greater species richness owing to colonization of a more stable riparian zone, ultimately changing habitat conditions. Grain size increases below the dam, which is a known dam impact. This data is particularly important as Utah faces climate change and population growth, both of which stress water availability, and has the potential to inform and improve watershed management practices to result in both a healthy fluvial system and a sustainable water resource.

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ABSTRACT:

We collected water samples from the Logan River, Red Butte Creek, and Provo River in Utah in June 2016 to assess the amount of human, ruminant, and dog fecal contamination in these watersheds. Samples were collected in sterile 1L bottles at sites where the iUTAH NSF EPSCoR program has installed aquatic sensor stations along a mountain-to-urban gradient in each watershed. After collection, we filtered samples through 0.2um PES filters, extracted the sample DNA using a MoBio PowerSoil DNA extraction kit, and analyzed the samples via qPCR.

By identifying the major sources of fecal pollution along urbanization gradients in Utah, we hope to inform efforts to manage fecal pollution in Utah's watersheds. In addition to creating generating raw qPCR values that show the relative contributions of each type (human, ruminant, and dog) to fecal pollution in the rivers sampled, we selected primer sets that we hope will be adopted as standard in future fecal pollution assessment efforts. We also created a standard operating procedure for the creation of qPCR standards, which will allow future researchers to determine total numbers of fecal indicator bacteria present in water samples.

Funded by the iUTAH NSF EPSCoR program (National Science Foundation, iUTAH-innovative Urban Transitions and Aridregion Hydro-sustainability, NSF Award Number 1208732) and conducted at Brigham Young University.

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Ferreira (2013) documented elevated concentrations of As and heavy metals in rivers that flow westward across the Wasatch Range and heavily-populated Utah Valley, Utah, to drain into Utah Lake, which is consistent with the history of unregulated mining in the watershed of Utah Lake. In Utah Valley it is not uncommon for urban residents to dig and maintain shallow (< 10 m) wells in their backyards, although the practice is illegal in Utah and unusual in urban areas outside of developing countries. Since the rivers in Utah Valley are losing streams, the question arose as to the levels of As and heavy metals in these shallow wells. The objectives of this study are to determine (1) the concentrations of contaminants in backyard wells (2) the pathways for shallow groundwater flow (3) why the urban residents of Utah Valley dig backyard wells. The objectives are being addressed by collecting water samples from backyard wells in Utah Valley and interviewing the owners of the backyard wells. Water temperature, pH, electrical conductivity, and dissolved oxygen are being measured on-site and water samples are being analyzed for nitrate, phosphate, sulfate, As, 11 heavy metals, and stable isotopes of hydrogen and oxygen. Chemical analysis of 107 backyard wells thus far has shown that EPA Drinking Water Standards are not met for Mn, As, Cd, Fe, Cu, Pb, and nitrate in 18.7%, 15.9%, 6.5%, 6.5%, 0.9%, 0.9%, and 0.9% of wells. Wells with elevated As and heavy metals tend to occur not near streams, but along the boundary between the groundwater recharge and discharge zones. According to a preliminary analysis of 80 interviews carried out with backyard well owners thus far, backyard wells are dug and maintained for emergency planning and for watering lawns and livestock, but not for gardens. Backyard well owners are conservative in terms of their social, political and religious attitudes, but are not survivalists or adherents to conspiracy theories. In fact, owners of backyard wells are no different than the mainstream of Utah culture, which suggests that backyard wells may be very common throughout the state. These findings raise the possibility that a state water policy that is backed by the public ought to include the promotion and legalization of safe water supply at the household level.

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ABSTRACT:

These data are from this publication: Oerter, E. J., Perelet, A., Pardyjak, E., & Bowen, G. (2017). Membrane inlet laser spectroscopy to measure H and O stable isotope compositions of soil and sediment pore water with high sample throughput. Rapid Communications in Mass Spectrometry, 31(1), 75-84.

Abstract:
RATIONALE: The fast and accurate measurement of H and O stable isotope compositions (δ2H and δ18O values) of soil and sediment pore water remains an impediment to scaling-up the application of these isotopes in soil and vadose hydrology. Here we describe a method and its calibration to measuring soil and sediment pore water δ2H and δ18O values using a water vapor-permeable probe coupled to an isotope ratio infrared spectroscopy analyzer.
METHODS: We compare the water vapor probe method with a vapor direct equilibration method, and vacuum extraction with liquid water analysis. At a series of four study sites in a managed desert agroecosystem in the eastern Great Basin of North America, we use the water vapor probe to measure soil depth profiles of δ2H and δ18O values.
RESULTS: We demonstrate the accuracy of the method to be equivalent to direct headspace equilibration and vacuum extraction techniques, with increased ease of use in its application, and with analysis throughput rates greater than 7 h1. The soil depth H and O stable isotope profiles show that soil properties such as contrasting soil texture and pedogenic soil horizons control the shape of the isotope profiles, which are reflective of local evaporation conditions within the soils.
CONCLUSIONS: We conclude that this water vapor probe method has potential to yield large numbers of H and O stable isotope analyses of soil and sediment waters within shorter timeframes and with increased ease than with currently existing methods.

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ABSTRACT:

These data are from the following publication:
Oerter, E. J., & Bowen, G. (2017). In situ monitoring of H and O stable isotopes in soil water reveals ecohydrologic dynamics in managed soil systems. Ecohydrology, 10(4).

Abstract:

The water cycle in urban and hydrologically-managed settings is subject to perturbations that are dynamic on small spatial and temporal scales, the effects of which may be especially profound in soils. We deploy a membrane inlet-based laser spectroscopy system in conjunction with soil moisture sensors to monitor soil water dynamics and H and O stable isotope ratios (δ H and δ18O values) in a seasonally irrigated urban landscaped garden soil over the course of 9 months between the cessation of irrigation in the autumn and the onset of irrigation through the summer. We find that soil water δ2H and δ18O values predominately reflect seasonal precipitation and irrigation inputs. A comparison of total soil water by cryogenic extraction and mobile soil water measured by in situ water vapor probes, reveals that initial infiltration events after long periods of soil drying (the autumn season in this case) emplace water into the soil matrix that is not easily replaced by, or mixed with, successive pulses of infiltrating soil water. Tree stem xylem water H and O stable isotope composition did not match that of available water sources. These findings suggest that partitioning of soil water into mobile and immobile “pools” and resulting ecohydrologic separation may occur in engineered and hydrologically-managed soils and not be limited to natural settings. The laser spectroscopy method detailed here has potential to yield insights in a variety of Critical Zone and vadose zone studies, potential that is heightened by the simplicity and portability of the system.

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SWMM Model for the Red Butte catchment
Created: Sept. 8, 2017, 3:23 p.m.
Authors: Hessam Tavakoldavani

ABSTRACT:

EPA Storm Water Modeling Management (SWMM) for a subcatchment in Salt Lake Valley, Red Butte Creek. It considers both the mountain and the urbanized areas.
This model still needs to be calibrated based on different intensities and periods of rainfall.
The SCS curve number, which is a simple and efficient method for determining the amount of runoff from a rainfall event in a particular area, was used for infiltration analyses.
the boundaries of subcatchment were derived based on a GIS-Hydrology work.
Also, soil information was obtained from National Resource Conservation Service (NRCS) for the area of study

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ABSTRACT:

Utah Lake, the largest freshwater lake in the United States west of the Mississippi River, has received
heavy loading of various contaminants, such as high concentrations of phosphorus (P) and nitrogen (N) wastes
from raw sewage, effluent from sewage treatment plants, runoff from surrounding agricultural and farming land,
and metals from mining and industrial activities since European settlement. However, the rate of loading of N, P,
and trace metals to Utah Lake varies both in space and time. Therefore, a good understanding of such spatial and
temporal variability is critical for developing integrated approaches to managing lake water quality. In this project,
we took water and floc layer sediment samples from the American Fork River, Provo River, Hobble Creek,
Spanish Fork River, Jordan River and Utah Lake to investigate the temporal and spatial variations in nutrient (P,
N) load and trace metal (mercury/methylmercury, arsenic, lead, cadmium, etc.) concentrations. In addition, water
samples were analyzed for H and O stable isotopes to establish a water budget for Utah Lake, and floc layer
sediment samples were analyzed for C and N stable isotopes to differentiate organic matter sources to Utah
Lake. Upon completion of this project, we were able to quantify spatial and temporal variations in nutrient and
metal loading to Utah Lake and to examine how this variability affected water quality. Furthermore, we were
able to trace the origins of organic matter sources to the lake and establish nutrient, metal, and water budget for
Utah Lake. The knowledge from this project can guide actions that are increasingly required to safeguard the
services provided by Utah Lake ecosystem in a future with increasing pressure on freshwater resources. The water,
nutrient, and trace metal budgets developed in this project provide important information for determining
which inflows are contributing the largest contaminant loads to Utah Lake. Consequently, the data derived from
this project can help state agencies to address significant questions in water quality, hydrologic, environmental,
and biogeochemical sciences and management related to human-environment interactions.

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ABSTRACT:

This resource contains the results of a nutrient uptake incubation experiment conducted at a mountain and urban site on the Logan River in northern Utah. The experiments were performed with biofilms grown for 14-15 days on nutrient diffusing substrates (NDS), 1-oz plastic cups filled with agar and capped with a fritted glass disc. We performed the nutrient uptake experiment by incubating biofilm-colonized discs in clear plastic jars filled with stream water spiked with nitrogen (N) and phosphorus (P) at a series of concentrations. The CSV file "nutrient uptake treatments" lists the treatments used in the nutrient uptake experiment at each site. Biofilms were incubated in situ for 2 hours at midday. Samples for dissolved nutrient analysis were collected from the nutrient treatment solutions used to fill the jars and from each jar at the end of the incubation. The dissolved oxygen concentration in each jar was measured at the start and end of the incubation. We calculated nutrient uptake rates as the rate of loss in water nutrients and net primary production as the change in dissolved oxygen concentration. We measured biofilm biomass as chlorophyll a. The CSV file “nutrient uptake results” contains summary statistics (mean, standard deviation, count) of nutrient uptake rates, net primary production rates, and chlorophyll a concentrations in nutrient uptake treatments at each site. The Word document “nutrient uptake analytical methods” contains the analytical methods used to measure nutrient concentrations.

We also examined biofilm nutrient limitation at each site using NDS. We constructed nutrient limitation NDS by filling 1-oz plastic cups with agar amended with either no nutrients (control), 0.5 M NH4-N (N), 0.5 M PO4-P (P), or 0.5 M NH4-N + 0.5 M PO4-P (N+P). NDS were then capped with a fritted glass disc and placed in the stream at each site during the same period that NDS for the nutrient uptake experiment were deployed. Biofilm biomass was measured as chlorophyll a and ash-free dry mass. The CSV file “nutrient limitation results” contains summary statistics of chlorophyll a concentration and ash-free dry mass in each nutrient treatment at each site. The Word document “nutrient uptake analytical methods” contains the analytical methods used to measure chlorophyll and ash-free dry mass.

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Device M1 Preliminary Testing
Created: Sept. 25, 2017, 2:16 p.m.
Authors: Chris Monson

ABSTRACT:

This data relates to an oxygen sensing microfluidic device, device M1. The data set includes calibration data, a calibration curve constructed from the calibration data, and a field test in the Farmington Bay of the Great Salt Lake. Further tests were planned, but this device was accidentally destroyed. New devices are being constructed and data for these devices will be posted when they are available.

Each text file represents one or two different oxygen concentrations that were measured either as part of the calibration curve (the files with dates) or in the field test (the files with lengths, which represent the water depth at which the measurement was made). The text files are generated by a potentiostat, and the headers of each text file merely give the information about the potentiostat settings. In the summary spreadsheet, the text files are summarized and the calibration curve is constructed and used to find the dissolved oxygen concentrations.

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Stream biofilm diphenhydramine dose-response experiment
Created: Oct. 1, 2017, 2:53 p.m.
Authors: Elizabeth Ogata · Donald Long · Michelle Baker · Zachary Aanderud · Emma Rosi

ABSTRACT:

This resource contains the results of a diphenhydramine dose-response experiment conducted on stream biofilms at a site on the Logan River in northern Utah. We grew stream biofilms on inorganic (fritted glass disc) and organic (cellulose sponge) substrates in the river for 20 days. The biofilm-colonized substrates were then placed as caps on contaminant exposure substrates (CES), 1-oz plastic cups filled with agar amended with diphenhydramine at a series of concentrations (control, 0.5 mM, 0.75 mM, 1.25m M, 2.5 mM, 15 mM). CES were then deployed in the river for 20 days.

At the end of the CES deployment, the biofilm-colonized substrates were used to perform a series of in-stream incubations. We measured respiration and productivity using a modified light-dark bottle incubation method and nitrogen fixation rates using an acetylene reduction assay. We measured biofilm biomass (chlorophyll a, ash-free dry mass) and calculated Autotrophic Index values (calculated as chlorophyll a concentration divided by ash-free dry mass). The CSV file “biomass_function_diphenhydramine” contains summary statistics (mean, standard deviation, count) of respiration rates, gross primary production rates, nitrogen fixation rates, chlorophyll a concentrations, ash-free dry mass, and Autotrophic Index values of biofilms on each diphenhydramine treatment and substrate type. The Word document “methods_diphenhydramine” describes the analytical methods used to measure chlorophyll and ash-free dry mass.

We characterized light availability and nutrient concentrations at the study site. The Word document “methods_diphenhydramine” describes the methods used to measure site characteristics and the analytical methods used to measure nutrient concentrations. The CSV file “site_characteristics_diphenhydramine” contains percent canopy openness, transmitted PAR, transmitted solar shortwave radiation, total nitrogen, total phosphorus, ammonium, nitrate, soluble reactive phosphorus, dissolved total iron, and dissolved ferrous iron concentrations.

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Risk Communication on Social Media to Spanish-Speaking Populations
Created: Oct. 11, 2017, 3:28 p.m.
Authors: Jared Stewart · Peter Howe · Yajie Li

ABSTRACT:

Heat is the leading cause of weather related fatalities in the United States. It is important that agencies and organizations understand heat and other extreme weather related risks, especially as climate change exacerbates the frequency and severity of extreme weather events. This research focused on communication strategies used by the National Weather Service, via official twitter feeds, from areas with high Hispanic populations. It can be concluded that many forecasting offices do not currently meet the communication needs of Spanish-Speaking populations and that critical alerts about life threatening risks should be made more frequently in Spanish.

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ABSTRACT:

This dataset includes data collected using a mobile sensing platform during baseflow and stormflow conditions in the Northwest Field Canal, located in Logan, UT. Data were collected by floating a payload of sensors in a longitudinal transect down the length of the canal and recording latitude, longitude, and several water quality variables, including fluorescent dissolved organic matter (FDOM), observations from custom fluorometers designed for calculating the fluorescence index (FI), dissolved oxygen, temperature, pH, specific conductance, and turbidity. The methods used in collection and processing of these data are described in detail in the methods document included within this resource.

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ABSTRACT:

This dataset includes grab sample data collected during baseflow and stormflow conditions in the Northwest Field Canal (NWFC), located in Logan, UT. Grab sample data includes results from samples that were analyzed using dissolved organic carbon concentration analysis and excitation emission matrix spectroscopy to determine organic matter concentration and characteristics. Methods used in sample collection and analysis are described in detail within the methods document included as part of this resource.

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ABSTRACT:

This dataset includes time series data collected during baseflow and stormflow conditions in the Northwest Field Canal, located in Logan, UT. Time series data includes fluorescent dissolved organic matter (FDOM), observations from custom fluorometers used to calculate the fluorescence index in situ, turbidity, and rainfall. Methods used for deploying sensors, collecting data, and processing for quality control are described in the methods document contained within this resource.

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Total mercury and methylmercury in Great Salt Lake water, sediment, and biota
Created: Oct. 31, 2017, 5:08 p.m.
Authors: Frank Black · Carla Valdes · William Johnson · Jeffrey N. Collins · James R. Goodman · Heidi J. Saxton · Christopher R. Mansfield · Joshua N. Schmidt · Shu Yang · Neil Swanson · Brooks Black · Blair Stringham · Abigail Rudd · Greg Carling · Ryan Rowland · Christine Rumsey

ABSTRACT:

Concentrations of total mercury (HgT) and methylmercury (MeHg) in Great Salt Lake (GSL) water, superficial sediment, brine flies, and ducks collected before (2007-2012) and after (2015-2016) closure of the culverts in the railroad causeway in late 2013. These data are discussed in the publication: Valdes, C., Black, F.J., Stringham, B., Collins, J.N., Goodman, J.R., Saxton, H.J., Mansfield, C.R., Schmidt, J.N., Yang, S., and Johnson, W.P., 2017. Total mercury and methylmercury response in water, sediment, and biota to destratificaiton of the Great Salt Lake, Utah, USA. Environmental Science and Technology, 51: 4887–4896.
Water column chemical and physical conditions were characterized at locations across the south arm of GSL. Water samples were collected at 0.2 m below lake surface and 0.5 m above lake bottom, referred to as shallow and deep samples, respectively. Water column temperature, specific conductance, pH, and dissolved oxygen (DO) were measured in the field using a calibrated YSI probe. Sulfide was measured in filtered water samples in the field using a photometric method (CHEMetrics). Water samples were collected by peristaltic pump using acid-washed teflon tubing and bottles. Filtered water samples were passed through a 0.45-micron pore size, capsule filters in the field. Water samples for HgT and MeHg were acidified to 0.5% using sulfuric acid the same day as sampling, then refrigerated until analyzed.
Water for HgT was oxidized by amendment to 5% BrCl. HgT was determined via reduction with SnCl2, purge and trap onto gold, thermal desorption, with quantification by cold vapor atomic fluorescence spectroscopy (CVAFS). MeHg concentration in water was measured after distillation with ammonium pyrrolidine dithiocarbamate, aqueous phase ethylation, purge and trap onto tenax, thermal desorption, pyrolitic decomposition, and CVAFS. Water samples for dissolved organic carbon analysis were placed on ice in the field, refrigerated, and measured (TOC-5000a, Shimadzu) within one week of collection using EPA Method 1684.
Surficial sediment was sampled at eleven sites in the GSL, and were collected by peristaltic pump using acid-washed PTFE tubing into FLPE bottles, and stored on ice in the field. Subsamples were oven dried at 105°C for 12 hours and re-weighed to determine water content and allow conversion between wet and dry weight (without salt correction). HgT was extracted from sediment by digestion in a 7:3 mixture of HNO3:H2SO4 at 80°C for 6 hours, followed by amendment to 5% BrCl. MeHg was leached from sediment with a mixture of potassium bromide, sulfuric acid, and copper sulfate, extracted into methylene chloride, back extracted into water, followed by aqueous phase ethylation, purge and trap, thermal desorption, pyrolitic decomposition, and CVAFS detection. Certified reference materials (CRMs) for HgT (MESS-3) and MeHg (CC-580) in sediment were analyzed.
Adult brine flies (Ephydra spp.) were collected from Lady Finger Point on Antelope Island. Flies were collected with nets, transferred into polypropelene tubes, placed on ice in the field, and frozen in the lab. Waterfowl were harvested with shotguns using non-lead from the GSL and surrounding wetlands. The age of each bird was determined by physical characteristics. The species sampled were Northern Shovelers (Anas clypeata), Mallard (Anas platyrhynchos), Gadwall (Anas strepera), and Cinnamon Teal (Anas cyanoptera). Tissue samples were frozen, later thawed, the skin removed, and breast muscle tissue was harvested.
Brine fly and waterfowl samples were freeze-dried and homogenized prior to analysis, and thus all HgT concentrations in biota are reported on a dry weight basis. Brine flies were digested in a 2:1 mixture of HNO3:H2SO4. Samples predigested at room temperature for 1 hour, then at 100 °C for 4 hours, then were amended to 1% BrCl. Digested samples were measured by oxidation with BrCl, reduction with SnCl2, purge and trap using dual-stage gold trap amalgamation and quantification by CVAFS. The duck muscle tissue was analyzed using thermal decomposition, amalgamation, and atomic absorption spectrophotometry using a DMA-80. Each analysis run included each of the CRMs TORT-2 and DORM-3.
Data contributors and project collaborators include Carla Valdes, Frank J. Black, Jeffrey N. Collins, James R. Goodman, Heidi J. Saxton, Christopher R. Mansfield, Joshua N. Schmidt, Shu Yang, William P. Johnson, Neil Swanson, Brooks Black, Abigail Rudd, Greg Carling, Diego P. Fernandez, John Luft, JimVan Leeuwend, Ryan Rowland, and Christine Rumsey.
Funding sources include the National Science Foundation, iUTAH-innovative Urban Transitions and Aridregion Hydro-sustainability, NSF Award Number 1208732, the Utah Division of Forestry, Fire, and State Lands (FFSL) of the Utah Department of Natural Resources, the W.M. Keck Foundation via the BRINE project, and NSF Award Number 1637196.

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Economics of water conservation in irrigated landscapes
Created: Nov. 4, 2017, 1:58 a.m.
Authors: Charles Sims · Augustina Odame

ABSTRACT:

The purpose of this research effort is to improve understanding of two key drivers of water use in irrigated landscapes: 1) irrigation technology adoption and 2) irrigation district hierarchies. The methodology used to address the first driver focuses on integrating economic models of optimal investment with hydrologic models of annual streamflow. Specifically, this approach quantifies how streamflow trends and streamflow variability influence the adoption of more efficient irrigation technologies in three watershed in Cache Valley. This improved understanding of the influence of streamflow trends and variability can be used to predict how one specific form of climate adaptation (uptake of water-saving irrigation technologies) will evolve in response to climate trends and variability. The methodology used to address the second driver is an agent-based model of the behaviors of canal district managers and owners. This methodology allows us to specify both economic and non-economic behaviors employed by three agent types (canal manager, residential water users, agricultural water users) in a specific canal in Cache Valley. The model accounts for realistic hydrologic aspects of the canal, the hierarchical relationship between canal managers and water users, as well as the variety of water use objectives held by owners of the canal company. This research provides an initial glimpse of the relative importance of institutions, social norms, and economics in water use decisions. These research efforts help solidify the links between RFA2 and RFA3.

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ABSTRACT:

This model instance represents a high resolution urban stormwater model developed using the Environmental Protection Agency's Stormwater Management Model (SWMM) for the City of Logan, Utah. It was developed as part of a larger coupled modeling effort, where the SWMM model represents only the built conveyance network of the stormwater conveyance system including pipes, inlets, outfalls, culverts, etc. This SWMM model was developed using high resolution geospatial survey data collected by Logan's public works department. This model was coupled to a larger two-dimensional hydraulic model that simulates overland and riverine flow. The SWMM model provided in this resource has, however, not been calibrated.

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Intermountain West Counties database
Created: Dec. 14, 2017, 10:44 p.m.
Authors: Carlos Licon · Ole Sleipness

ABSTRACT:

The data set contains 267 indicators for the 414 counties of the 11 states that contain the Intermountain West region in U.S. The specific counties that make the Intermountain West are a subset of 246 counties identified in the dataset. The reason to include all the counties in the dataset is to allow the removal or addition of counties according to different criteria. Different considerations of what criteria should be followed to define the intermountain West region can produce different groupings of counties. This dataset will be used to identify and evaluate sustainable development possibilities for each individual county through a comparative performance analysis. The dataset contains indicators measuring three aspects of each county: individual sociodemographic composition, economic characteristics, and the environmental and biophysical aspects of each county. All the information has been obtained from public access sources as indicated in the labels file.

A separate file (sIMWscores) contains the scores calculated through a comparative performance assessment of indicators. These scores evaluate the following for each county in the Intermountain West:

1. Six different types of restrictions mutually imposed between the economic, environmental, and social indicators
• the social restrictions to environmental activities
• the social restrictions to economic activities
• the environmental restrictions to economic activities
• the environmental restrictions to social activities
• the economic restrictions to social activities
• the economic restrictions to environmental activities

2. Three scores describing individual performance of environment, social, and economic activities as defined through the combined indicators performance.
• percent of total possible environmental activities
• percent of total possible social activities
• percent of total possible economic activities

3. The overlap of
• social and economic activities
• economic and environmental activities
• environmental and social activities

4. The overlap of all three sectors, which constitutes the possibilities for sustainable development

5. The conflict scores between environmental, social, and economic activities, produced by restrictions.
• conflicts between social and economic activities
• conflicts between economic and environmental activities
• conflicts between environmental and social activities

Scores calculates through a performance based comparison of a selection of indicators. These indicators were selected by a group of planning experts. The assessment model and the graphic outputs are available from the authors (by request).

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Aquatic GAMUT sensor data download (WaterML in R)
Created: Jan. 2, 2018, 8:38 p.m.
Authors: Erin Jones

ABSTRACT:

This dataset includes R code, specifically the package WaterML, to download water quality data from iUTAH GAMUT station sensors installed to look at water quality/quantity along three montane-to-urban watersheds: Logan River, Red Butte Creek, and Provo River. An explanation of the GAMUT sensor network can be found at gamut.iutahepscor.org. The code requires installation of packages 'plyr' and 'WaterML'. Instructions for modifying code to extract sensor data for your timepoint of interest are included in the README file. The code has the option to write sensor data to .csv files in your working directory.

Additional code available at https://github.com/erinfjones/GAMUTdownload

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ABSTRACT:

Annual melting of the snow pack in the Uintah Mountain range flush trace metals from the soil profile into the Provo river. River sampling, in addition to sampling overland flow during melting events indicate the concentrations of trace metals in the watershed. This sampling offers many insights into the chemistry of the watershed, but does not help us locate the origins of trace metals as they are flushed from the soil profile into the Provo river. This study was done to measure spatial variations of physical and chemical soil characteristics that effect the mobility and bioavailability of trace metals during annual snow melt. Our goal is to use data to identify areas within the watershed where pockets of trace metals might be highest. This will allow future soil and water sampling to hone in on specific areas of the watershed. Future sampling will include XRD, static leaching, and isotope analysis. Furthering the knowledge of biogeochemical process in the Provo river watershed.
Sample sites were randomly and evenly distributed in the Upper Provo River Watershed. Using long/lat lines on google earth to create 10 quadrants. Two sites within each quadrant were selected to produce 20 sample sites. Four of these 20 sites were purposefully selected due to the presence of lysimeters where previous research had been done in relation to other Provo River iUTAH research projects. This created site ID's, an example being Q1.L1 referring to quadrant 1, and site one which contained a lysimeter. Q1.2 refers to the second site within quadrant one and does not contain a lysimeter. Soil samples were collected contemporaneously using a standard soil T-probe. Visual observations, such as slope, and basic ecological observations such as dominant vegetation type, and observable health of vegetation were also noted. Samples were dried and ground in the BYU Environmental Analytical Lab. Tests performed were: texture (particle fraction analysis), pH (saturated paste), electrical conductivity (EC), % Organic Matter (Wakley-Black titration), Total Carbon/Total Nitrogen (LECO CN Determinator), Nitrate (Chromotrophic Acid), and microwave digestion/ICP-OES. Results were hand recorded before being entered onto an excel spreadsheet.
All samples were collected on Monday June 26 2017 between the hours of 7am-7pm.

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The impact of competition on plant water use efficiency
Created: Jan. 17, 2018, 1:36 a.m.
Authors: Rosanise Odell · William Anderegg · Kailiang Yu

ABSTRACT:

Plants experience stress competing for water with neighboring plants, both with members of the same species (intraspecific competition) and different species (interspecific competition). As plants conduct photosynthesis, they open pores in their leaves called stomata to uptake carbon dioxide from the atmosphere. However, there is a tradeoff: as carbon is gained, water is lost through evaporation as stomata open during the transpiration process. This tradeoff—the carbon gain to water lost during photosynthesis—represents the plant’s water use efficiency. Plant physiological stress due to external factors may affect stomatal regulation and water use efficiency. Through two experiments, one in a controlled growth chamber and the other in the natural area of Red Butte Garden, this study analyzes the differences in water use efficiency of native Utah plant species (Populus tremuloides, Quercus gambelii, Acer grandidentatum and Acer negundo) as they face differing levels of interspecific and intraspecific competition. We found that generally, plants facing higher levels competition exhibit lower water use efficiency. Understanding the correlation between competition and water use efficiency will help predict future plant and forest success not only to stressors such as competition, but also to changing water availability resulting from global climate change.

The datasets contained here are as follows: calculated water use efficiency (WUE) and competition indices (CI) for individual trees in Red Butte Garden interspecific experiment: Quercus gambelii, Acer grandidentatum and Acer negundo (using Hegyi’s 1974 equation for competition index), and the transpiration (E), photosynthesis (A) and stomatal conductance (gs) for each tree. There were two dates of data collection: June 28, 2016 and July 3, 2016. These same gas exchange variables were recorded for the intraspecific competition experiment, using data from the Anderegg Lab's drought experiment of Populus tremuloides in Fall of 2016. P. tremuloides were either planted one to a pot, or two, to mimic an environment with no intraspecific competition or with intraspecific competition.

Competition indices were calculated using measurements of DBH (diameter at breast height) of 3 experimental trees for each named species in the interspecific competition experiment, and compared to distance from surrounding trees in a 7.0 m radius. Gas exchange variables were obtained from output from a LiCor 6800. Water use efficiency of each tree was calculated with the equation WUE=A/gsw.

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Logan River, flow and stage at Dewitt Springs
Created: Jan. 28, 2018, 6:48 p.m.
Authors: Bethany Neilson

ABSTRACT:

The QC0 file contains the raw pressure, temperature, and depth data collected by an in-situ AquaTroll. The QC1 file contains the quality-controlled depth data and the derived stage and discharge data. The depth data is a measure of the water surface elevation relative to the AquaTroll. The derived stage data is the water surface elevation relative to a benchmark at the site. The discharge data is calculated from the stage data using the relationship established from the site rating curve. The stage-discharge relationship was developed by making measurements of flow and stage under varying flow conditions and thus establishing a relationship between water depth and flow at the site. Flow measurements were made with a YSI Flowtracker handheld ADV using the velocity area method.

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ABSTRACT:

The QC0 file contains the raw pressure, temperature, and depth data collected by an in-situ AquaTroll. The QC1 file contains the quality-controlled depth data and the derived stage and discharge data. The depth data is a measure of the water surface elevation relative to the AquaTroll. The derived stage data is the water surface elevation relative to a benchmark at the site. The discharge data is calculated from the stage data using the relationship established from the site rating curve. The stage-discharge relationship was developed by making measurements of flow and stage under varying flow conditions and thus establishing a relationship between water depth and flow at the site. The barometric pressure data was collected using an in-situ BaroTroll. Flow measurements were made with a YSI Flowtracker handheld ADV using the velocity area method or a Teledyne StreamPro ADCP.

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Logan River, flow and stage at Beaver Creek
Created: Jan. 28, 2018, 8:44 p.m.
Authors: Bethany Neilson

ABSTRACT:

This dataset contains flow and stage data for Beaver Creek, a tributary to the Logan River. The QC0 file contains the raw pressure, temperature, and depth data collected by an in-situ AquaTroll. The QC1 file contains the quality-controlled depth data and the derived stage and discharge data. The depth data is a measure of the water surface elevation relative to the AquaTroll. The derived stage data is the water surface elevation relative to a benchmark at the site. The discharge data is calculated from the stage data using the relationship established from the site rating curve. The stage-discharge relationship was developed by making measurements of flow and stage under varying flow conditions and thus establishing a relationship between water depth and flow at the site. Flow measurements were made with a YSI Flowtracker handheld ADV using the velocity area method.

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Logan River, flow and stage at Wood Camp
Created: Jan. 28, 2018, 8:48 p.m.
Authors: Bethany Neilson

ABSTRACT:

This dataset contains stage and flow data at Wood Camp on the Logan River. The QC0 file contains the raw pressure, temperature, and depth data collected by an in-situ AquaTroll. The QC1 file contains the quality-controlled depth data and the derived stage and discharge data. The depth data is a measure of the water surface elevation relative to the AquaTroll. The derived stage data is the water surface elevation relative to a benchmark at the site. The discharge data is calculated from the stage data using the relationship established from the site rating curve. The stage-discharge relationship was developed by making measurements of flow and stage under varying flow conditions and thus establishing a relationship between water depth and flow at the site. Flow measurements were made with a YSI Flowtracker handheld ADV using the velocity area method or using a truck with a boomed and line attached to a weight and a Marsh Mcbirney Flo-mate 2000.

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ABSTRACT:

This dataset contains flow, stage, and barometric pressure data for Right Hand Fork, a tributary to the Logan River. The QC0 file contains the raw pressure, temperature, and depth data collected by an in-situ AquaTroll. The QC1 file contains the quality-controlled depth data and the derived stage and discharge data. The depth data is a measure of the water surface elevation relative to the AquaTroll. The derived stage data is the water surface elevation relative to a benchmark at the site. The discharge data is calculated from the stage data using the relationship established from the site rating curve. The stage-discharge relationship was developed by making measurements of flow and stage under varying flow conditions and thus establishing a relationship between water depth and flow at the site. Flow measurements were made with a YSI Flowtracker handheld ADV using the velocity area method. The barometric pressure data was collected using an in-situ BaroTroll.

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ABSTRACT:

The QC0 file contains the raw pressure, temperature, and depth data collected by an in-situ AquaTroll. The QC1 file contains the quality-controlled depth data and the derived stage and discharge data. The depth data is a measure of the water surface elevation relative to the AquaTroll. The derived stage data is the water surface elevation relative to a benchmark at the site. The discharge data is calculated from the stage data using the relationship established from the site rating curve. The stage-discharge relationship was developed by making measurements of flow and stage under varying flow conditions and thus establishing a relationship between water depth and flow at the site. Flow measurements were made with a YSI Flowtracker handheld ADV using the velocity area method. The barometric pressure data was collected using an in-situ BaroTroll.

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Logan River, flow and stage at Ricks Spring
Created: Jan. 28, 2018, 9 p.m.
Authors: Bethany Neilson

ABSTRACT:

This dataset contains flow and stage data for Rick's Spring, a tributary to the Logan River. The QC0 file contains the raw pressure, temperature, and depth data collected by an in-situ AquaTroll. The QC1 file contains the quality-controlled depth data and the derived stage and discharge data. The depth data is a measure of the water surface elevation relative to the AquaTroll. The derived stage data is the water surface elevation relative to a benchmark at the site. The discharge data is calculated from the stage data using the relationship established from the site rating curve. The stage-discharge relationship was developed by making measurements of flow and stage under varying flow conditions and thus establishing a relationship between water depth and flow at the site. Flow measurements were made with a YSI Flowtracker handheld ADV using the velocity area method.

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Composite Resource Composite Resource
Quality Control Experiment
Created: Feb. 22, 2018, 11:37 p.m.
Authors: Amber Jones · Dave Eiriksson · Jeffery S. Horsburgh

ABSTRACT:

These are data resulting from and related to an effort to examine subjectivity in the process of performing quality control on water quality data measured by in situ sensors. Participants (n=27) included novices unfamiliar with and technicians experienced in quality control. Each participant performed quality control post processing on the same datasets: one calendar year (2014) of water temperature, pH, and specific conductance. Participants were provided with a consistent set of guidelines, field notes, and tools. Participants used ODMTools (https://github.com/ODM2/ ODMToolsPython/) to perform the quality control exercise. This resource consists of:
1. Processed Results: Each file in this folder corresponds to one of the variables for which quality control was performed. Each row corresponds to a single time stamp and each column corresponds to the processed results generated by each participant. The first column corresponds to the original, raw data.
2. Survey Data: The files in this folder are related to an exit survey administered to participants upon completion of the exercise. It includes the survey questions (pdf), the full Qualtrics output (QualityControlSurvey.pdf), data and metadata files organized and encoded for display in the Survey Data Viewer (http://data.iutahepscor.org/surveys/survey/QCEXP) (QCExperimentSurveyDataFile.csv, QCExperimentSurveyMetadata.csv), and a file used to organize data for plots for the associated paper.
3. Field Record: Participants were provided this document, which gives information about the field maintenance activities relevant to performing QC.
4. Scripts: Each file in this folder corresponds to a script automatically generated by ODMTools while performing quality control. The files are organized by user ID and by variable.
5. Code and Analysis: Script used to generate the figures for this work in the associated paper. It is important to note that novice users correspond to IDs 1-22 and experienced users correspond to IDs 25-38. This folder also includes subsets of the data organized in supporting files used to generate Figure 6 (ExpGapVals.xlsx) and Table 5 (NoDataCount.xlsx).

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Generic Generic

ABSTRACT:

Representing urban water demands economically is useful to understand how anticipated changes like population growth, conservation, water development, climate change, and environmental water demands may affect water deliveries and scarcity. Utah is the second driest state in the nation, while per capita water use is near the highest in the nation, averaging 167 gallons per person per day. This implies that creative water management will be ongoing in Utah’s future. Urban economic loss functions are estimated using residential demand functions for Utah’s Wasatch Front Metropolitan Area, which includes Logan, Salt Lake City, Ogden, Layton, Provo, and Orem urban regions. Water price, volume of water applied at that price, urban population, and price elasticity data are presented. Results show seasonal residential water demand functions and seasonal urban (residential, industrial, institutional, and commercial) economic loss functions for Logan, Ogden, Salt Lake City, and Provo metropolitan areas. Limitations to this method are outlined and discussion focuses on estimating urban water demand functions and potential economic losses input into hydro-economic models and ecological-economic models to evaluate promising solutions to Utah’s persistent water problems.

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Composite Resource Composite Resource
Spawn Creek - Beaver Pond Water Quality data
Created: June 13, 2018, 4:49 p.m.
Authors: Deni Murray · Janice Brahney · Bethany Neilson

ABSTRACT:

Beavers alter stream environments by impounding flow and flooding the landscape. This project aims to test whether beaver dams alter the stream biogeochemistry and productivity. Specifically, we hypothesize that dam will be warmer, have greater productivity (measured by chlorophyll proxy), and higher DOC, turbidity, and nutrient concentrations than downstream areas. Field methods include water, periphyton and sediment sampling in paired beaver ponds and stream areas immediately downstream of the dam. Additional sites include one below all dams and one above all dams. We analyzed Spawn Creek which has current beaver activity.

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Generic Generic

ABSTRACT:

Municipal water managers face increasing challenges to manage already over allocated water resources due to changes in climate, technology and infrastructure, and conflicting goals set by stakeholders. To address these challenges, researchers have used unvalidated agent-based models and water pricing as means to test new management strategies to increase water conservation adoption by household users. In addition, water use reduction has been found to be inelastic to its cost, as the decision-making process made by household users whether to conserve water is still relatively unknown. Managers need more information on how households use and decide to change their water use to better address these growing challenges. This project addresses how to quantify the household decision making process by merging psychological attributes (Motivation, Social Network Influence, Opportunity, Encouragement) with known physical household attributes to further explain water use. This was achieved by using survey, landscape, high-frequency indoor appliance water use, and weather data as input to a household water use in an agent-based model framework. This data is specific to Logan UT and comes from the iUTAH 2014 survey, Utah mapping portal, local weather monitoring stations, and studies of indoor water use. The resulting agent-based model is used to observe and illustrate how Logan UT household water use could change if the needs of the household’s psychological attributes are met. Validation of the model’s outputted water use was achieved using Logan UT 2014 linked water use and billing. Results show that water use validation worked well for indoor use with the matching of appliances to the number of people living within the home because the high-frequency indoor appliance data used was a good representation of indoor water use, whereas outdoor use validation was more difficult due to the wide variation in plant and soil composition of households, landscape watering methods including secondary water use, and residential behaviors of over and under watering. Households with high Motivation, Social Network Influence, and Opportunity behavioral attributes saved more water than those that did not. Encouragement alone did not increase water conservation very much. However, when combined with Social Network Influence, they had a much larger impact on how households made decisions, and that the size and shape of the network structure mattered less than the quality of the content being shared through the network. These results suggest water managers could increase household water conservation by being aware of specific behavioral attribute that contribute to the conservation adoption processes, which could be determined through the use of annual surveys. Water managers should also include a bottom-up information exchange network amongst households into existing top-down management strategies to further increase the chance that household water users will respond to management strategies. This database contains the following: 1) the 1_ArcMap Folder which contains an ArcMap desktop files used to determine the landscape data; 2) the 2_Data Compile Folder which contains all data that was used to complete this project and produce the model inputs; 3) the 3_ABM Model Folder which holds the project agent-based model, its inputs and results; 4) the 4_R Code Folder which holds the R code used to generate results for the published research paper. All of which is detailed in the accompanying Read Me file.

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Script Resource Script Resource
Stochastic Harmonic Autoregressive Parametric (SHArP) Weather Generator
Created: June 25, 2018, 8:21 p.m.
Authors: Kimberly Smith · Courtenay Strong · Firas Rassoul-Agha

ABSTRACT:

This collection of MATLAB scripts runs the temperature component of the stochastic harmonic autoregressive parametric (SHArP) weather generator, which simulates trended, nonstationary precipitation occurrence, precipitation amount, and temperature values. The precipitation component is not included here because it is based off of previous weather generators and doesn't use any new methods. The temperature component follows a concept introduced in previous studies, but SHArP simulates temperature values directly as opposed to simulating the temperature residuals. SHArP weather generator validation and illustrations at a single site have been published in the Journal of Applied Meteorology and Climatology (Smith et al. 2017; "A new method for generating stochastic simulations of daily air temperature for use in weather generators"; https://doi.org/10.1175/JAMC-D-16-0122.1), and the multisite generalization of SHArP is in press in the same journal (Smith et al. 2018; "Multisite generalization of the SHArP weather generator"; https://doi.org/10.1175/JAMC-D-17-0236.1).

How to use:
- All input data need to be combined into a single .mat structure file and contain the number of locations to be simulated, the number of days to simulate, a time matrix (in format: year month day), the day of year corresponding to each day, the precipitation occurrence 1s and 0s in logical format corresponding to "wet" or "dry" days (determined from observations or downscaled climate model output), the maximum temperature training data for each site (i.e. observations or downscaled climate model output), and the minimum temperature training data for each site.
- This .mat structure file (called "sett") is the input to fit_SHArP_1, which fits the parameters needed to run the model. fit_SHArP_1 internally uses fit_SHArP_var_1a to determine the coefficients for each of the 26 variables per site in the model; this latter script is not run separately. The output from fit_SHArP_1 is called the driver_t structure and needs to contain maximum and minimum temperature data (from observations or downscaled climate model output), the precipitation occurrence 1s and 0s in logical format corresponding to "wet" or "dry" days (determined from observations or downscaled climate model output), a time matrix (in format: year month day), a variable structure that contains the 26 coefficients for each variable at each site, b_k, c_k, and the results from the EOF analysis on the precipitation occurrence patterns.
- The driver_t structure is the input to simulate_SHArP_2, which gives maximum temperature and minimum temperature as output. This script can also be modified to output the temperature mean and noise but note that this will increase computation time significantly.

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Composite Resource Composite Resource

ABSTRACT:

This data set is a composite of all data which were used in our analysis. These data include avian species abundance counts, human disturbance assessment, habitat type, elevation, and latitude/longitude for each monitoring location. Additional abundance data were incorporated from eBird.org, and the Partners in Flight Species Assessment Scores were retrieved for all documented species for which they were available. The data set also includes preliminary summary statistics for each site that was later used in our analysis.

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Generic Generic
The effect of anthropogenic nitrogen and sedimentation on primary producers mediated through tadpole bioturbation
Created: June 26, 2018, 8:10 p.m.
Authors: Betsy Bancroft · Terri Hildebrand · Barry Baker · Erika Seirup · Kylie Gillins

ABSTRACT:

Freshwater habitats comprise some of the most altered ecosystems on Earth, primarily due to anthropogenic disturbances in hydrology and nutrient cycling. Many freshwater systems in North America are limited by nitrogen and phosphorus, and their addition from anthropogenic sources (from agricultural and residential runoff or atmospheric deposition from air pollution) can cause eutrophication. Changes in abiotic and biotic factors due to eutrophication often result in reduced water quality and ecosystem services such as water filtration. Projected shifts in regional precipitation and temperature as a component of global climate change will further alter the functioning of freshwater ecosystems. Alterations in precipitation, coupled with shifts in land-use, are projected to increase sediment loading in freshwater systems. Sediment loading in freshwater ecosystems can result in changes to community structure, biomass, and primary productivity. In addition, sedimentation can reduce net photosynthesis rates by smothering periphyton, the photosynthetic protists that exist in the biofilm that forms on surfaces. Sediment can be cleared in freshwater systems through several routes, including consumption of sediments by animals and bioturbation (biological activity that influences sediment transport, deposition, and accrual). Larval amphibians (primarily tadpoles) may play an important role in sediment accrual and nutrient recycling rates through both sediment consumption and bioturbation. Bioturbation by larval amphibians, as any other behavior, may be affected by environmental stressors. Nitrogen, in the form of nitrate or nitrite, may influence tadpole activity rate. Although we have an understanding of the effects of nutrient and sediment loading on aquatic systems, we do not understand how organisms such as larval amphibians might mediate the effects of these two stressors on primary producers in aquatic systems. Bioturbation and grazing by amphibians could affect growth of primary producers in three ways: 1) tadpoles could increase the amount of nitrogen suspended in the water column; 2) tadpoles can clear sediment from surfaces, thereby increasing light available for periphyton photosynthesis; 3) tadpole grazing on primary producers (phytoplankton and periphyton) could reduce biomass of these primary producers. Sedimentation and nutrient loading are issues negatively affecting Utah’s water quality.
Our work focuses on two areas of the southern region where nitrogen inputs and sedimentation are important regional stressors. We will first sample natural sedimentation rates and nitrogen levels in ponds at the Canyonlands Research Center (near Moab, UT) and sites in and near Cedar City, UT, and then experimentally manipulate nitrate addition, macrophyte presence, sedimentation, and tadpole presence to test the effects of nitrogen and sedimentation on tadpole behavior and primary production. Our work will begin to identify potential community linkages in consumers and primary producers in the presence of two abiotic stressors. Understanding the connections among species and how those connections influence the response of functional groups in the community (i.e. primary producers) is increasingly important in the face of local and global environmental changes.

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Composite Resource Composite Resource

ABSTRACT:

This project involved 20 semi-structured interviews with iUTAH researchers to ask questions pertaining to teamwork processes inherent in large scale interdisciplinary projects. Additionally, questions pertaining to project success and project evaluation were asked. Interviews were conducted either in-person with researchers who were located in the state, and over the phone with researchers who were located out of the state. Interviews were recorded and transcribed and analyzed for the aforementioned themes. Interviews may not be shared in order to protect the identify of participants. At the completion of the project, a masters thesis will be made publicly available describing the methods and findings from this project.

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Generic Generic

ABSTRACT:

This project is a compilation and synthesis of publications by researchers on the iUTAH project (innovative Urban Transitions and Aridregion Hydro-sustainability) who were focused on social and engineering water science (referred to as Research Focus Area 2 or RFA2). Data are represented in a spreadsheet coded for various attributes, including each paper's objective, core finding, summary contribution, unit of analysis, geographic focus, and connection to iUTAH's iSAW conceptual framework (Hale et al. 2015). A codebook for variables is provided in a separate file. Ultimately, a manuscript will be written based on a synthesis of these data.

Hale RL, A Armstrong, MA Baker, S Bedingfield, D Betts‎, C Buahin, M Buchert, T Crowl, RR Dupont‎, JR Ehleringer, J Endter-Wada, C Flint, J Grant, S Hinners, JS Horsburgh, D Jackson-Smith, AS Jones, C Licon‎, SE Null, A Odame, DE Pataki, D Rosenberg, M Runburg‎, P Stoker, C Strong. 2015. iSAW: Integrating structure, actors, and water to study socio-hydro-ecological systems. Earth’s Future. 3(3): 110-132. https://doi.org/10.1002/2014EF000295.

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iUTAH RFA2 Impact Assessment Interviews
Created: July 23, 2018, 8:15 p.m.
Authors: Courtney Flint · K. Taylor Dean

ABSTRACT:

In order to assess the impacts on stakeholder decisions and actions linked to iUTAH's social and engineering science and research efforts, interviews were conducted in 2017 with 17 researchers and 13 external partners (who were identified by researchers as having been involved in collaborative efforts). Interviews were recorded, transcribed and analyzed thematically for reporting. For 16 participants (8 researchers and 8 external partners), a revised informed consent process was conducted in which they all agreed to be identified in project reporting on 4 case studies. All other participants remain confidential per the original informed consent process. We have included the interview protocols (questions) for researchers and partners (as questions asked to the researchers and partners differed slightly) as well as a summary report of findings.

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Model Instance Resource Model Instance Resource

ABSTRACT:

The results included are based on the HSPF model simulations developed for the Jordan River watersehds. The base model used to simulate was developed by a consultant (STANTEC in 2010/2011) and employed by the Salt Lake County, Utah. The model was calibrated and statistical results were checked only for the Big Cottonwood Canyons at the Canyons Mouth and other several location in the Jordan River. The model was applied to study climate and land use change in March 2017. The historical time periods considered are Jan1 1995 to Dec 31,2004. The calibration time period considered for the streamflow is Jan1,2005 to Dec 31,2006 (it varies for other water quality parameters considering the data availability). Future simulations include 2035 to 2044 and 2085 to 2094. The model results were simulated in an hourly time steps and this resource has the daily results. The results included are only for the climate change scenarios as the canyons have negligible effects of the land use and land cover changes. The three scenarios considered are based on the RCP6 climate scenario that was dynamically downscaled using the Weather Research & Forecasting (WRF) model and statistically downscaled two climate scenarios corresponding to the mean of the driest and wettest quartiles of the statistically downscaled CMIP5 database at https://gdo-dcp.ucllnl.org/downscaled_cmip_projections/dcpInterface.html .

For each streamflow tab in the file, the Observed column indicates results forcing the model with station observations. Future simulation columns labeled Min_* provide results for the mean of the driest quartile of CMIP5 simulations, RCP_* provide results for the WRF simulation of RCP 6.0, and Max_* provide results for the mean of the wettest quartile of CMIP5 simulations. The second tab in the file provides sample results from the HSPF standard calibration procedure.

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