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David E Rosenberg

Utah State University | Associate professor

 Recent Activity

ABSTRACT:

Each Climate Adaptation Science (CAS) project participant/group will complete a Data Collection Plan prior to starting project work. A data collection plan template is provided.

Complete the following for each data collection effort that has funding support from CAS or involves a CAS project participant. All fields are required. “Data” are interpreted broadly to mean all data, models, code, directions, and other artifacts developed and used as part of the effort. Note that if there are substantive changes to the types of data, methods, data formats, products, or availability of data, an updated plan should be submitted.

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ABSTRACT:

The Colorado River Compact apportions water between upper and lower basin and requires the upper basin to deliver a total of 7.5 MAF to lower basin each year. The Colorado river system has been very reliable in past and has survived many dry periods without failing to meet the demand requirements of both basins. The drought that began in the region at the turn of the century has rendered it very difficult for the upper basin to meet the delivery requirements to the lower basin. Many management options have been explored and some have been implemented to maintain increase the reliability of the system. This report focuses on creating a pareto front for the reliability of the Colorado river supply in response to demands to upper and lower basin. This could help in identify what would be the tradeoffs for reliability of one basin if the system is managed to meet the requirements of the other basin.

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ABSTRACT:

This resource shares raw and processed pressure transducer, river stage, river flow, river temperature, and channel cross-section data collected and estimated at the Morton Bear River Bottoms on the Bear River, Utah by undergraduate Freshmen Bear River Fellows participating in the Bear River Fellows program between August 14, 2013 and November 18, 2017 (http://BearRiverFellows.usu.edu).

A full description of resource contents is provided in the meta-data file MortonBearRiverFellowsRepositoryText.docx

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ABSTRACT:

This collection contains all resources generated as part of the Climate Adaptation Science (CAS) project (https://climateadaptation.usu.edu/). Resources include student course projects, research projects, internship work, assessments of educational outcomes, and other project materials. When creating resources, CAS participants will make all input data, models, code, results, instructions, and other digital artifacts developed for the project available for others to use, with the exception of sensitive human subjects data (expected level of reproducibility of at least Artifacts available). The steps at http://climateadaptation.usu.edu/project-data-models-code/ provide instructions for CAS participants to create a Hydroshare resource and request to add the resource to this collection. These steps were approved by the CAS Leadership Team on Nov. 15, 2018 and will be updated as needed. This collection is maintained by the CAS project coordinator.

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ABSTRACT:

For my term project for the Water Resources Systems Analysis course (CEE 6410), I will use systems analysis approach for improving aquatic habitat for Bonneville cutthroat trout (BCT) in the Bear River watershed in Utah. My goal is to maximize water depth for BCT habitat while meeting the electricity demand produced by hydropower in the watershed.

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 Contact

Resources
All 0
Collection 0
Composite Resource 0
Generic 0
Geographic Feature 0
Geographic Raster 0
HIS Referenced Time Series 0
Model Instance 0
Model Program 0
MODFLOW Model Instance Resource 0
Multidimensional (NetCDF) 0
Script Resource 0
SWAT Model Instance 0
Time Series 0
Web App 0
Generic Generic
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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Model Program Resource Model Program Resource
Blended Near Optimal Tools
Created: Feb. 20, 2017, 5:53 a.m.
Authors: David Rosenberg

ABSTRACT:

Links to the repository (https://github.com/dzeke/Blended-Near-Optimal-Tools) that stores the Matlab 2013a source code and (1) Documentation for blended near-optimal tools that (2) generate alternatives, (3) visualize alternatives, and allow a user to interactively explore the near-optimal region from which alternatives are generated. Also contains the data and model files for a (4) linear programming example application to manage water quality for Echo Reservoir, Utah, (5) mixed-integer programming example application to manage water supply and demands in Amman, Jordan, and (6) multi-objective linear programming reservoir operations problem.

Near-optimal alternatives perform within a (near-optimal) tolerable deviation of the optimal objective function value and are of interest to managers and decision makers because they can address un-modelled objectives, preferences, limits, uncertainties, or issues that are not considered by the original optimization model or it's optimal solution. Mathematically, the region of near-optimal alternatives is defined by the constraints for the original optimization model as well as a constraint that limits alternatives to those with objective function values that are within a tolerable deviation of the optimal objective function value. The code and tools within this repository allow users to generate and visualize the structure and full extent of the near-optimal region to an optimization problem. The tools also allow users to interactively explore region features of most interest, streamline the process to elicit un-modelled issues, and update the model formulation with new information. The tools and their use are described here for generating, visualizing, and interactively exploring near-optimal alternatives to optimization problems, but the tools are general and can be used to generate and visualize points within any high-dimensional, closed, bounded region that can be defined by a system of constraints. The parallel coordinate visualization and several interaction tools can also be used for any high-dimensional data set.

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Generic Generic

ABSTRACT:

This resource describes the data and script files used to mine text from 40 water resources systems analysis course syllabi and generate the results presented in Rosenberg et al (2017) "Towards More Integrated Formal Education and Practice in the Water Resources Systems Analysis." ASCE-Journal of Water Resources Planning and Management. The original course syllabi are available on a repository of water resources systems analysis teaching materials at http://ecstatic.usu.edu. The ReadMe file below further describes each file. This work is part of a larger effort to review 40 WRSA course syllabi, interview 10 practitioners, and compare skills taught to the skills practitioners say they need. A preprint of the acticle is provided in the .docx file.

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Generic Generic

ABSTRACT:

This resource describes the data and script files used to mine text from 40 water resources systems analysis course syllabi and generate the results presented in Rosenberg et al (2017) "Towards More Integrated Formal Education and Practice in the Water Resources Systems Analysis." ASCE-Journal of Water Resources Planning and Management. The original course syllabi are available on a repository of water resources systems analysis teaching materials at http://ecstatic.usu.edu. The ReadMe file below further describes each file. This work is part of a larger effort to review 40 WRSA course syllabi, interview 10 practitioners, and compare skills taught to the skills practitioners say they need. A preprint of the acticle is provided in the .docx file.

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Model Program Resource Model Program Resource
Value Landscape Engineering Lifecycle Model (VLE)
Created: April 16, 2018, 6:12 p.m.
Authors: David Rosenberg · Kelly Kopp · Heidi Kratsch · Larry Rupp · Paul Johnson · Roger Kjelgren

ABSTRACT:

The Value Landscape Engineering (VLE) spreadsheet program identifies the costs, labor, water, fertilizers, pesticides, energy, and fuel required to install and maintain a residential or commercial landscape in Utah. The program also identifies the carbon footprint and particulates generated from landscape installation and maintenance activities. VLE considers all activities associated with a particular landscape over its life with the goal to maximize value and reduce required inputs. The VLE spreadsheet program tabulates all onsite costs, inputs, and impacts over the life of the landscape including preparing the site, purchasing and installing materials, annual maintenance and operations, and replacing landscape features and components that wear out or die. A variety of program options allow the user to select the planting and mulch materials and coverage, structures, irrigation systems, equipment, and to tailor the analysis to site-specific conditions. Users can simultaneously compare up to three different landscapes.
Data to support the spreadsheet program was gathered from the scientific literature, nurseries, websites of manufacturers and home building supply stores, extension publications, and landscape cost estimate reports. Cache Valley and Wasatch Front arborists, landscapers, and Cooperative Extension professionals also provided information specific to their expertise. Because urban landscapes are complex systems, the spreadsheet program makes several simplifying assumptions. Thus, spreadsheet program estimates of required inputs and impacts are accurate to within 30%. Users should verify cost estimates with bids from landscape companies. Given these estimation levels, use the spreadsheet program to compare the relative advantages and tradeoffs among different landscapes. We demonstrate use of the spreadsheet program for three landscapes at the Jordan Valley Water Conservancy District (JVWCD) conservation garden. These landscapes are the Traditional Landscape that has a large area of cool-season turfgrass, shrubs, perennials, ground cover, and common shade trees; the Perennial Landscape that has mostly drought-tolerant perennials and annuals; and the Woodland Landscape that consists largely of drought-tolerant shrubs and trees. To verify spreadsheet program results, we compare spreadsheet program estimates of water, labor, fertilizer, and fuel use in each landscape to observations made over 8 years by JVWCD garden staff. Generally, spreadsheet program estimates and JVWCD staff observations agree within the 30% estimation level for the spreadsheet program. Homeowners, commercial property owners, and landscapers can use the spreadsheet program to identify the total costs, water use, and other required inputs for their landscape choices. The program can identify tradeoffs in costs, inputs, and impacts among an existing (or planned) landscape and modifications to it. By examining results and changing the landscape design, the user can develop a landscape plan that should cost less and require less water, labor, fertilizers, and other inputs.

The published version of the work is available at: Rosenberg, D. E., Kopp, K., Kratsch, H. A., Rupp, L., Johnson, P., and Kjelgren, R. (2011). "Value Landscape Engineering: Identifying Costs, Water Use, Labor, and Impacts to Support Landscape Choice." JAWRA Journal of the American Water Resources Association, 47(3), 635-649. http://dx.doi.org/10.1111/j.1752-1688.2011.00530.x.

Description of file contents:
1) VLE_Manual_Sept2011.pdf: Model manual including quick start guide and directions to use the spreadsheet model
2) ModelDataFiles.zip: Zip folder with files for the different versions of the model.
3) FileDescriptions.txt: Explanation of files in ModelDataFiles.zip and list of model versions

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Composite Resource Composite Resource

ABSTRACT:

This report uses linear optimization to identify a monthly reservoir release strategy that maximizes end-of-water-year storage in Island Park Reservoir, while also satisfying habitat and flow requirements for fish and anglers. Using historic data, I explore how these strategies change across different hydrologic regimes and which fishery constraints are the most limiting.

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Composite Resource Composite Resource

ABSTRACT:

For my term project for the Water Resources Systems Analysis course (CEE 6410), I will use systems analysis approach for improving aquatic habitat for Bonneville cutthroat trout (BCT) in the Bear River watershed in Utah. My goal is to maximize water depth for BCT habitat while meeting the electricity demand produced by hydropower in the watershed.

Show More
Collection Resource Collection Resource
Climate Adaptation Science Project Work
Created: Dec. 7, 2018, 7:03 p.m.
Authors: CAS Coordinator · David E Rosenberg

ABSTRACT:

This collection contains all resources generated as part of the Climate Adaptation Science (CAS) project (https://climateadaptation.usu.edu/). Resources include student course projects, research projects, internship work, assessments of educational outcomes, and other project materials. When creating resources, CAS participants will make all input data, models, code, results, instructions, and other digital artifacts developed for the project available for others to use, with the exception of sensitive human subjects data (expected level of reproducibility of at least Artifacts available). The steps at http://climateadaptation.usu.edu/project-data-models-code/ provide instructions for CAS participants to create a Hydroshare resource and request to add the resource to this collection. These steps were approved by the CAS Leadership Team on Nov. 15, 2018 and will be updated as needed. This collection is maintained by the CAS project coordinator.

Show More
Composite Resource Composite Resource

ABSTRACT:

This resource shares raw and processed pressure transducer, river stage, river flow, river temperature, and channel cross-section data collected and estimated at the Morton Bear River Bottoms on the Bear River, Utah by undergraduate Freshmen Bear River Fellows participating in the Bear River Fellows program between August 14, 2013 and November 18, 2017 (http://BearRiverFellows.usu.edu).

A full description of resource contents is provided in the meta-data file MortonBearRiverFellowsRepositoryText.docx

Show More
Composite Resource Composite Resource

ABSTRACT:

The Colorado River Compact apportions water between upper and lower basin and requires the upper basin to deliver a total of 7.5 MAF to lower basin each year. The Colorado river system has been very reliable in past and has survived many dry periods without failing to meet the demand requirements of both basins. The drought that began in the region at the turn of the century has rendered it very difficult for the upper basin to meet the delivery requirements to the lower basin. Many management options have been explored and some have been implemented to maintain increase the reliability of the system. This report focuses on creating a pareto front for the reliability of the Colorado river supply in response to demands to upper and lower basin. This could help in identify what would be the tradeoffs for reliability of one basin if the system is managed to meet the requirements of the other basin.

Show More
Composite Resource Composite Resource
CAS Data Collection Plan Template
Created: Jan. 17, 2019, 5:31 a.m.
Authors: David Rosenberg · CAS Coordinator

ABSTRACT:

Each Climate Adaptation Science (CAS) project participant/group will complete a Data Collection Plan prior to starting project work. A data collection plan template is provided.

Complete the following for each data collection effort that has funding support from CAS or involves a CAS project participant. All fields are required. “Data” are interpreted broadly to mean all data, models, code, directions, and other artifacts developed and used as part of the effort. Note that if there are substantive changes to the types of data, methods, data formats, products, or availability of data, an updated plan should be submitted.

Show More