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Anthony Michael Castronova

CUAHSI | Hydrologic Scientist

Subject Areas: Hydrology, Hydroinformatics, Hydrologic Modeling

 Recent activity

ABSTRACT:

Continued investment and development of cyberinfrastructure (CI) for water science research is transforming the way future scientists approach large collaborative studies. Among the many challenges, that we as a community need to address, are integrating existing CI to support reproducible science, enabling open collaboration across traditional domain and institutional boundaries, and extending the lifecycle of data beyond the scope of a single project. One emerging solution for addressing these challenges is HydroShare JupyterHub which is an open-source, cloud-based, platform that combines the data archival and discovery features of HydroShare with the expressive, metadata-rich, and self-descriptive nature of Jupyter notebooks. This approach offers researchers a mechanism for designing, executing, and disseminating toolchains with supporting data and documentation. The goals of this work are to establish a free and open source platform for domain scientists to (1) conduct data intensive and computationally intensive collaborative research, (2) utilize high performance libraries, models, and routines within a pre-configured cloud environment, and (3) enable dissemination of research products. This presentation will discuss our approach for hydrologic model simulation, sensitivity analysis, and optimization applications in this platform by establishing a generic CI pattern that can be adopted to support research, classroom, and workshop activities

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ABSTRACT:

This is a Jupyter notebook that demonstrates how NWM forecasts for Hurricane Harvey can be subsetted using the CUAHSI-JupyterHub architecture.

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ABSTRACT:

This is a HUC boundary that Hurricane Harvey hit.

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ABSTRACT:

Hydrologic Terrain Analysis Jupyter Notebook used to demonstrate the use of the Jupyter Notebook App for watershed delineation.

To use the Jupyter Notebook click on the "Open With" blue bottom at the top right of this page and choose "Jupyter". Then run the first few cells on the Welcome page. These cells establish a secure connection to the HydroShare and get the main notebook and the inputs to run the example. When the main code and the inputs are retrieved, you can click on "TauDEM.ipynb" to see the code and run it. The Jupyter Notebook also has steps to save all the inputs, outputs, and the main code into a new resource.

Presentation at EarthCube all hands meeting, June 6-8, 2018, Washington, DC https://www.earthcube.org/ECAHM2018

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ABSTRACT:

This is a Jupyter notebook that demonstrates how to preview Hurricane Harvey Streamflow data that is stored in an Observations Data Model v.2 SQLite file. It's meant to be executed on the https://jupyter.cuahsi.org notebook server and relies on several pre-installed packages, e.g. utilities.timeseries and utilities.hydroshare. This notebook will need to be modified for it to be executed elsewhere.

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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
JupyterHub Terrain Processing
Created: June 15, 2016, 3:37 p.m.
Authors: Tony Castronova

ABSTRACT:

An example workflow for processing DEM's. The JupyterHub notebook included within this resource uses the TauDEM library for parallel terrain processing operations.

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Geographic Raster Geographic Raster
Logan Digital Elevation Model
Created: July 22, 2016, 3:45 p.m.
Authors: Anthony Castronova

ABSTRACT:

A digital elevation model encompassing the Logan River watershed in northern Utah.

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Generic Generic
Beaver Divide Air Temperature
Created: July 22, 2016, 8:46 p.m.
Authors: Anthony Castronova

ABSTRACT:

iUTAH researchers have developed and deployed an ecohydrologic observatory to study water in ‘Gradients Along Mountain to Urban Transitions’ (GAMUT). The GAMUT Network measures aspects of climate, hydrology, and water quality along a mountain-to-urban gradient in three watersheds that share common water sources (winter-derived precipitation) but differ in the human and biophysical nature of land-use transitions. Designing GAMUT was a 12-month process involving faculty and technicians from across Utah’s research-intensive institutions: Brigham Young University, the University of Utah, and Utah State University.

This dataset contains raw data for all of the air temperature in degrees Celsius measured for the iUTAH GAMUT Network climate site near Beaver Divide.

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Generic Generic
RHESSys Sample Data
Created: Aug. 12, 2016, 4 p.m.
Authors: Anthony Castronova

ABSTRACT:

sample rhessys data

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Time Series Time Series

ABSTRACT:

This dataset contains time series of observations of water temperature in the Little Bear River, UT. Data were recorded every 30 minutes. The values were recorded using a HydroLab MS5 multi-parameter water quality sonde connected to a Campbell Scientific datalogger.

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Generic Generic
Site 1: Charters TWP., Plum run
Created: Feb. 23, 2017, 8:55 p.m.
Authors: Anthony Castronova

ABSTRACT:

This is my abstract

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Generic Generic
Climate Data Download for NOCA Observatory
Created: March 22, 2017, 6:02 p.m.
Authors: Anthony Castronova

ABSTRACT:

This a download of VIC fluxesw data and vizualization processing results from the Daily_VIC_1915_2011 (Livneh et al. 2013); Livneh B., E.A. Rosenberg, C. Lin, B. Nijssen, V. Mishra, K.M. Andreadis, E.P. Maurer, and D.P. Lettenmaier, 2013: A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions, Journal of Climate, 26, 9384–9392.

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Generic Generic
Services for Supporting Hydrologic Science
Created: March 27, 2017, 3:25 p.m.
Authors: Anthony Castronova

ABSTRACT:

This is a presentation that Tony Castronova gave at the 2017 Mason Water Forum at George Mason University. It outlines the data, training, and education/outreach services that CUAHSI provides to the water science community.

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Generic Generic
Daily Aggregate Temperature for Beaver Divide
Created: April 17, 2017, 3:47 p.m.
Authors: Anthony Castronova

ABSTRACT:

iUTAH researchers have developed and deployed an ecohydrologic observatory to study water in ‘Gradients Along Mountain to Urban Transitions’ (GAMUT). The GAMUT Network measures aspects of climate, hydrology, and water quality along a mountain-to-urban gradient in three watersheds that share common water sources (winter-derived precipitation) but differ in the human and biophysical nature of land-use transitions. Designing GAMUT was a 12-month process involving faculty and technicians from across Utah’s research-intensive institutions: Brigham Young University, the University of Utah, and Utah State University.

This dataset contains raw data for all of the air temperature in degrees Celsius measured for the iUTAH GAMUT Network climate site near Beaver Divide.

[Modified in JupyterHub on 2017-04-17 15:47:39.041903]
This daily average air temperature for the Beaver Divide gauging station that is maintained by iUtah researchers.

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Web App Resource Web App Resource
JupyterHub
Created: April 25, 2017, 2:32 p.m.
Authors: Anthony Castronova

ABSTRACT:

This web app launches HydroShare resources in a online Python environment using the JupyterHub software stack.

JupyterHub Version 1.1.2
https://github.com/hydroshare/hydroshare-jupyterhub/releases/tag/v1.1.2

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Composite Resource Composite Resource

ABSTRACT:

This is a step-by-step demonstration of how to view and download forecasts from any stream in the National Hydrography Dataset with the National Water Model App.

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Generic Generic
Summer Institute - JupyterHub Demos
Created: June 22, 2017, 3:01 a.m.
Authors: Anthony Castronova

ABSTRACT:

Jupyterhub demos that were presented to CUAHSI Summer Institute participants at the National Water Center in Tuscaloosa Alabama on 05/22/2017. This resource consists of the following material:

1. Powerpoint presentation outlining JupyterHub
2. NWM-preview.ipynb -- Uses iRODs to inspect and plot NWM data
3. HAND.ipynb -- Uses TauDEM to calculate height above nearest drainage for the Onion Creek watershed in Texas
4. Oniondata.tar -- Supplementary data for the Onion Creek watershed, used in the HAND.ipynb.
5. HAND-HydroTerre.ipynb -- Uses HydroTerre and TauDEM to extend HAND.ipynb for a different region of the U.S.

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Model Program Resource Model Program Resource
Storm Water Management Model (SWMM)
Created: June 3, 2015, 7:17 p.m.
Authors: Lewis Rossman · Trent Schade · Daniel Sullivan · Robert Dickinson · Carl Chan · Edward Burgess

ABSTRACT:

The EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas on which rain falls and runoff is generated. The routing portion of SWMM transports this runoff through a conveyance system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. SWMM was first developed back in 1971 and has undergone several major upgrades since then. The current edition, Version 5, is a complete re-write of the previous release. Running under Windows, EPA SWMM 5 provides an integrated environment for editing drainage area input data, running hydraulic and water quality simulations, and viewing the results in a variety of formats. These include color-coded drainage area maps, time series graphs and tables, profile plots, and statistical frequency analyses.

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Composite Resource Composite Resource

ABSTRACT:

Jupyter notebooks are becoming popular among the geoscience community for there ability to clearly present, disseminate, and describe scientific findings in a transparent and reproducible manner. This also makes them a desirable mechanism for sharing and collaborating scientific data and workflows with colleagues during the research process, especially when addressing large-scale cross-disciplinary geoscience issues. This work extends Jupyter notebooks to operate in a pre-configured cloud environment that is integrated with HydroShare for its data sharing and collaboration functionality, and notebooks are executed on the Resourcing Open Geospatial Education and Research (ROGER) supercomputer hosted in the CyberGIS center. This design enables researchers to address problems that are often larger in scale than can be done on a typical desktop computer. Additionally, the integration of these technologies enables researchers to collaborate on notebook workflows that execute in the cloud and are shared through the HydroShare platform. The goals of this work are to establish an open source platform for domain scientists to (1) conduct data intensive and computationally intensive collaborative research, and (2) organize data driven educational material via classroom modules, workshops, or training courses. This presentation will discuss recent efforts towards achieving these goals, and describe the architectural design of the notebook server in an effort to support collaborative and reproducible science.

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Generic Generic

ABSTRACT:

Data archival and dissemination is a challenging task for scientists and engineers, and if not done properly, hinders discovery of data applicable to an ongoing project. The next generation of scientists must be well versed in numerous methods of discovering, collecting, and processing water-related data, which is further complicated by the variety in data repositories, le formats, and encoding standards. CUAHSI (the Consortium of Universities for the Advancement of Hydrologic Science Inc.; https://www.cuahsi.org/) offers free data services and tools to address these issues. This workshop presents recent software development efforts to support (1) advanced data searching via the HIS Catalog API and (2) cloud-based hydrologic data analysis. The structure of this workshop will be a mixture of short presentations and interactive tutorials aimed to provide an introduction to research-oriented data discovery and analysis. Participants are encouraged to work through examples to better understand how they can leverage CUAHSI resources to supplement their research activities. We welcome participants that wish to learn how our tools and services can be leveraged in a research capacity.

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Generic Generic

ABSTRACT:

This resource was developed as a HydroShare workshop demonstration for the CUAHSI Hydroinformatics conference, July 25-27, 2017, Tuscaloosa, AL.

When you open this resource with the CUAHSI JupyterHub server (upper right, click on Open With, Select JupyterHub NCSA), you will launch a Welcome Notebook that will connect you to the CyberGIS virtual machine on the ROGER super computer at the University of Illinois, Urbana-Champagne. When you execute (Run Step 1 and Step 2 only) in the Jupyter Notebook cells on the Welcome Notebook, you will download related data and two Notebooks designed to explore hydrologic research problem solving using data and model integration in HydroShare . Skip Step 3 "Welcome" tutorial steps unless you want to explore how to do work and Save back to HydroShare.

Click on the hyperlink to ThunderCreek_DataIntegration_Beginner.ipynb. The beginner notebook is an Introduction for new HydroShare users who may have limited experience with Python code and Jupyter Notebooks. The advanced notebook explores how to combine watershed data with hydrology models (e.g. DHSVM) and the Landlab modeling framework (e.g. landsliding).

The problem: Researchers need a modeling workflow that is flexible for developing their own code, with easy access to distributed datasets, shared on a common platform for coupling multiple models, usable by science colleagues, with easy publication of data, code, and scientific studies.

The emerging solution: Collaborate with the CUAHSI HydroShare community to use and contribute to water data software and hardware tools, so that you can focus on your science, be efficient with your time and resources, and build on existing research in multiple domains of water science.

Beginner Notebook (time savings ~ 9 months)
Download water data from CUAHSI HIS
Develop your own utilites (e.g. download hydrometeorology)
Save your results on HydroShare for your colleagues

Advanced Notebook (time savings ~2.5 years)
Run a preconfigured hydrology model installed on the CUAHSI JupyterHub server
Run a published Landlab landslide model
Publish your results and get a DOI

This is a Watershed Dynamics Model developed by the Watershed Dynamics Research Group in the Civil and Environmental Engineering Department at the University of Washington for the Thunder Creek basin in the Skagit Watershed, WA, USA in collaboration with CUAHSI.

The resource was originally derived from a reproducible demonstration of the landslide modeling results from: Strauch, R., Istanbulluoglu, E., Nudurupati, S. S., Bandaragoda, C., Gasparini, N. M., and Tucker, G. E.: A hydro-climatological approach to predicting regional landslide probability using Landlab, Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2017-39, in review, 2017.

How are you using HydroShare?
https://docs.google.com/forms/d/e/1FAIpQLSeD4K9faWoHjy_ZwZhz3zHWxYH2vIhBFsvz5uhVbMvsXNuoeA/viewform

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Composite Resource Composite Resource
CZO Data Managers Workshop Resources
Created: Aug. 1, 2017, 5:09 a.m.
Authors: Anthony Castronova

ABSTRACT:

This resource contains the data for a workshop held on August 1st in Boulder Colorado

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Time Series Time Series
Water temperature data from the Little Bear River, UT
Created: Nov. 2, 2017, 10:19 p.m.
Authors: Anthony Castronova

ABSTRACT:

This dataset contains time series of observations of water temperature in the Little Bear River, UT. Data were recorded every 30 minutes. The values were recorded using a HydroLab MS5 multi-parameter water quality sonde connected to a Campbell Scientific datalogger.

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Time Series Time Series
Water temperature data from the Little Bear River, UT
Created: Nov. 3, 2017, 3:55 p.m.
Authors: Anthony Castronova

ABSTRACT:

This dataset contains time series of observations of water temperature in the Little Bear River, UT. Data were recorded every 30 minutes. The values were recorded using a HydroLab MS5 multi-parameter water quality sonde connected to a Campbell Scientific datalogger.

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Composite Resource Composite Resource

ABSTRACT:

The development and adoption of technologies by the water science community to improve our ability to openly collaborate and share workflows will have a transformative impact on how we address the challenges associated with collaborative and reproducible scientific research. Jupyter notebooks offer one solution by providing an open-source platform for creating metadata-rich toolchains for modeling and data analysis applications. Adoption of this technology within the water sciences, coupled with publicly available datasets from agencies such as USGS, NASA, and EPA enables researchers to easily prototype and execute data intensive toolchains. Moreover, implementing this software stack in a cloud-based environment extends its native functionality to provide researchers a mechanism to build and execute toolchains that are too large or computationally demanding for typical desktop computers. Additionally, this cloud-based solution enables scientists to disseminate data processing routines alongside journal publications in an effort to support reproducibility. For example, these data collection and analysis toolchains can be shared, archived, and published using the HydroShare platform or downloaded and executed locally to reproduce scientific analysis. This work presents the design and implementation of a cloud-based Jupyter environment and its application for collecting, aggregating, and munging various datasets in a transparent, sharable, and self-documented manner. The goals of this work are to establish a free and open source platform for domain scientists to (1) conduct data intensive and computationally intensive collaborative research, (2) utilize high performance libraries, models, and routines within a pre-configured cloud environment, and (3) enable dissemination of research products. This presentation will discuss recent efforts towards achieving these goals, and describe the architectural design of the notebook server in an effort to support collaborative and reproducible science

This was presented as an EPoster at the 2017 American Geophysical Union and can be found at:
https://agu2017fallmeeting-agu.ipostersessions.com/default.aspx?s=2B-C4-70-3C-B8-A0-0D-77-35-04-7C-F2-A4-1B-36-10

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Composite Resource Composite Resource
Terrain Processing - TauDem Example
Created: Feb. 22, 2018, 5:43 p.m.
Authors: Anthony Castronova

ABSTRACT:

An example workflow for processing DEM terrain processing. The Jupyter notebook included within this resource uses the TauDEM software package for parallel terrain processing operations.

More information on TauDEM can be found at: http://hydrology.usu.edu/taudem/taudem5/

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Collection Resource Collection Resource
JupyterHub Example Notebooks
Created: Feb. 22, 2018, 5:58 p.m.
Authors: Anthony Castronova

ABSTRACT:

This is a collection of resources that demonstrate the CUAHSI JupyterHub platform. Each of these can be launched using the JupyterHub WebApp and executed in the cloud.

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Composite Resource Composite Resource
SUMMA TestCase Data - Celia 1990
Created: March 16, 2018, 6:55 p.m.
Authors: Anthony Castronova

ABSTRACT:

This is the input data for the Celia 1990 SUMMA testcase.

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Collection Resource Collection Resource

ABSTRACT:

Scientists are faced with many challenges throughout the research lifecycle ranging from data collection and management to collaboration and reproducible science. These challenges are exacerbated for large studies by increased scope and complexity that results from the interdisciplinary nature of water science. The next generation of water scientists must be comfortable using a variety of software, tools, and platforms on a daily basis to efficiently and effectively conduct their research. The Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI) aims to assist scientists in these efforts by investing in community-driven cyberinfrastructure research projects. This cyberseminar series presents efforts made by CUAHSI to alleviate the burden common of data-related tasks and is separated into three distinct seminars that collectively discuss the challenges associated with data management, collaboration, and reproducible science. Each seminar will focus on a specific scientific use cases and will demonstrate how free and open source software can be used to overcome data-related research challenges. Participants will learn about new technologies that can assist both academic and educational water science settings.

Dates, Speakers, and Topics:

April 13: Data Archiving and Dissemination Tools to Support Water Science Research | Liza Brazil, CUAHSI
April 20: Cloud-hosting Water Science Data for Collaborative Research | Mark Henderson, CUAHSI
April 27: Cyberinfrastructure to Support Water Science Education and Reproducible Science | Anthony Castronova, CUAHSI

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Composite Resource Composite Resource

ABSTRACT:

Fluency in software tools, libraries, and languages is becoming an essential skill of scientists that can directly influence the effectiveness and efficiency of their work. While graduate students often learn these skills while conducting research, these are difficult to teach undergraduate students. This seminar will discuss CUAHSI’s investment in cyberinfrastructure to support water science research, training, and education. Topics will range from designing educational modules and hosting workshops to hydrologic modeling and data analysis. Participants can expect a primer on JupyterHub and the cyberinfrastructure that has been designed to support these workflows, as well as detailed demonstrations of common educational and research use cases. Participants are expected to have a basic understanding of HydroShare.org and the Python programming language, and are encouraged to participate in the live demonstrations.

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Generic Generic

ABSTRACT:

The CUAHSI-SCOPE team conducted user-based research to evaluate and design an improved user experience for HydroShare. The user-oriented project focused on identifying key users and workflows, defining current limitations of the system, and developing a comprehensive document of design recommendations.

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Composite Resource Composite Resource
Hurricane Harvey Streamflow Preview Notebook
Created: May 11, 2018, 3:28 p.m.
Authors: Anthony Castronova

ABSTRACT:

This is a Jupyter notebook that demonstrates how to preview Hurricane Harvey Streamflow data that is stored in an Observations Data Model v.2 SQLite file. It's meant to be executed on the https://jupyter.cuahsi.org notebook server and relies on several pre-installed packages, e.g. utilities.timeseries and utilities.hydroshare. This notebook will need to be modified for it to be executed elsewhere.

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Generic Generic

ABSTRACT:

Hydrologic Terrain Analysis Jupyter Notebook used to demonstrate the use of the Jupyter Notebook App for watershed delineation.

To use the Jupyter Notebook click on the "Open With" blue bottom at the top right of this page and choose "Jupyter". Then run the first few cells on the Welcome page. These cells establish a secure connection to the HydroShare and get the main notebook and the inputs to run the example. When the main code and the inputs are retrieved, you can click on "TauDEM.ipynb" to see the code and run it. The Jupyter Notebook also has steps to save all the inputs, outputs, and the main code into a new resource.

Presentation at EarthCube all hands meeting, June 6-8, 2018, Washington, DC https://www.earthcube.org/ECAHM2018

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Geographic Feature (ESRI Shapefiles) Geographic Feature (ESRI Shapefiles)
HUC 120200
Created: June 13, 2018, 1:43 p.m.
Authors: Anthony Castronova

ABSTRACT:

This is a HUC boundary that Hurricane Harvey hit.

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Composite Resource Composite Resource
Hurricane Harvey NWM Subsetting Exercise
Created: June 13, 2018, 2:54 p.m.
Authors: Anthony Castronova

ABSTRACT:

This is a Jupyter notebook that demonstrates how NWM forecasts for Hurricane Harvey can be subsetted using the CUAHSI-JupyterHub architecture.

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Composite Resource Composite Resource

ABSTRACT:

Continued investment and development of cyberinfrastructure (CI) for water science research is transforming the way future scientists approach large collaborative studies. Among the many challenges, that we as a community need to address, are integrating existing CI to support reproducible science, enabling open collaboration across traditional domain and institutional boundaries, and extending the lifecycle of data beyond the scope of a single project. One emerging solution for addressing these challenges is HydroShare JupyterHub which is an open-source, cloud-based, platform that combines the data archival and discovery features of HydroShare with the expressive, metadata-rich, and self-descriptive nature of Jupyter notebooks. This approach offers researchers a mechanism for designing, executing, and disseminating toolchains with supporting data and documentation. The goals of this work are to establish a free and open source platform for domain scientists to (1) conduct data intensive and computationally intensive collaborative research, (2) utilize high performance libraries, models, and routines within a pre-configured cloud environment, and (3) enable dissemination of research products. This presentation will discuss our approach for hydrologic model simulation, sensitivity analysis, and optimization applications in this platform by establishing a generic CI pattern that can be adopted to support research, classroom, and workshop activities

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