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R Scripts for Evaluating Annual Streamflow Ensemble Metrics and Data and Results from their Application in the Colorado River Basin
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| Type: | Resource | |
| Storage: | The size of this resource is 61.6 MB | |
| Created: | Dec 07, 2023 at 9:27 p.m. | |
| Last updated: | Jul 03, 2024 at 8:53 p.m. (Metadata update) | |
| Published date: | Jul 03, 2024 at 8:53 p.m. | |
| DOI: | 10.4211/hs.d7b65c91dda047e1969a9f9cd09b489f | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 503 |
| Downloads: | 55 |
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Abstract
This resource contains the R Scripts developed to characterize and assess annual streamflow ensembles using an extensive set of statistical metrics. We have assembled a broad set of metrics and applied them to annual streamflow in the Colorado River at Lees Ferry to illustrate the approach. We have also developed a tree-based classification approach to categorize both ensembles and metrics. The results, also included here, provide a way to visualize and interpret differences between streamflow ensembles. The presented metrics and their classification provide an analytical framework for characterizing and assessing the suitability of future streamflow ensembles, recognizing the presence of non-stationarity, and contributing to better planning in river basins.
This resource contains the data and scripts used in
Salehabadi, H., Tarboton, D. G., Wheeler, K. G., Smith, R., & Baker, S. (2024). Quantifying and Classifying Streamflow Ensembles Using a Broad Range of Metrics for an Evidence-Based Analysis: Colorado River Case Study. Water resources research, 60, e2024WR037225. https://doi.org/10.1029/2024WR037225
Subject Keywords
Coverage
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Content
README.txt
R Scripts for Evaluating Annual Streamflow Ensemble Metrics and data and results from their application in the Colorado River Basin Organization of this Resource Ensemble Comparison folder (EnsembleComparison). - MasterScript_EnsembleComparison.R. R script that computes cross ensemble comparison metrics. - HydrologyScenarios.xlsx. Input file for the R script. Tabs in this file hold the data for each ensemble. There is a Readme tab describing the content and a tab where users can control the ensembles and metrics that are to be computed by the R script. - R_Files. Folder with R functions for evaluating the metrics. These are called by the master script. - Results. Folder where a PDF file with results is output. Ensemble Specific Metrics folder (EnsembleSpecificMetrics). - MasterScript_EnsembleSpecificMetrics.R. R script that computes ensemble specific metrics. - HydrologyScenarios.xlsx. Input file for the R script. Tabs in this file hold the data for each ensemble. There is a Readme tab describing the content and a tab where users can control the ensembles and metrics that are to be computed by the R script. - R_Files. Folder with R functions for evaluating the metrics. These are called by the master script. - Results. Folder were multiple PDF files, one file for each ensemble, are output. To reproduce these results you need R software available from https://www.R-project.org/. R Core Team (2023). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ The master scripts above are programmed to download and install the needed R packages and should be run using R. R Studio https://posit.co/download/rstudio-desktop/ provides a convenient environment for running R. Results here were obtained using R version 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts" running in R Studio version 2023.06.0+421 "Mountain Hydrangea" Release (583b465ecc45e60ee9de085148cd2f9741cc5214, 2023-06-05) for windows. R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License. RStudio is available from Posit Software under the terms of version 3 of the GNU Affero General Public License.
Related Resources
| This resource is described by | Salehabadi, H., Tarboton, D. G., Wheeler, K. G., Smith, R., & Baker, S. (2024). Quantifying and Classifying Streamflow Ensembles Using a Broad Range of Metrics for an Evidence-Based Analysis: Colorado River Case Study. Water resources research, 60, e2024WR037225. https://doi.org/10.1029/2024WR037225 |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
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| Bureau of Reclamation | Cataloguing and Generating Hydrology Scenarios in the Colorado River Basin | R21AC10342 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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