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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
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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
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This resource was created using funding from the following sources:
Cataloguing and Generating Hydrology Scenarios in the Colorado River Basin
R21AC10342
How to Cite
Salehabadi, H., D. Tarboton (2024). R Scripts for Evaluating Annual Streamflow Ensemble Metrics and Data and Results from their Application in the Colorado River Basin, HydroShare, https://doi.org/10.4211/hs.d7b65c91dda047e1969a9f9cd09b489f
This resource is shared under the Creative Commons Attribution CC BY.
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