S&T Project 19178 Final Report: Can better representation of low-elevation snowpack improve operational forecasts?
This report describes the research efforts that brought together a range of new snow datasets for watershed applications, including watershed model validation, to assess different strategies for watershed modeling to shed insight on how model representations of watershed heterogeneity impact snow accumulation and melt, and runoff generation. The work created a new snow data processing and analysis tool called SHREAD and developed new capabilities for model implementation and discretization, including additional scripts and insights for configuring the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models. Eight configurations of SUMMA with varying levels of spatial complexity were generated and tested for the drainage basin of Buffalo Bill Reservoir, on the Shoshone River, Wyoming. These models were assessed with a priori parameters and after calibration. A key finding is that, before calibration, more complex models that recognize differences in radiation exposure in subelements of the model simulation perform markedly better than those that do not, whereas all models perform similarly after calibration. Given the influence of solar radiation on snowmelt in the Western United States, this finding may guide more judicious implementation of watershed models not only for forecasting (for which operational models recognize mainly elevation aspects of watersheds) but also climate impact analyses.
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| description | This report describes the research efforts that brought together a range of new snow datasets for watershed applications, including watershed model validation, to assess different strategies for watershed modeling to shed insight on how model representations of watershed heterogeneity impact snow accumulation and melt, and runoff generation. The work created a new snow data processing and analysis tool called SHREAD and developed new capabilities for model implementation and discretization, including additional scripts and insights for configuring the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models. Eight configurations of SUMMA with varying levels of spatial complexity were generated and tested for the drainage basin of Buffalo Bill Reservoir, on the Shoshone River, Wyoming. These models were assessed with a priori parameters and after calibration. A key finding is that, before calibration, more complex models that recognize differences in radiation exposure in subelements of the model simulation perform markedly better than those that do not, whereas all models perform similarly after calibration. Given the influence of solar radiation on snowmelt in the Western United States, this finding may guide more judicious implementation of watershed models not only for forecasting (for which operational models recognize mainly elevation aspects of watersheds) but also climate impact analyses. |
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| landingPage | https://data.usbr.gov/catalog/4665/item/11551 |
| modified | 2022-10-03T10:36:21Z |
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| title | S&T Project 19178 Final Report: Can better representation of low-elevation snowpack improve operational forecasts? |
