تقرير
Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System
| العنوان: | Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System |
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| المؤلفون: | Timothy M. Lahmers, Sujay V Kumar, Daniel Rosen, Aubrey Duggar, David J. Gochis, Joseph A Santanello, Chandana Gangodagamage, Rocky Dunlap |
| المصدر: | Water Resources Research. 58(3) |
| بيانات النشر: | United States: NASA Center for Aerospace Information (CASI), 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Earth Resources And Remote Sensing |
| الوصف: | he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications. |
| نوع الوثيقة: | Report |
| اللغة: | English |
| تدمد: | 1944-7973 0043-1397 |
| DOI: | 10.1029/2021WR029867 |
| URL الوصول: | https://ntrs.nasa.gov/citations/20220004182 |
| ملاحظات: | 281945.02.04.03.92 80NSSC20K1330 NNX17AE79A NNH15ZDA001N-MAP |
| رقم الأكسشن: | edsnas.20220004182 |
| قاعدة البيانات: | NASA Technical Reports |
Full Text Finder | تدمد: | 19447973 00431397 |
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| DOI: | 10.1029/2021WR029867 |