Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona
abstract: The National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) will provide the next generation of operational streamflow forecasts at different lead times across United States using the Weather Research and Forecasting (WRF)-Hydro hydrologic system. These forecast...
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ndltd-asu.edu-item-573102020-06-02T03:01:27Z Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona abstract: The National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) will provide the next generation of operational streamflow forecasts at different lead times across United States using the Weather Research and Forecasting (WRF)-Hydro hydrologic system. These forecasts are crucial for flood protection agencies and water utilities, including the Salt River Project (SRP). The main goal of this study is to calibrate WRF-Hydro in the Oak Creek Basin (OCB; ~820 km2), an unregulated mountain sub-watershed of the Salt and Verde River basins in Central Arizona, whose water resources are managed by SRP and crucial for the Phoenix Metropolitan area. As in the NWM, WRF-Hydro was set up at 1-km (250-m) resolution for the computation of the rainfall-runoff (routing) processes. Model forcings were obtained by bias correcting meteorological data from the North American Land Data Assimilation System-2 (NLDAS-2). A manual calibration approach was designed that targets, in sequence, the sets of model parameters controlling four main processes responsible for streamflow and flood generation in the OCB. After a first calibration effort, it was found that WRF-Hydro is able to simulate runoff generated after snowmelt and baseflow, as well as magnitude and timing of flood peaks due to winter storms. However, the model underestimates the magnitude of flood peaks caused by summer thunderstorms, likely because these storms are not captured by NLDAS-2. To circumvent this, a seasonal modification of soil parameters was adopted. When doing so, acceptable model performances were obtained during calibration (2008-2011) and validation (2012-2017) periods (NSE > 0.62 and RMSE = ~2.5 m3/s at the daily time scale). The process-based calibration strategy utilized in this work provides a new approach to identify areas of structural improvement for WRF-Hydro and the NWM. Dissertation/Thesis Hussein, Abdinur Jirow (Author) Mascaro, Giuseppe (Advisor) Vivoni, Enrique (Advisor) Xu, Tianfang (Committee member) Arizona State University (Publisher) Civil engineering Flood forecasting Flood management Hydrological model NLDAS-2 forcing Water resources management WRF-Hydro model eng 110 pages Masters Thesis Civil, Environmental and Sustainable Engineering 2020 Masters Thesis http://hdl.handle.net/2286/R.I.57310 http://rightsstatements.org/vocab/InC/1.0/ 2020 |
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language |
English |
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Dissertation |
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Civil engineering Flood forecasting Flood management Hydrological model NLDAS-2 forcing Water resources management WRF-Hydro model |
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Civil engineering Flood forecasting Flood management Hydrological model NLDAS-2 forcing Water resources management WRF-Hydro model Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona |
description |
abstract: The National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) will provide the next generation of operational streamflow forecasts at different lead times across United States using the Weather Research and Forecasting (WRF)-Hydro hydrologic system. These forecasts are crucial for flood protection agencies and water utilities, including the Salt River Project (SRP). The main goal of this study is to calibrate WRF-Hydro in the Oak Creek Basin (OCB; ~820 km2), an unregulated mountain sub-watershed of the Salt and Verde River basins in Central Arizona, whose water resources are managed by SRP and crucial for the Phoenix Metropolitan area. As in the NWM, WRF-Hydro was set up at 1-km (250-m) resolution for the computation of the rainfall-runoff (routing) processes. Model forcings were obtained by bias correcting meteorological data from the North American Land Data Assimilation System-2 (NLDAS-2). A manual calibration approach was designed that targets, in sequence, the sets of model parameters controlling four main processes responsible for streamflow and flood generation in the OCB. After a first calibration effort, it was found that WRF-Hydro is able to simulate runoff generated after snowmelt and baseflow, as well as magnitude and timing of flood peaks due to winter storms. However, the model underestimates the magnitude of flood peaks caused by summer thunderstorms, likely because these storms are not captured by NLDAS-2. To circumvent this, a seasonal modification of soil parameters was adopted. When doing so, acceptable model performances were obtained during calibration (2008-2011) and validation (2012-2017) periods (NSE > 0.62 and RMSE = ~2.5 m3/s at the daily time scale).
The process-based calibration strategy utilized in this work provides a new approach to identify areas of structural improvement for WRF-Hydro and the NWM. === Dissertation/Thesis === Masters Thesis Civil, Environmental and Sustainable Engineering 2020 |
author2 |
Hussein, Abdinur Jirow (Author) |
author_facet |
Hussein, Abdinur Jirow (Author) |
title |
Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona |
title_short |
Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona |
title_full |
Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona |
title_fullStr |
Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona |
title_full_unstemmed |
Process-Based Calibration of WRF-Hydro Model in Unregulated Mountainous Basin in Central Arizona |
title_sort |
process-based calibration of wrf-hydro model in unregulated mountainous basin in central arizona |
publishDate |
2020 |
url |
http://hdl.handle.net/2286/R.I.57310 |
_version_ |
1719315829696233472 |