Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF‐Hydro‐RAPID Modeling Framework |
| |
| Authors: | Peirong Lin Mohammad Adnan Rajib Zong‐Liang Yang Marcelo Somos‐Valenzuela Venkatesh Merwade David R Maidment Yan Wang Li Chen |
| |
| Affiliation: | 1. Jackson School of Geosciences, University of Texas at Austin, Austin, Texas;2. Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana;3. Key Laboratory of Regional Climate‐Environment Research for Temperate East Asia of Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;4. Department of Agricultural and Forestry Sciences, University of La Frontera, Temuco, Chile;5. Center for Research in Water Resources, University of Texas at Austin, Austin, Texas;6. College of Hydrology and Water Resources, Hohai University, Nanjing, China |
| |
| Abstract: | This study assesses a large‐scale hydrologic modeling framework (WRF‐Hydro‐RAPID) in terms of its high‐resolution simulation of evapotranspiration (ET) and streamflow over Texas (drainage area: 464,135 km2). The reference observations used include eight‐day ET data from MODIS and FLUXNET, and daily river discharge data from 271 U.S. Geological Survey gauges located across a climate gradient. A recursive digital filter is applied to decompose the river discharge into surface runoff and base flow for comparison with the model counterparts. While the routing component of the model is pre‐calibrated, the land component is uncalibrated. Results show the model performance for ET and runoff is aridity‐dependent. ET is better predicted in a wet year than in a dry year. Streamflow is better predicted in wet regions with the highest efficiency ~0.7. In comparison, streamflow is most poorly predicted in dry regions with a large positive bias. Modeled ET bias is more strongly correlated with the base flow bias than surface runoff bias. These results complement previous evaluations by incorporating more spatial details. They also help identify potential processes for future model improvements. Indeed, improving the dry region streamflow simulation would require synergistic enhancements of ET, soil moisture and groundwater parameterizations in the current model configuration. Our assessments are important preliminary steps towards accurate large‐scale hydrologic forecasts. |
| |
| Keywords: | evapotranspiration streamflow surface runoff base flow MODIS WRF‐Hydro Noah‐MP RAPID |
|
|
