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Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow Over Texas Using the Wrf-Hydro-Rapid Modeling Framework1

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Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow Over Texas Using the Wrf-Hydro-Rapid Modeling Framework1 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION Vol. 54, No. 1 AMERICAN WATER RESOURCES ASSOCIATION February 2018 SPATIOTEMPORAL EVALUATION OF SIMULATED EVAPOTRANSPIRATION AND STREAMFLOW OVER TEXAS USING THE WRF-HYDRO-RAPID MODELING FRAMEWORK1 Peirong Lin, Mohammad Adnan Rajib , Zong-Liang Yang, Marcelo Somos-Valenzuela , Venkatesh Merwade, David R. Maidment, Yan Wang, and Li Chen2 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 fil- ter 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 impor- tant preliminary steps towards accurate large-scale hydrologic forecasts. (KEY TERMS: evapotranspiration; streamflow; surface runoff; base flow; MODIS; WRF-Hydro; Noah-MP; RAPID.) Lin, Peirong, Mohammad Adnan Rajib, Zong-Liang Yang, Marcelo Somos-Valenzuela, Venkatesh Merwade, David R. Maidment, Yan Wang, and Li Chen, 2018. Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF-Hydro-RAPID Modeling Framework. Journal of the American Water Resources Association (JAWRA) 54(1): 40-54. https://doi.org/10.1111/1752-1688.12585 INTRODUCTION in transformation of hydrologic forecasting approaches from statistical and stochastic methods based on recorded observations (McEnery et al., The ability and accuracy of weather prediction 2005) to deterministic and probabilistic forecasts have greatly improved over the past decade, resulting based on numerical weather prediction (NWP) tools 1Paper No. JAWRA-16-0033-P of the Journal of the American Water Resources Association (JAWRA). Received January 27, 2016; accepted August 9, 2017. © 2017 American Water Resources Association. Discussions are open until six months from issue publication. 2Graduate Research Assistant (Lin) and Professor (Yang), Jackson School of Geosciences, University of Texas at Austin, 2225 Speedway, Stop C1160, Austin, Texas 78712; Graduate Research Assistant (Rajib) and Associate Professor (Merwade), Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana 47907; Professor (Yang), Key Laboratory of Regional Climate-Environment Research for Temper- ate East Asia of Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Associate Professor (Somos-Valen- zuela), Department of Agricultural and Forestry Sciences, University of La Frontera, Temuco 4780000, Chile; Professor (Maidment), Center for Research in Water Resources, University of Texas at Austin, Austin, Texas 78712; and Graduate Student (Wang) and Assistant Professor (Chen), College of Hydrology and Water Resources, Hohai University, Nanjing 210000, China (E-Mail/Yang: [email protected]). JAWRA 40 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION SPATIOTEMPORAL EVALUATION OF SIMULATED EVAPOTRANSPIRATION AND STREAMFLOW OVER TEXAS USING THE WRF-HYDRO-RAPID MODELING FRAMEWORK (Cloke and Pappenberger, 2009). Numerous studies hydrologic simulations. While global- and continen- have highlighted recent efforts in developing such tal-scale evaluations of Noah-MP have been docu- forecasting systems for Europe (Thielen et al., 2009), mented (e.g., Yang et al., 2011; Cai et al., 2014a), Africa (Thiemig et al., 2010), South America (Paiva these studies implemented the model at a resolution et al., 2011), and the entire globe (Pappenberger usually coarser than 0.125° and used limited gauge et al., 2012; Alfieri et al., 2013; Winsemius et al., locations at major rivers and basin outlets as a refer- 2013). ence for model evaluation. David et al. (2013) evalu- Likewise, a continental-scale high-resolution ated RAPID’s performance using runoff outputs from hydrologic forecasting system for the United States multiple LSMs, with a focus on the routing parame- (U.S.) has been developed recently (Maidment, 2016), ter optimization, but they did not establish linkages which literally transforms a real-time weather map between streamflow prediction errors with biases in to a river forecast map, using an earth system model- LSM-simulated water fluxes. Therefore, it is impor- ing framework. This hydrologic forecasting system tant to assess the model performance at finer spa- uses the community WRF-Hydro model (Gochis et al., tiotemporal scales than previous studies and 2015), an architectural framework which leverages establish the relationships between the errors in the the U.S. operational weather forecasting, the state-of- modeled streamflow and the biases in runoff compo- the-art land surface models (LSMs), and the geo- nents. referenced vector river network — the National This study uses WRF-Hydro-RAPID over Texas in Hydrography Dataset Plus (NHDPlus), providing the offline mode such that Noah-MP is run in a streamflow forecasts at 2.67 million river reaches stand-alone mode (i.e., uncoupled to WRF) to simu- operationally across the contiguous U.S. Comparing late land surface hydrology (Gochis et al., 2015). Due to previous gauge-based forecasting points at ~4,000 to emerging interests in using satellite-based evapo- nationally (McEnery et al., 2005), this new forecast- transpiration (ET) data to calibrate hydrologic mod- ing system represents a factor of 741 increase in spa- els (e.g., Kunnath-Poovakka et al., 2016), this study tial coverage, signaling a substantial shift from also evaluates the modeled ET against the Moderate watershed hydrology to continental hydrology. Resolution Imaging Spectroradiometer (MODIS) ET The National Flood Interoperability Experiment to understand the potential usefulness of the remo- (NFIE), a research collaboration among academia, tely sensed ET product in improving streamflow pre- federal agencies, and private partners, was proposed dictions. to translate the unprecedented information on river While the current operational U.S. National Water flow forecasts to inundation maps, which will eventu- Model (NWM) has evolved from the NFIE initiative, ally inform local emergency response planning (Maid- it has several advanced features compared to the ment, 2016). Since the onset of NFIE, continuous model configurations presented in this study. Specifi- efforts have been made in a wide range of aspects, cally, NWM has a streamflow data assimilation capa- including the development of baseline geospatial bility, a more physically based hydrologic routing hydrologic data for the continental flood forecasting scheme, a feature allowing simple level-pool routing system (Viger et al., 2016), the river hydraulics and for over 1,200 major reservoirs, and tools for model inundation mapping capability at high resolution calibrations (http://water.noaa.gov/about/nwm). (Follum et al., 2016), and the development of web The aim of this study is not to obtain the best- platforms for warning delivery to emergency respon- achievable prediction skills as required in an opera- ders and the general public (Swain, 2015). While tional setting. Instead, it is to establish a better these efforts are related mostly to the communication understanding of the model behaviors across a cli- and the translation of hydrologic simulations, their mate gradient with a focus on the interplay between potential strengths and weaknesses in terms of water biases in ET and individual runoff components. Based balances have not been well evaluated. Such evalua- upon the default Noah-MP configurations, the results tion is essential for ensuring the robustness of the presented here should be viewed as a reference for hydrologic modeling framework across the intended the baseline model performance, with a hope to bene- spatiotemporal scales. fit future model users who work on specific water- As the demonstration version of the continental- sheds in Texas and similar regions and to guide scale river modeling system, the WRF-Hydro-RAPID future model improvement activities. framework was used at the 2015 NFIE Summer The model and data used in this study are first Institute (Maidment, 2016). Within this framework, described, followed by the methodology. Next, results the refined Noah LSM with multi-parameterization and discussions on assessing the modeled ET, daily options (hereafter Noah-MP) (Niu et al., 2011) and streamflow, and the individual runoff components are the Routing Application for Parallel computatIon of presented. The last section summarizes the major Discharge (RAPID) (David et al., 2011) were
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