Using MODAWEC to generate daily weather data for the EPIC model |
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| Authors: | Junguo Liu Jimmy R. Williams Xiuying Wang Hong Yang |
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| Affiliation: | 1. State Key Laboratory of Geodesy and Earth''s Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China;2. Institute of Earth Sciences, Academia Sinica, Taipei, Taiwan;3. Center for Space Research, University of Texas at Austin, Austin, USA;4. Department of Geological Sciences, Jackson School of Geosciences, University of Texas at Austin, Austin, USA;1. State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China;2. Center for Agricultural Resources Research, Chinese Academy of Sciences, Shijiazhuang 050021, China;3. Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78758, United States;4. Department of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73072, United States;5. Geosciences Rennes, UMR CNRS 6118, Université de Rennes 1, Rennes, France;6. National Centre for Groundwater Research and Training, Adelaide, South Australia 5001, Australia;7. School of the Environment, Flinders University, Adelaide, South Australia 5001, Australia;8. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;9. College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China |
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| Abstract: | Although the EPIC model has been widely used in agricultural and environmental studies, applications of this model may be limited in the regions where daily weather data are not available. In this paper, a stand-alone MODAWEC model was developed to generate daily precipitation and maximum and minimum temperature from monthly precipitation, maximum and minimum temperature, and wet days. A case study shows that the crop yields and evapotranspiration (ET) simulated with the generated daily weather data compare very well with those simulated with the measured daily weather data with low normalized mean square errors (0.008–0.017 for crop yields and 0.003–0.004 for ET). The MODAWEC model can extend the application of the EPIC model to the regions where daily data are not available or not complete. In addition, the generated daily weather data can possibly be used by other environmental models. Associated with MODAWEC, the EPIC model can play a greater role in assessing the impacts of global climate change on future food production and water use. |
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