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A comprehensive approach to evaluating watershed models for predicting river flow regimes critical to downstream ecosystem services |
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| Affiliation: | 1. Food, Agricultural and Biological Engineering Department, The Ohio State University, Columbus, OH 43210, USA;2. Department of Earth, Environmental, and Planetary Sciences, Case Western Reserve University, Cleveland, OH 44106, USA;3. Environmental Science, Grace College, Winona Lake, IN 46590, USA;4. National Center for Water Quality Research, Heidelberg University, Tiffin, OH 44883, USA;5. Aquatic Ecology Laboratory, Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43212, USA;1. Federal Institute of Hydrology, Am Mainzer Tor 1, 56068 Koblenz, Germany;2. Brandenburgische Technische Universität Cottbus, Seestr. 45, 15526 Bad Saarow, Germany;1. Department of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing, Jiangsu 210093, PR China;2. Key Laboratory of Surficial Geochemistry, Ministry of Education, Nanjing, Jiangsu 210093, PR China;1. Applied Hydrometeorological Research Institute, Nanjing University of Information Science & Technology (NUIST), Nanjing, China;2. Key Laboratory of Meteorological Disaster of Ministry of Education, NUIST, Nanjing, China;3. Department of Marine, Earth and Atmospheric Sciences, North Carolina State University, Raleigh, USA;4. International Institute for Earth System Science (ESSI), Nanjing University, Nanjing, China;1. Institute of Geography, Fujian Normal University, Fuzhou 350007, China;2. College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China;3. State Key Laboratory of Humid Subtropical Mountain Ecology (Funded by Ministry of Science and Technology and Fujian Province), Fuzhou 350007, China;4. Dorset Environmental Science Centre, Ontario Ministry of Environment and Climate Change, 1026 Bellwood Acres Road, Dorset, Ontario P0A 1E0, Canada;1. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography & Limnology, Chinese Academy of Sciences, Nanjing 210008, PR China;2. School of Geographical Sciences, Southwest University, Chongqing 400715, PR China;3. Key Laboratory of Eco-environments in Three Gorges Reservoir Region (Ministry of Education), Chongqing 400715, PR China |
| Abstract: | Selection of strategies that help reduce riverine inputs requires numerical models that accurately quantify hydrologic processes. While numerous models exist, information on how to evaluate and select the most robust models is limited. Toward this end, we developed a comprehensive approach that helps evaluate watershed models in their ability to simulate flow regimes critical to downstream ecosystem services. We demonstrated the method using the Soil and Water Assessment Tool (SWAT), the Hydrological Simulation Program–FORTRAN (HSPF) model, and Distributed Large Basin Runoff Model (DLBRM) applied to the Maumee River Basin (USA). The approach helped in identifying that each model simulated flows within acceptable ranges. However, each was limited in its ability to simulate flows triggered by extreme weather events, owing to algorithms not being optimized for such events and mismatched physiographic watershed conditions. Ultimately, we found HSPF to best predict river flow, whereas SWAT offered the most flexibility for evaluating agricultural management practices. |
| Keywords: | Watershed modeling Eutrophication Runoff Great Lakes Lake Erie Allochthonous inputs Non-point source pollution Algal bloom SWAT"} {"#name":"keyword" "$":{"id":"kwrd0055"} "$$":[{"#name":"text" "_":"Soil and Water Assessment Tool DLBRM"} {"#name":"keyword" "$":{"id":"kwrd0065"} "$$":[{"#name":"text" "_":"Distributed Large Basin Runoff Model HSPF"} {"#name":"keyword" "$":{"id":"kwrd0075"} "$$":[{"#name":"text" "_":"Hydrology Simulation Program–Fortran GOF"} {"#name":"keyword" "$":{"id":"kwrd0085"} "$$":[{"#name":"text" "_":"goodness-of-fit SCS"} {"#name":"keyword" "$":{"id":"kwrd0095"} "$$":[{"#name":"text" "_":"Soil Conservation Service HRU"} {"#name":"keyword" "$":{"id":"kwrd0105"} "$$":[{"#name":"text" "_":"hydraulic response unit STATSGO"} {"#name":"keyword" "$":{"id":"kwrd0115"} "$$":[{"#name":"text" "_":"state soil geographic USGS"} {"#name":"keyword" "$":{"id":"kwrd0125"} "$$":[{"#name":"text" "_":"U S Geological Survey BMP"} {"#name":"keyword" "$":{"id":"kwrd0135"} "$$":[{"#name":"text" "_":"best management practice |
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