A Reduced Parameter Stream Temperature Model (RPSTM) for basin-wide simulations |
| |
| Affiliation: | 1. CoDA Laboratory, Dept. of CSE, IIT Roorkee, India;2. Dept. of CSE, IIT Kharagpur, India;3. Dept. of CS, National Tsing Hua University, Hsinchu, Taiwan;4. Advanced Computing and Microelectronics Unit, Indian Statistical Institute, Kolkata, India;1. Hydrological Forecasting Office, Institute of Meteorology and Water Management – National Research Institute, ul. Piotra Borowego 14, Cracow 30-215, Poland;2. Department of Environmental Protection and Development, Faculty of Environmental Engineering, Warsaw University of Technology, ul. Nowowiejska 20, Warsaw 00-653, Poland;3. Department of Bioresource Engineering, McGill University, 21 111 Lakeshore Road, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada;1. Department of Physics, University of Fribourg, 1700 Fribourg, Switzerland;2. Institute of Fundamental and Frontier Sciences, UESTC, Chengdu 610054, China;2. School of Business Administration, China University of Petroleum – Beijing, 18 Fuxue Road, Changping, Beijing, China;1. MOE Key Laboratory of Hydrodynamics, Shanghai Jiao Tong University, Shanghai 200240, China;2. Key Laboratory of Estuarine and Coastal Engineering, Ministry of Transport, Shanghai 201201, China;3. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;4. Department of Ecohydrology, Institute of Fresh-water Ecology and Inland Fisheries, Berlin 12587, Germany;5. MOE Key Laboratory of Hydrodynamics, Shanghai Jiaotong University, Shanghai 200240, China;6. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China |
| |
| Abstract: | Water temperature is a crucial variable that shapes biological communities and controls rates of ecosystem processes in rivers. Fully parameterized heat balance models have been used to provide accurate estimates, but high parameterization costs make them difficult to apply at basin-wide scales. As parts of a collaborative modeling project to address future impacts of climate and land-use management on the Muskegon River, we developed a Reduced Parameter Stream Temperature Model (RPSTM), a mechanistic, spatially explicit but easier to parameterize model. Here we describe and test RPSTM's applicability by conducting a series of daily water temperature simulations (1985–2005). RPSTM performed well along the river network. The predictions were most sensitive to air temperature, depth, and solar radiation, but relatively insensitive to rates of surface runoff. This modeling approach is easily integrated into complex multi-modeling systems to evaluate effects of long-term changes in watershed hydrology, climate, and land management across river networks. |
| |
| Keywords: | Stream/water temperature modeling Integrated modeling Energy/heat balance Climate change Hydrology Muskegon river |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
