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Application of hydrological models with increasing complexity to subarctic catchments
Affiliation:1. International Water Management Institute, Colombo, Sri Lanka;2. School of Foreign Affairs, Georgetown University, Washington, DC, USA;3. Independent Scholar, Bloomington, Indiana;4. International Water Management Institute, Lalitpur, Nepal;1. Energy Geosciences Division, Lawrence Berkeley National Laboratory 1 Cyclotron Road, M.S. 74R-316C, Berkeley, CA 94704, USA;2. Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory 1 Cyclotron Road, M.S. 74R-316C, Berkeley, CA 94704, USA;1. Department of Physics, Cornell University, Ithaca, NY 14853, United States;2. School of Applied & Engineering Physics, Cornell University, Ithaca, NY 14853, United States;3. Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109, United States;4. Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, NY 14853, United States
Abstract:Many available complex models tend to demand far more input information than is afforded by subarctic remote regions, such as vast areas of North America and Eurasia. A suitable level of model complexity must be sought so that the model matches both the availability of data, but also the spatial and temporal scale at which the major hydrological processes occur. The present paper describes a method to seek a level of model complexity suitable for simulation of runoff for a particular environment at a particular scale, commensurate with the limited data availability in remote areas. Processes in a simple model are stepwise replaced by representations taken from a more complex model, to achieve a balance between data requirement and model complexity at different spatial and temporal scales. The results suggest that it is not always necessary to switch directly from a simple hydrological model to complex one, because at particular spatial and temporal scales, runoff may be sensitive to only a number of processes.
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