期刊
JOURNAL OF HYDROMETEOROLOGY
卷 14, 期 6, 页码 1754-1772出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/JHM-D-12-0138.1
关键词
Hydrology; Surface fluxes; Land surface model; Model evaluation; performance; Model output statistics
资金
- project Climate Science for a Sustainable Energy Future
- DOE Earth System Modeling Program
- U.S. DOE [DE-AC05-76RL01830]
In this study, the authors applied version 4 of the Community Land Model (CLM4) integrated with an uncertainty quantification (UQ) framework to 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning a wide range of climate and site conditions to investigate the sensitivity of runoff simulations to major hydrologic parameters and to assess the fidelity of CLM4, as the land component of the Community Earth System Model (CESM), in capturing realistic hydrological responses. They found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture-related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, water-limited hydrologic regime and finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study evaluated the parameter identifiability of hydrological parameters from streamflow observations at selected MOPEX basins and demonstrated the feasibility of parameter inversion/calibration for CLM4 to improve runoff simulations. The results suggest that in order to calibrate CLM4 hydrologic parameters, model reduction is needed to include only the identifiable parameters in the unknowns. With the reduced parameter set dimensionality, the inverse problem is less ill posed.
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