Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model: Evidence from MOPEX Basins

• DOI: 10.1175/jhm-d-12-0138.1
• Publication Date: 2013-05-03T19:14:43Z
• Authors: Maoyi Huang; Zhangshuan Hou; L. Ruby Leung; Yinghai Ke; Ying Liu; Zhufeng Fang; Yu Sun
• Keywords: Identifiability; Hydrological modelling

Abstract In this study, the authors applied version 4 of Community Land Model (CLM4) integrated with an uncertainty quantification (UQ) framework to 20 selected watersheds from Parameter Estimation Experiment (MOPEX) spanning a wide range climate and site conditions investigate sensitivity runoff simulations major hydrologic parameters assess fidelity CLM4, as land component Earth System (CESM), in capturing realistic hydrological responses. They found that for simulations, most significant are those related subsurface parameterizations. Soil texture–related surface secondary significance. Moreover, soil play important roles parameter sensitivity. general, water-limited regime finer texture result stronger output variables, such its components, input CLM4. This study evaluated identifiability streamflow observations at MOPEX basins demonstrated feasibility inversion/calibration CLM4 improve simulations. The results suggest order calibrate parameters, model reduction is needed include only identifiable unknowns. With reduced set dimensionality, inverse problem less ill posed.