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Title: Classification of hydrological parameter sensitivity and evaluation of parameter transferability across 431 US MOPEX basins

Effective uncertainty quantification approaches are needed to identify important parameters or factors that affect complex Earth system models that composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in Community Land Model (CLM) simulations of runoff and latent heat flux in a watershed are evaluated. Simple residual statistics, the Nash-Sutcliffe coefficient, and log mean square error are used as alternative measures of the deviations between the simulated and field observed values. The effects of the input parameters on the deviations are evaluated quantitatively using analysis of variance (ANOVA) based on the generalized linear model (GLM), and using generalized cross validation (GCV) based on the multivariate adaptive regression splines (MARS) model. These analyses 1) help identify how to adjust parameter values and therefore the calibration of the CLM parameters and to improve the model’s simulations, and 2) can approximately predict the model calibration performance. The convergence behavior of the sensitivity analysis with number of sampling points for both ANOVA and GCV is also examined relative to different combinations of input parameters and output response variables and their metrics.
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Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 0022-1694; KJ0401000
DOE Contract Number:
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Hydrology; Journal Volume: 536
Research Org:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Country of Publication:
United States
uncertainty quantification; sensitivity analysis; calibration; hydrologic parameters; community land model