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Water 2015, 7(12), 6810-6826; doi:10.3390/w7126662

On Approaches to Analyze the Sensitivity of Simulated Hydrologic Fluxes to Model Parameters in the Community Land Model

1
Experimental and Computational Engineering Group, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
2
Hydrology Group, Pacific Northwest National Laboratory, Richland, WA 99352, USA
3
Earth System Analysis and Modeling Group, Pacific Northwest National Laboratory, Richland, WA 99352, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Paolo Reggiani and Ezio Todini
Received: 9 September 2015 / Revised: 24 November 2015 / Accepted: 27 November 2015 / Published: 4 December 2015
(This article belongs to the Special Issue Uncertainty Analysis and Modeling in Hydrological Forecasting)
View Full-Text   |   Download PDF [4322 KB, uploaded 4 December 2015]   |  

Abstract

Effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including 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. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization. View Full-Text
Keywords: sensitivity analysis; model selection; hydrologic parameters; Community Land Model sensitivity analysis; model selection; hydrologic parameters; Community Land Model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Bao, J.; Hou, Z.; Huang, M.; Liu, Y. On Approaches to Analyze the Sensitivity of Simulated Hydrologic Fluxes to Model Parameters in the Community Land Model. Water 2015, 7, 6810-6826.

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