Sensitivity Analysis for an Infiltration-Runoff Model with Parameter Uncertainty
Publication: Journal of Hydrologic Engineering
Volume 15, Issue 9
Abstract
Evaluation of the uncertainty effect of input parameters on model outputs is presented. HYDROL-INF, an infiltration-runoff model for layered soils, is used for simulating infiltration and surface runoff. The predictive uncertainty related to the modeling is evaluated. Specifically, a three-step procedure is implemented for sensitivity analysis of the model. The first step involves application of the local sensitivity analysis to gain a qualitative ranking of the whole set of input parameters for different model outputs with a relatively low computational cost. In the second step, the first-order second moment (FOSM) method is used to obtain the most sensitive parameters to the output from the parameters identified by the local sensitivity analysis. Third, the robust and computationally efficient Fourier amplitude sensitivity test (FAST) is conducted to overcome the nonlinearity problem for estimating the uncertainty of the model. Furthermore, the proposed methodology is applied to a three-layer soil system with varying permeability under unsteady rainfall. The soil system consists of loamy sand, sandy loam, and clay loam. The model outputs considered herein include cumulative infiltration and runoff. Dissimilar lists of crucial parameters are identified by using the FOSM and FAST methods. It is found that the combination of different soil layers and rainfall conditions have significant influences on the variance contribution of individual parameters to the total variance of the model.
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Acknowledgments
The writers would like to thank M. Levent Kavvas and Miguel A. Mariño for their helpful suggestions. This research was funded by the National Natural Science Foundation of China (NSFC) (Grant No. NNSFC50739003) and the Fundamental Research Funds for the Central Universities.
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Published In
Journal of Hydrologic Engineering
Volume 15 • Issue 9 • September 2010
Pages: 671 - 679
Copyright
© 2010 ASCE.
History
Received: Feb 27, 2009
Accepted: Mar 2, 2010
Published online: Mar 16, 2010
Published in print: Sep 2010
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