Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 11 2 2007 10.5194/hess-11-793-2007 http://www.hydrol-earth-syst-sci.net/11/793/2007/ http://www.hydrol-earth-syst-sci.net/11/793/2007/hess-11-793-2007.html http://www.hydrol-earth-syst-sci.net/11/793/2007/hess-11-793-2007.pdf 793 817 2007-02-05 Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation Y. Tang P. Reed preed@engr.psu.edu T. Wagener K. van Werkhoven Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA This study seeks to identify sensitivity tools that will advance our understanding of lumped hydrologic models for the purposes of model improvement, calibration efficiency and improved measurement schemes. Four sensitivity analysis methods were tested: (1) local analysis using parameter estimation software (PEST), (2) regional sensitivity analysis (RSA), (3) analysis of variance (ANOVA), and (4) Sobol's method. The methods' relative efficiencies and effectiveness have been analyzed and compared. These four sensitivity methods were applied to the lumped Sacramento soil moisture accounting model (SAC-SMA) coupled with SNOW-17. Results from this study characterize model sensitivities for two medium sized watersheds within the Juniata River Basin in Pennsylvania, USA. Comparative results for the 4 sensitivity methods are presented for a 3-year time series with 1 h, 6 h, and 24 h time intervals. The results of this study show that model parameter sensitivities are heavily impacted by the choice of analysis method as well as the model time interval. Differences between the two adjacent watersheds also suggest strong influences of local physical characteristics on the sensitivity methods' results. This study also contributes a comprehensive assessment of the repeatability, robustness, efficiency, and ease-of-implementation of the four sensitivity methods. Overall ANOVA and Sobol's method were shown to be superior to RSA and PEST. Relative to one another, ANOVA has reduced computational requirements and Sobol's method yielded more robust sensitivity rankings. Abbaspour, K C., Schulin, R., and van Genuchten M Th.: Estimating unsaturated soil hydraulic parameters using ant colony optimization, Adv. Water Resour., 24, 827–841, 2001. Anderson, E A.: National Weather Service River Forecast System - Snow Accumulation and Ablation Model, Tech. rep., NOAA Technical Memorandum NWS Hydro-17, Dept. of Commerce, Silver Spring, Maryland, USA, 1973. 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