HR: 1340h
AN: H43A-0484    [Abstracts]
TI: Understanding Parameter Sensitivity in Complex Watershed-Scale Water Quality Models Using Generalized Sensitivity Analysis
AU: * Zheng, Y
EM: yzheng@bren.ucsb.edu
AF: Donald Bren School of Environmental Science and Management, University of California, Santa Barbara, Bren Hall, University of California, Santa Barbara, Santa Barbara, CA 93106 United States
AU: Keller, A A
EM: keller@bren.ucsb.edu
AF: Donald Bren School of Environmental Science and Management, University of California, Santa Barbara, Bren Hall, University of California, Santa Barbara, Santa Barbara, CA 93106 United States
AB: Water quality simulation using watershed-scale water quality models involves significant parameter uncertainty. Given the complexity of the models, a preliminary sensitivity analysis (SA) before a full-blown uncertainty analysis is necessary, but challenging. Although a few sensitivity studies have been conducted for watershed models, selecting which parameters should be included in the uncertainty analysis is an issue. Generalized Sensitivity Analysis (GSA) is a Monte Carlo based approach with some useful additional features. Its applicability to watershed-scale models is examined in this study, using the WARMF model as an example. Specifically, the study aims to determine (1) whether GSA can be applied at an affordable computation cost for watershed model analysis; (2) whether GSA can discriminate between sensitive and non-sensitive parameters; and (3) to what extent the results of the SA are conditioned on the management questions addressed by the overall analysis. A synthetic-catchment approach is developed to investigate these problems. The analysis shows that GSA can be applied in a practical manner to small watershed models, which yields insights into model and parameter behavior. Some case-specific conclusions on experimental conditions (i.e. number of runs, protection level) for GSA are achieved. Strong dependency of sensitivity on management interests are revealed as well. Overall, the study provides intuitive guiding information for future use of GSA for watershed problems.
DE: 1847 Modeling
DE: 1871 Surface water quality
DE: 1873 Uncertainty assessment (3275)
DE: 1879 Watershed
SC: Hydrology [H]
MN: Fall Meeting 2005