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Marginal Utility of Conditional Sensitivity Analyses for Dynamic Models
Citation:
Purucker, Tom, T. Hong, AND C. Kuan. Marginal Utility of Conditional Sensitivity Analyses for Dynamic Models. 2015 ESA Annual Meeting, Baltimore, MD, August 09 - 14, 2015.
Impact/Purpose:
Poster for ESA conference.
Description:
Background/Question/MethodsDynamic ecological processes may be influenced by many factors. Simulation models thatmimic these processes often have complex implementations with many parameters. Sensitivityanalyses are subsequently used to identify critical parameters whose uncertainties can be further reduced or better described and prediction variability minimized. In this study, we compare the ability of partial derivative based local sensitivity analysis methods to a variance decomposition based global sensitivity analysis technique (Sobol ' method). We use an ecological exposure model that is used to estimate pesticide concentrations in runoff and vertical soil compartments. Daily simulations are performed that fully explore the input parameter space. Estimated concentrations are compared to data collected over the course of a growing season from an experimental site in Georgia and representative local and global sensitivity analyses are conducted and compared.Results/ConclusionsOur results demonstrate that parameter sensitivity is conditional for dynamic models and should be examined at appropriate spatial and temporal resolution with global methods to avoid omitting important parameters. Sensitivities can and do change when they are evaluatedtemporally, with depth, as well as taking other related conditions into account. This is a differentapproach than traditional sensitivity analysis, whose conclusions are drawn by essentially"averaging" across all conditions thus could result in omitting important parameters. Forinstance, to better predict pesticide's residual concentration at shallow depths (0-15cm), one should focus on pesticide application rates, pesticide decay rate on foliage and rain intensity that have more direct impact on predicted pesticide concentrations. While in deeper soil compartments (> 15cm), more attention should be paid to the partitioning coefficient-organic component, the decay rate in the soil and water, and the accuracy of the rainfall time series. Global approaches can yield a better understanding about the interplay betweensensitivity/uncertainty and model dynamics in non-monotonic, non-linear systems.
