Parameter uncertainty and interaction in complex environmental models

Parameter uncertainty and interaction in complex environmental models Recently developed models for the estimation of risks arising from the release of toxic chemicals from hazardous waste sites are inherently complex both structurally and parametrically. To better understand the impact of uncertainty and interaction in the high‐dimensional parameter spaces of these models, the set of procedures termed regional sensitivity analysis has been extended and applied to the groundwater pathway of the MMSOILS model. The extension consists of a tree‐structured density estimation technique which allows the characterization of complex interaction in that portion of the parameter space which gives rise to successful simulation. Results show that the parameter space can be partitioned into small, densely populated regions and relatively large, sparsely populated regions. From the high‐density regions one can identify the important or controlling parameters as well as the interaction between parameters in different local areas of the space. This new tool can provide guidance in the analysis and interpretation of site‐specific application of these complex models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Water Resources Research Wiley

Parameter uncertainty and interaction in complex environmental models

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Publisher
Wiley
Copyright
Copyright © 1994 by the American Geophysical Union.
ISSN
0043-1397
eISSN
1944-7973
DOI
10.1029/94WR01732
Publisher site
See Article on Publisher Site

Abstract

Recently developed models for the estimation of risks arising from the release of toxic chemicals from hazardous waste sites are inherently complex both structurally and parametrically. To better understand the impact of uncertainty and interaction in the high‐dimensional parameter spaces of these models, the set of procedures termed regional sensitivity analysis has been extended and applied to the groundwater pathway of the MMSOILS model. The extension consists of a tree‐structured density estimation technique which allows the characterization of complex interaction in that portion of the parameter space which gives rise to successful simulation. Results show that the parameter space can be partitioned into small, densely populated regions and relatively large, sparsely populated regions. From the high‐density regions one can identify the important or controlling parameters as well as the interaction between parameters in different local areas of the space. This new tool can provide guidance in the analysis and interpretation of site‐specific application of these complex models.

Journal

Water Resources ResearchWiley

Published: Nov 1, 1994

References

  • Water quality modeling: A review of the analysis of uncertainty
    Beck, Beck
  • A three‐dimensional analytical method for predicting leachate migration
    Huyakorn, Huyakorn; Ungs, Ungs; Mulkey, Mulkey; Sudicky, Sudicky
  • Data requirements for seasonal discharge programs: An application of a regionalized sensitivity analysis
    Lence, Lence; Takyi, Takyi

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