Stochastic Calibration of Riverine Water Quality Models
Abstract:Though commonly used, the suitability of deterministic calibration criteria for stochastic model calibration and uncertainty analysis is not, however, clear. The approach of this paper is to examine the suitability, relative benefits and substantial disadvantages of ‘deterministic-optimization’ approaches in stochastic contexts. We propose, and then demonstrate, three alternate calibration strategies suitable for modelling water quality under uncertainty. The findings suggest potential improvements be made to current calibration paradigms. Since many environmental systems, and almost all water quality models, are subject to substantial uncertainty (be it expressly acknowledged or otherwise), approaches such as those proposed hold substantial, widely applicable, benefits
Document Type: Research Article
Publication date: January 1, 2008
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