This paper presents an approach to calibrating a holistic water resources–economic model, which involves essential water resources and economic components in a consistent model. The model is formulated as an optimization model, with the objective of maximizing economic welfares/profits from water uses. When we apply the model to a baseline scenario against real-world conditions, the economic outputs are often expected to match the observations at the base level, since a wide divergence between model outcomes and actual results is not appropriate for analyzing policy options starting from the baseline. Following the concept of “positive mathematical programming,” the holistic water resources–economic model is calibrated to a baseline level using programming constraints and “positive” inferences from baseline observations. The calibration task is complicated by the fact that a large number of interdependent parameters should be calibrated simultaneously. A numerical approach based on hybrid genetic algorithms is used to implement the calibration procedure.
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Cai et al. (2006) studied this question.
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