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SCREENING THE RELOCATION STRATEGIES OF WATER QUALITY MONITORING STATIONS BY COMPROMISE PROGRAMMING1
Authors:Shu‐Kuang Ning  Ni‐Bin Chang
Abstract:Water quality monitoring network designs historically have tended to use experience, intuition, and subjective judgment in siting monitoring stations only sporadically. Better design procedures for optimizing monitoring systems with respect to multiple criteria decision analysis had rarely been put into practice up front when the needs for intensive monitoring became critical. This paper describes a systematic relocation strategy that is organized to identify several significant planning objectives and consider a series of inherent constraints simultaneously. The planning objectives considered in this analysis are designed to enhance the detection possibility for lower compliance areas, reflect the emphasis for different attainable water uses at different locations, promote the potential detection for the lower degradation areas of pollutants, increase the protection degree of those areas with higher population density in the proximity of the river system, and strengthen the pre‐warning capability of water quality for water intakes. The constraint set contains the limitations of budget, the equity implication, and the detection sensitivity in the water environment. A case study in the Kao‐Ping River Basin, South Taiwan, demonstrates the application potential of this methodology based on a seamless integration between the optimization and the simulation models. It enables identification of the optimal locational pattern stepwise using the embedded screening and sequencing capacity in a compromise programming model. However, a well calibrated and verified water quality model is an indispensable tool in support of this multiobjective evaluation. Extra sampling procedures become necessary for the sites with sparse environmental information. Comparison of planning outcomes of compromise programming is made against previously achieved analyses by using weighted programming and fuzzy programming.
Keywords:rivers/streams  monitoring network  water quality  watershed management  compromise programming  multicriteria decision making
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