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Urban water management is a demanding decision-making environment where optimal planning presupposes a synthesis of heterogeneous information of high spatial resolution to ensure site-specific implementation. To assist the decision maker in this task, the development of spatial decision support systems (SDSS) with a distinct spatial character is considered sine qua non. The paper describes the development of a prototype SDSS supporting strategic planning, providing examples from a particular application in water demand management (WDM). A three-stage approach is developed and utilized: After an initial user-defined choice of strategies to be explored, the system produces suitability maps for each individual attribute of the strategies in question using type-1 and type-2 fuzzy inference systems. The results are aggregated using ordered weighted averaging, allowing for the incorporation of the decision maker’s optimism in the final outcome. The last stage consists of an optimization procedure enabling the identification of an optimal composite strategy, from a water saving point of view, under user defined investment constraints. The results support the case of using SDSS based on approximate reasoning to complement engineering expertise for urban water management applications tailored to user characteristics and site-specific constraints.
Makropoulos et al. (Thu,) studied this question.