Decision Support Systems for Integrated Water Resources Management Under Water Scarcity

Abstract

Environmental decision support systems (EDSS) can be defined as intelligent information systems that are able to integrate numerical models (linear or nonlinear) with artificial intelligence (AI) techniques, together with geographical information and environmental ontologies. EDSS emulate the expert’s reasoning processes in decision making, integrating geographical information and environmental ontologies, reducing the time in which decisions are made, as well as improving the consistency and quality of those decisions. EDSS can be useful to cope with the complexity and multidisciplinary nature of Integrated Water Resource Management (IWRM). Besides, the Drought Management Plan Report written by the Water Scarcity and Droughts Expert Network (November 2007) states the “Development of decision support systems for the best exploitation of all information available, including drought forecasts, in order to optimize drought management and mitigation measures” as one of the main needs for advances in drought research. The necessity to confront complexity when dealing with IWRM is first stated in the paper. Then an EDSS as a promising tool to cope with this complexity is introduced, putting special emphasis in a proposal for EDSS development. Next the paper reviews the more relevant decision support systems (DSS) published for IWRM under water scarcity. Classical DSS to model environmental systems as well as those DSS including knowledge-based or AI techniques (i.e., EDSS) are reviewed. Open questions related to the EDSS development and application include improvement of data and knowledge acquisition and knowledge implementation methods, better integration of numerical models and AI techniques (both in simulation and real applications), evaluation of EDSS (lack of benchmarks), protocols to facilitate sharing and reuse of knowledge, involvement of end-users, and probably others.