A review of 20-year applications of multi-attribute decision-making in environmental and water resources planning and management

Abstract

Multi-attribute decision-making (MADM) is an umbrella term to describe a series of mathematical frameworks that, in essence, enable the decision-makers to evaluate the desirability of any feasible solution by considering a set of, often, conflicting evaluation criteria. Given their vast capabilities, the MADM methods are especially helpful for water resources planning and management. This review attempts to shed light on the roles of the MADM methods in the field of water resources decision-making during the last two decades. More than 320 scholarly published articles from 57 different countries were analyzed based on the geographic factors, the number of decision-makers involved, the type of MADM methods, the number of alternatives and criteria, the weight assignment methods, the viewpoints on uncertainty, and the subject of these studies. The results clearly revealed the ever-rising applications of the MADM methods for water resources management. It was also found that some regions, such as the Middle East, more frequently resort to these methods to address their water crisis problems. This review indicated that the analytical hierarchy process (AHP) was the most popular MADM method. Based on the reviewed studies and their results, three major recommendations can be made herein: (1) It is wise to address the uncertainty associated with the applications of the MADM methods in the field of water resources by conducting sensitivity analysis and/or resorting to probabilistic/fuzzy frameworks; (2) given the identified tendency toward subjective MADM, it is crucial to employ checking frameworks, such as the Delphi methods, to assess the consistency of the subjective evaluations; and (3) it is necessary to consider not only the technical criteria but the economic, environmental, legislative, and political evaluation criteria as well to account for the multidimensional nature of water resources problems.