Abstract

Over the past decades, increasing awareness has been raised regarding the development of sophisticated mathematical models for supporting agricultural water management. These models aim to cope with the problems of aggravating water shortage and serious water quality degradation and at the same time satisfy the requirement of socioeconomic development. However, the intrinsic uncertainties associated with the agricultural water management systems would bring significant difficulties in formulating and solving the related models and lead to dilemma of decision making. The objective of this study is to give a general introduction of how to conceptualize and formulate inexact optimization models for supporting integrated agricultural water quantity and quality management under uncertainty. A number of inexact optimization approaches based on stochastic, fuzzy, and interval programming models are introduced. Each of them is capable of handling a certain type of uncertain information, which depends on the uncertain features of the system components. Finally, the applicability of various optimization methods is demonstrated through an agricultural water management example.