| Water resource shortages and water supply instability are considered major barriers to sustainable water resources management. One major factor contributing to the formation of such barriers is the lack of efficient decision-making approaches to facilitate decision makers in developing sustainable water resources management policies. Though a number of mathematical programming methods have been used to overcome the above mentioned barriers, significant effort is required to develop robust programming approaches in order to deal with increasingly complicated real-world problems.;The major contributions of this research are as follows: (1) The proposed SIFLP, STFLP and IVFLP methods are able to fill the missing information gaps when solving conventional fuzzy possibilistic programming problems, such that solutions with enhanced reliability can be obtained. (2) The proposed IRFLP and RTSP are able to deal with problems where conventional intervals are ineffective in reflecting the complexity of parameters, or where specific demands of dual-layer solutions are desired by decision makers. (3) The proposed ITSP and IMSP methods can facilitate decision makers in making a rapid and sequential response to upcoming severe flooding disasters by efficiently operating multiple control measures in a quantified manner, particularly in large-scale floodplain management systems, as well as long-term planning problems. (4) The proposed IFSP can address flexible economic measures in accordance with water-availability conditions, thus being capable of solving problems with randomly-varied water quantity inputs. (5) The proposed simulation-based rough-interval programming approach incorporates both land-use management and water-resources management in a general modeling framework to support comprehensive decision making under complex individual- and/or dual-uncertainty.;In this dissertation research, a set of inexact mathematical programming methods are developed and applied to water resources management. They include four inexact fuzzy programming methods (i.e. SIA-based inexact fuzzy linear programming, SIFLP; SIA-based two-stage fuzzy linear programming, STFLP; inexact interval-valued fuzzy linear programming, IVFLP; rough-interval fuzzy linear programming, IRFLP) and four stochastic programming methods (i.e. inexact two-stage stochastic programming, ITSP; inexact fuzzy-stochastic programming, IFSP; rough-interval two-stage stochastic programming, RTSP; inexact multi-stage stochastic programming, IMSP). In addition to the aforementioned efforts, a simulation-based rough-interval programming approach is developed for integrated agricultural land-use and irrigation management in China's rural regions. The approach is beneficial to decision making under various uncertainties and complexities. |
