Water supply system management design and optimization under uncertainty

A water supply system collects, treats, stores, and distributes water among water sources and consumers. Increasing population, diminishing supplies and variable climatic conditions can cause difficulties in meeting water demands; especially in arid and semiarid regions where water resources are limited. Given the system complexity and the interactions among users and supplies, a large-scale water supply management model can be useful for decision makers to plan water management strategies to cope with future water demand changes. When this long range water supply plan is developed, accuracy and reliability are the two most important factors. To develop an accurate model, as much information as possible on the system has to be considered. As a result, the water supply system has become more complicated and comprehensive structures. Stochastic search techniques thus have evolved to find the most accurate solution for the future water supply plan. Future uncertainty also has been considered to improve system reliability as well as economic feasibility. This suite of tools can be also useful in deriving consensus among competing water needs for proposed long-term water supply plans.; In this study, a general large-scale water supply system that is comprised of modular components including water sources, users, recharge facilities, and water and wastewater treatment plants was developed in a dynamic simulation environment that helps users easily understand the model structure. The model was applied to a realistic hypothetical system and simulated several possible 20-year planning scenarios. In addition to water balances and water quality analyses, construction and operation and maintenance of system components costs were estimated for each scenario. One set of results demonstrates that construction of small-cluster decentralized wastewater treatment systems could be more economical than a centralized plant when communities are spatially scattered or located in steep areas where pumping costs may be prohibitive.; The Shuffled Frog Leaping Algorithm (SFLA), then, was used to minimize the total system cost of the general water supply system. Sizing decisions of system components' capacities---pipe diameter, pump design capacity and head, canal capacity, and water and wastewater treatment capabilities---are decision variables with flow allocations over the water supply network to meet water demands. An explicit representation of energy consumption cost for the operation of satellite wastewater treatment facilities was incorporated into the system in the optimization process of overall system cost. Although the study water supply systems included highly nonlinear terms in the objective function and constraints and several hundred decisions variables, a stochastic search algorithm was applied successfully to find optimal solutions that satisfied all the constraints for the study networks.; An accurate water supply plan is achieved. However, the system reliability is not assured. A robust optimization approach, hence, was introduced into the design process of a water supply system as a framework to consider uncertainties of the correlated future data by applying a new robust optimization approach. The approach allows for the control of the degree of conservatism which is a crucial factor for the system reliabilities and economical feasibilities. The system stability is guaranteed under the most uncertain condition. It was found that the water supply system with uncertainty can be a useful tool to assist decision makers to develop future water supply schemes.