Decision Support System for Planning of integrated Water Reuse Projects
Thesis or dissertation
University of Exeter
The availability of fresh water supplies throughout the world has been getting scarcer over the past several decades, leading to existing or impending water shortages in many regions. In this context, water reuse has emerged as a genuine and reliable alternative that can be used to supplement, and in some cases substitute traditional water sources. The practice of water reclamation and reuse has developed tremendously in the last century. With the rate of growth projected to increase even further, water reuse schemes of larger size will have to be planned, addressing an ever expanding list of technological, environmental, social and financial considerations. Therefore, decision support systems (DSS) are acutely needed to assist the planners of future water reuse schemes. The DSS developed in this thesis and embodied in the WTRNet (Water Treatment for Reuse with Network Distribution) software tool takes into account the interactions that exist between the individual schemes components (treatment trains, distribution system and end-users of reclaimed water) in evaluation and selection of most promising design alternatives. Comprising of a simulation and optimisation components, the DSS provides a user-friendly platform for evaluation and optimisation of integrated water reuse schemes. The numbers of potential design alternatives for schemes of different size are determined, and are shown to be substantially reduced by using rules that determine feasible treatment trains. Optimisation algorithms appropriate for schemes of different size are developed and tested on case studies to verify the DSS, which includes a novel and efficient linear programming methodology of least-cost sizing of reclaimed water distribution systems. The benefits of evaluation in the proposed manner are demonstrated by deriving optimal water reuse schemes for the City of Waterloo, Ontario, Canada. The results of application of WTRNet on the case study indicate that the selection of optimal treatment alternatives based on different criteria has potentially significant effect on the cost of optimal alternatives, and that the selection of end-users requires a structured approach that takes into account factors other than their demand and location relative to the source.