Decision Support Model for a Sustainable Regional Water Supply

Licentiate thesis, 2018

Water supply provision has traditionally been a municipal responsibility. However, environmental, social and economic drivers are now making it more attractive to manage the water services in a more aggregated way. Yet, even though municipalities have cooperated to improve their water supply provision for decades, the topic is fairly under-researched and advantages and disadvantages not fully understood. Further, decisions regarding drinking water cooperation and other regional interventions are often made without a proper method of balancing, for example, the economic, health and environmental effects thereof. This thesis presents a decision support model to aid in regional water supply decision-making. The model is based on a combination of cost-benefit analysis and multi-criteria decision analysis for sustainability assessments of regional water supply interventions, including formations of inter-municipal cooperations. The proposed model integrates quantitative and semi-quantitative information on sustainability criteria, and it provides a novel way of presenting monetized benefits and costs with non-monetized social and environmental effects of regional water supply alternatives. The decision support model is based on a probabilistic approach where uncertainties are represented by statistical probability distributions and modeled by means of Monte Carlo simulations. A case study is used to exemplify and evaluate model application in decision situations regarding regionalization of water governance, (de)centralization of water production, and source water quality and redundancy aspects. The proposed model can be used by decision-makers to develop coherent preferences within economic, environmental and social sustainability so that decisions on regional water supply interventions can be taken with a higher degree of confidence. The results of the thesis contribute to a decision support toolbox needed to make proper evaluations and informed decisions in order to achieve long term sustainable water supply solutions.