Selecting Portfolios of Water Supply and Demand Management Strategies Under Uncertainty—Contrasting Economic Optimisation and ‘Robust Decision Making’ Approaches

Planning appropriate portfolios of new water supplies and demand management measures requires considering a wide array of options and their interactions over a largely unknown future. Various modelling-assisted approaches are available to help this planning process. This paper applies two such frameworks to the UK’s Thames water resource system and compares their methods and outputs: how they consider uncertainty, how they represent supply and demand management options, and what plans each recommends. The first method is the current England and Wales industry standard: annual least-cost capacity expansion optimisation over a 25 to 30 year time horizon considering capital, operating (fixed and variable), social and environmental costs. The second approach uses stochastic simulation and regret analysis to select a preferred alternative, then statistical cluster analysis to identify causes of system failure enabling further plan improvement. When applied iteratively with system planners this second approach is referred to as Robust Decision Making (RDM). The economic optimisation approach considers all plausible combinations of supply and conservation schemes and recommends the least-cost schedule of their implementation. Our RDM application considers a smaller number of options but makes a more detailed assessment of the effect of uncertainty (supply, demand and energy price uncertainty were considered) on multiple criteria of system performance. The simulation-based approach also enables more realistic interaction amongst supply and demand management schemes. Both approaches recommended different plans which we explain by discussing the benefits and limitations of each. Joint application is recommended to produce least-cost plans that are robust considering multiple criteria of performance across a wide range of futures. Copyright Springer Science+Business Media B.V. 2013