Finding Robust Solutions to Water Resources Problems

Abstract

Water resources planners and managers are continually faced with decisions to be made under uncertainty. In planning problems such as water supply, flood control, and ground-water remediation, the trade-offs among expected cost, cost variability, and system performance and reliability must be assessed amidst inherent variability and imperfect information. Robust optimization (RO) is introduced as a framework for evaluating these trade-offs and controlling the effects of uncertainty in water resources screening models. Upon the introduction of scenarios, which represent realizations of the random parameters in the model, two types of robustness are defined: a policy is optimality-robust if it remains optimal or nearly optimal for all scenarios, and feasibility-robust if it remains feasible or nearly feasible for all scenarios. Applications to urban water transfer planning and ground-water quality management are presented, with optimality robustness related to cost variability and feasibility robustness related to system reliability. Results show that RO can be a useful framework for evaluating the intrinsic trade-offs involving risk and finding solutions that hedge against inherent and parameter uncertainty.