Risk‐based water resources planning is based on the premise that water managers should invest up to the point where the marginal benefit of risk reduction equals the marginal cost of achieving that benefit. However, this cost‐benefit approach may not guarantee robustness under uncertain future conditions, for instance under climatic changes. In this paper, we expand risk‐based decision analysis to explore possible ways of enhancing robustness in engineered water resources systems under different risk attitudes. Risk is measured as the expected annual cost of water use restrictions, while robustness is interpreted in the decision‐theoretic sense as the ability of a water resource system to maintain performance—expressed as a tolerable risk of water use restrictions—under a wide range of possible future conditions. Linking risk attitudes with robustness allows stakeholders to explicitly trade‐off incremental increases in robustness with investment costs for a given level of risk. We illustrate the framework through a case study of London's water supply system using state‐of‐the ‐art regional climate simulations to inform the estimation of risk and robustness.
Significant population increase in urban areas is likely to result in a deterioration of drought security and level of service provided by urban water resource systems. One way to cope with this is to optimally schedule the expansion of system resources. However, the high capital costs and environmental impacts associated with expanding or building major water infrastructure warrant the investigation of scheduling system operational options such as reservoir operating rules, demand reduction policies, and drought contingency plans, as a way of delaying or avoiding the expansion of water supply infrastructure. Traditionally, minimizing cost has been considered the primary objective in scheduling capacity expansion problems. In this paper, we consider some of the drawbacks of this approach. It is shown that there is no guarantee that the social burden of coping with drought emergencies is shared equitably across planning stages. In addition, it is shown that previous approaches do not adequately exploit the benefits of joint optimization of operational and infrastructure options and do not adequately address the need for the high level of drought security expected for urban systems. To address these shortcomings, a new multiobjective optimization approach to scheduling capacity expansion in an urban water resource system is presented and illustrated in a case study involving the bulk water supply system for Canberra. The results show that the multiobjective approach can address the temporal equity issue of sharing the burden of drought emergencies and that joint optimization of operational and infrastructure options can provide solutions superior to those just involving infrastructure options.
Choosing secure water resource management plans inevitably requires trade-offs between risks (for a variety of stakeholders), costs, and other impacts. We have previously argued that water resources planning should focus upon metrics of risk of water restrictions, accompanied by extensive simulation and scenario-based exploration of uncertainty. However, the results of optimization subject to risk constraints can be sensitive to the specification of tolerable risk, which may not be precisely or consistently defined by different stakeholders. In this paper, we recast the water resources planning problem as a multiobjective optimization problem to identify least cost schemes that satisfy a set of criteria for tolerable risk, where tolerable risk is defined in terms of the frequency of water use restrictions of different levels of severity. Our proposed method links a very large ensemble of climate model projections to a water resource system model and a multiobjective optimization algorithm to identify a Pareto optimal set of water resource management plans across a 25 years planning period. In a case study application to the London water supply system, we identify water resources management plans that, for a given financial cost, maximize performance with respect to one or more probabilistic criteria. This illustrates trade-offs between financial costs of plans and risk, and between risk criteria for four different severities of water use restrictions. Graphical representation of alternative sequences of investments in the Pareto set helps to identify water management options for which there is a robust case for including them in the plan.
Water scarcity occurs when water demand exceeds natural water availability over a range of spatial and temporal scales. Though meteorological and hydrological droughts have been analyzed over large spatial scales, the impacts of water scarcity have typically been addressed at a catchment scale. Here we explore how droughts and water scarcity interact over a larger and more complex spatial domain, by combining climate, hydrological, and water resource system models at a national scale across England and Wales. This approach is essential in a highly connected and heterogeneous region like England and Wales, where we represent 80 different catchments; 70 different water resource zones; 16 water utility companies; and the water supply for over 50 million people. We find that if a reservoir's storage is in its first percentile (i.e., the volume that is exceeded 99% of the time), then there is, on average, a 40% chance that reservoirs in neighboring catchments will also be at or below their first percentile storage volume. The coincidence of low reservoir storage decays relatively quickly, stabilizing after about 100–150 km, implying that if interbasin transfers are to be provided to enhance drought resilience, they will need to be at least this length. Based on a large ensemble of future climate simulations, we show that extreme droughts in precipitation, streamflow, and reservoir storage volume are projected to worsen in every catchment. The probability of a year with water use restrictions doubles by 2050 and is four times worse by 2100.
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