Globally, the pressures of expanding populations, climate change, and increased energy demands are motivating significant investments in re-operationalizing existing reservoirs or designing operating policies for new ones. These challenges require an understanding of the tradeoffs that emerge across the complex suite of multi-sector demands in river basin systems. This study benchmarks our current capabilities to use Evolutionary Multi-Objective Direct Policy Search (EMODPS), a decision analytic framework in which reservoirs' candidate operating policies are represented using parameterized global approximators (e.g., radial basis functions) then those parameterized functions are optimized using multi-objective evolutionary algorithms to discover the Pareto approximate operating policies. We contribute a comprehensive diagnostic assessment of modern MOEAs' abilities to support EMODPS using the Conowingo reservoir in the Lower Susquehanna River Basin, Pennsylvania, USA. Our diagnostic results highlight that EMODPS can be very challenging for some modern MOEAs and that epsilon dominance, time-continuation, and auto-adaptive search are helpful for attaining high levels of performance. The ε-MOEA, the auto-adaptive Borg MOEA, and ε-NSGAII all yielded superior results for the six-objective Lower Susquehanna benchmarking test case. The top algorithms show low sensitivity to different MOEA parameterization choices and high algorithmic reliability in attaining consistent results for different random MOEA trials. Overall, EMODPS poses a promising method for discovering key reservoir management tradeoffs; however algorithmic choice remains a key concern for problems of increasing complexity

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As "instruments of development" providing flexible and firm hydropower, flood protection, and dependable water deliveries among other co-benefits (World Commission on Dams, 2000), large dam projects continue to attract national and regional investment. However, significant social and environmental impacts associated with large dam construction and operation (

Abstract. The construction of the Akosombo and Kpong dams in the Lower Volta River Basin in Ghana changed the downstream riverine ecosystem and affected the lives of downstream communities, particularly those who lost their traditional livelihoods. In contrast to the costs borne by those in the vicinity of the river, Ghana as a whole, has enjoyed vast economic benefits from the affordable hydropower, irrigation schemes and lake tourism that developed after construction of the dams. Herein lies the challenge; there exists a trade-off between water for river ecosystems and related services on the one hand, and anthropogenic water demands such hydropower or irrigation on the other. In this study, an Evolutionary Multi-Objective Direct Policy Search (EMODPS) is used to identify the multi-sectorial trade-offs that exist in the Lower Volta River Basin. Three environmental flows, previously determined for the Lower Volta are incorporated separately as an environmental objective. The results highlight the dominance of hydropower production in the Lower Volta, but show that there is room for providing environmental flows under current climatic and water use conditions if firm energy requirement from Akosombo Dam reduces by 12 % to 38 % depending on the environmental flow regime that is implemented. There is uncertainty in climate change effects on runoff in this region, however multiple scenarios are investigated. It is found that climate change leading to increased annual inflows to the Akosombo Dam reduces the trade-off between hydropower and the environment while climate change resulting in lower inflows provide the opportunity to strategically provide dry season environmental flows, that is, reduce flows sufficiently to meet low flow requirements for key ecosystem services such as the clam fishery. This study not only highlights the challenges in balancing anthropogenic water demands and environmental considerations in managing existing dams, but also identifies opportunities for compromise in the Lower Volta River.

<p>The integrated management of water reuse technologies and their coordination with the operations of the other water system components are fundamental to fully exploit the reuse potential. Yet, these technologies are usually designed considering their individual parameters (e.g., efficiency, durability, maintenance costs, energy consumption), more than the integration with traditional water management practices, and the impacts on the final users at the system scale.</p> <p>Here, we adopt a portable framework based on optimal control methods and machine learning to evaluate the cross-sector impacts of water loops. The framework is developed for the Apulia Region, Southern Italy, a drought-prone area characterized by the presence of a complex water distribution network and multiple conflicting users across agricultural districts, industry, and drinking water supply.</p> <p>The robustness of each adaptation strategy is comprehensively investigated through a scenario-based approach, including the analysis of climatic, socio-economic (drinking, irrigation, and industrial water demand pattern), legal (environmental flow constraints), and technological (water reuse implementation) aspects.</p> <p>Results show that the combined effect of climate and socio-economic changes will dramatically affect the Apulia water system, leading to unsustainable pressure on freshwater resources. In addition, the implementation of the environmental flow constraints will further reduce the operation space. Future water deficit is thus expected to increase at half-century (2050-2059) as well as in the long-term (2090-2099), especially under the more extreme climate projection (RCP 8.5).</p> <p>Results also show that water reuse actions remarkably improve the situation, but the effect is only partial and far from entirely closing the gap with the current situation. This means that the specific adaptation actions here adopted are not sufficient and that it is necessary to further promote the spread of the reuse technologies and increase their efficiency.</p> <p>The proposed framework is a decision support system that aims at assisting policy-makers in the transition to a circular water economy by integrating water management and treatment-reuse technologies.</p>