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Recent water infrastructure planning models demonstrate that explicitly accounting for hydrological changes in long‐term water planning reduces costs and increases system robustness. However, current models do not consider the effects of other changes occurring in the system over long time horizons, namely technology and policy innovation. By leveraging state‐of‐the‐art dynamic control techniques, we propose a suite of tools that explicitly relate hydrologic change, technology innovation, and policy interventions to system‐level water costs. We design robust and cost‐optimal strategies for water supply expansion under hydrological variability and hundreds of plausible innovation states, for example, treatment cost and diversification improvements, deployment times, and demand reduction campaigns. Our approach circumvents the need to pre‐assign probabilities to innovation scenarios and, instead, directly calculates the effects of technology, policy, and hydrology variations on system cost and planning strategies to identify avenues of impactful innovation. These tools can support technology development hubs, urban, state, and federal water planners in anticipating cost implications of technology and policy innovation at the local level, and prioritizing high‐impact innovation goals based on quantitative targets. Results for the case study of Santa Barbara, California identify high‐value innovation attributes for the city as well as combinations of innovation attributes across technologies and policies, and quantify their potential utility cost reductions. Plain Language Summary: Planning for water infrastructure is difficult due to the long‐term planning horizons and changes in climate, policy, and technology that can occur in these systems. Many studies have focused on incorporating climate uncertainty but have ignored the potential impact of innovation in policy and technology. The lack of tools to assess the impact of innovation on water infrastructure planning is problematic on two fronts. First, water planners lack decision support tools to guide their strategies to yield potential benefits of innovation. Second, technology and policy innovation researchers lack tools to prioritize R&D advances and policy changes based on their impact on water system‐level costs. This work addresses this gap by generating robust and cost‐optimal strategies for water supply expansion under hydrological variability and hundreds of plausible innovation states. This is crucial for sustainable and effective water infrastructure planning that can adapt to future uncertainties and capitalize on emerging opportunities. Key Points: In addition to climate change, technology, and policy innovation can impact long‐term water system cost, and planning strategiesQuantifying system‐level value of innovation aids in identifying high‐impact states of innovation [ABSTRACT FROM AUTHOR]

Uncertainty arising from climate change poses a central challenge to the long‐term performance of many engineered water systems. Water supply infrastructure projects can leverage different types of flexibility, in planning, design, or operations, to adapt infrastructure systems in response to climate change over time. Both flexible planning and design enable future capacity expansion if‐and‐when needed, with flexible design proactively incorporating physical design changes that enable retrofits. All three forms of flexibility have not previously been analyzed together to explicitly assess their relative value in mitigating cost and water supply reliability risk. In this paper, we propose a new framework to evaluate combinations of flexible planning, design, and operations. We develop a nested stochastic dynamic optimization approach that jointly optimizes dam development and operating policies under dynamic climate uncertainty. We demonstrate this approach on a reservoir project near Mombasa, Kenya. Our results find that flexible operations have the greatest potential to reduce costs. Flexible design and flexible planning can amplify the value of flexible operations under higher discounting scenarios and when initial infrastructure capacities are undersized. This approach provides insight on the climate change and techno‐economic conditions under which flexible planning, design, and operations can be best leveraged individually or in combination to reduce climate change uncertainty risks in water supply infrastructure projects. Key Points: We develop a framework to compare the value of combinations of flexibility in water supply infrastructure planning, design, and operationsFlexible operations are more effective than flexible planning or design in addressing climate uncertainty in water‐limited environmentsFlexible planning and design are more useful when initial reservoir capacity is low, discounting is high, or the cost of shortages is high [ABSTRACT FROM AUTHOR]

Socio-economic costs of drought are progressively increasing worldwide due to undergoing alterations of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, traditional drought indexes often fail in detecting critical events in highly regulated systems, where natural water availability is conditioned by the operations of water infrastructures such as dams, diversions, and pumping wells. Here, ad hoc index formulations are usually adopted based on empirical combinations of several, supposed-to-be significant, hydro-meteorological variables. These customized formulations, however, while effective in the design basin, can hardly be generalized and transferred to different contexts. In this study, we contribute FRIDA (FRamework for Index-based Drought Analysis), a novel framework for the automatic design of basin-customized drought indexes. In contrast to ad-hoc, empirical approaches, FRIDA is fully-automated, generalizable, and portable across different basins. FRIDA builds an index representing a surrogate of the drought conditions of the basin, computed by combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm. We used the Wrapper for Quasi Equally Informative Subset Selection W_GEISS which features a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The preferred variable subset is selected among the efficient solutions and used to formulate the final index according to alternative model structures. We apply FRIDA to the case study of the Jucar river basin (Spain), a drought prone, highly regulated Mediterranean water system, where an advanced drought management plan relying on the formulation of an ad-hoc State Index is used for triggering drought restraining measures. The State Index was constructed empirically with a trial-and-error process begun in the '80s and finalized in 2007, guided by the experts from Confederaciòn Hidrogràfica del Jùcar. Our results show that the automated variable selection outcomes align with CHJ's 25 years-long empirical refinement. In addition, the resultant FRIDA index outperforms the official State Index in terms of accuracy in reproducing the target variable and cardinality of the selected inputs' set. [ABSTRACT FROM AUTHOR]

Global trends in population growth and rising economic prosperity are expected to increase the demand for energy, food, and water, particularly affecting rapidly-growing African economies. To support the production of clean energy and extensive irrigation projects, investment in large dams is increasing. To promote development pathways that are socially inclusive as well as environmentally and economically sustainable it is crucial to assess the social, economic, and environmental impacts of such funding, taking into account the interests of local stakeholders.In this work, we explore the effects of alternative development pathways on the water-energy-food nexus of the Omo River – Lake Turkana basin (Ethiopia and Kenya). In this peculiar region, dam infrastructure development and expanding agriculture might impact the local social, economic, and environmental structures. In the lower Omo valley, seasonal Omo floods support the practice of recession agriculture, which constitutes the livelihood of local indigenous tribes. Further downstream, on the Ethiopian-Kenyan border, the Omo river contributes about 90% of inflow volume to Lake Turkana. This endorheic lake is located in an extremely arid part of the Kenyan Rift Valley and its' water is key to support the local pastoralists and fishermen. We analyze the effects of alternative energy and food development pathways from a multi-sectoral perspective, assessing the trade-offs in respect of hydropower production, irrigation supply, indigenous recession agriculture and other ecosystem services in the Lower Omo as well as fish yield in Lake Turkana. In addition, we test the robustness of the designed pathways against a wide range of potential changes in both flow regimes and irrigation demands. We do so using a two stage framework to first identify optimal pathways using an optimization procedure with a simplified system model, and then testing the pathways identified as optimal using a more detailed (but computationally expensive) model of the nexus interactions. Results show that our approach provides an objective framework to identify solutions that are able to address the water-energy-food nexus tradeoffs and that perform robustly under changing climatic and societal conditions. [ABSTRACT FROM AUTHOR]

With more than 3500 hydropower dams currently being planned or built around the world, the need for optimal dam planning is more compelling than ever. Current literature efforts are directed towards strategic sizing and siting of dams to maximize economic return and minimize environmental impacts in regime conditions. However, also the initial transient phase of reservoir filling may have substantial environmental and economic implications and, especially in large projects, it can be responsible for critical sectoral conflicts associated to dam development. In this phase, precaution towards downstream impacts requires transiting high percentages of inflow, resulting in multi-years, even decadal, filling transients. Conversely, upstream interests (e.g., hydropower production) favor fast impoundment of water, albeit generating critical periods of minimal streamflow downstream. In this process, hydroclimatic variability plays a key role: if the filling occurs during a dry spell, augmented impacts must be endured by upstream and downstream sectors. The state of global climate teleconnections represents a valuable source of predictability of local hydrometeorological anomalies, which can provide a dual support to dam planning. First, in scheduling a favorable time to start the filling operations based on local effects of long-term climatic oscillations, and second, in designing effective filling strategies adaptive to medium-term hydroclimatic variability. In this work, we consider the case study of the Omo-Turkana basin (Ethiopia-Kenya) to demonstrate the use of seasonal drought forecasts based on multiple climate teleconnections for modulating reservoir filling operations according to the predicted drought conditions, e.g. by transiting higher fractions of the inflow when a drought is forecasted. This case study is in this respect exemplary, because the impacts due to the construction and filling of Gibe III dam and to the current construction of Koysha dam, raised the strong opposition of local communities and international organizations. We run a retrospective analysis of Gibe III filling and compare the impacts of the historical filling strategy to designed alternative strategies, demonstrating the potential to significantly decrease downstream impacts, for instance by successfully maintaining the level of downstream Lake Turkana up to one meter higher than historically observed. Our approach also shows that 2015 was an unfavorable year to begin the filling operations of Gibe III, and significant damage could be avoided by delaying or anticipating the operations by 2-3 years. Finally, we predict that the planned time to start filling the Koysha dam, 2021, occurs at the beginning of a multi-year drought and we issue recommendations on more favorable timings. [ABSTRACT FROM AUTHOR]