Globally, many countries are actively seeking to maximize the hydropower potential of major river basins, yielding proposals for constructing approximately 3,700 major dams in the near future. At present, economic cost-benefit analyses are the dominant approach for evaluating candidate dam designs. Yet they typically fail to explore the interdependence of dam design and operation by (i) monetizing and aggregating potentially conflicting and heterogeneous objectives into a single metric and (ii) using predefined operating rules aimed at maximizing specific performance objectives for the dams to be designed. Careful consideration of alternative reservoir operating schemes can help to avoid biases in how optimal dam sizes are identified while also clarifying their capacity to adapt to changing hydroclimatic conditions and human demands. This paper presents an integrated framework to solve coupled dam sizing and operation design problems. The framework combines Multiobjective Robust Decision Making and Evolutionary Multiobjective Direct Policy Search into a novel approach to dam sizing, which internalizes the operation design problem and explicitly considers uncertainty in external drivers. We demonstrate the potential of this integrated dam design framework through an ex-post design analysis of the Kariba dam in the Zambezi river basin. Our results show that careful exploration of the coupled planning/operation search space yields designs that significantly outperform the existing Kariba system. Moreover, we demonstrate that our framework leads to a significant reduction in capital costs (i.e., smaller reservoir sizes) while simultaneously improving system robustness with respect to changing hydroclimatology and human irrigation demands.

The value of streamflow forecasts to inform water infrastructure operations has been extensively studied. Yet, their value in informing infrastructure design is still unexplored. In this work, we investigate how dam design is shaped by information feedbacks supporting the implementation of flexible operating policies informed by streamflow forecasts to enable the design of less costly reservoirs relative to alternatives that do not rely on forecast information. Our approach initially explores the maximum potential gain attainable by searching and using the most valuable forecast information and lead time. We then analyze the results? sensitivities relative to existing and synthetic biased forecasts. We demonstrate our approach through an ex post analysis of the Kariba Dam in the Zambezi River Basin. Results show that informing dam design with perfect forecasts enables attaining the same hydropower production of the existing dam, while reducing infrastructure size and associated capital costs by 20%. A forecast‐informed operation of the existing system can instead facilitate an annual average increase of 60 GWh in hydropower production. This finding, extrapolated to the new planned dams in the basin, suggests that forecast informed policies could yield power production benefits equal to 75% of the current annual electricity consumption of the Zambian agricultural sector. The use of biased forecasts substantially reduces this gain, showing that the ESP forecasts value is marginal and that informed infrastructure designs are particularly vulnerable to forecast overestimation. Advancing information feedbacks may therefore become a valuable asset for the ongoing hydropower expansion in the basin.

No abstract

 Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.