Abstract
AbstractThe 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.
Highlights
Dam design and operation are classically treated as two independent problems
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
We demonstrate the value of our methodological contribution through an ex post design analysis of the Kariba Dam in the Zambezi River Basin (ZRB), a region where there are a large number of dams planned in the near future (World Bank, 2010), motivating the need for innovations in dam design
Summary
Dam design and operation are classically treated as two independent problems. Optimal reservoir capacity sizing has typically been addressed using a least-cost problem framing, aimed at minimizing total costs (e.g., Perelman et al, 2013 in the water sector; Rodriguez et al, 2015 in the energy sector). More recent examples (e.g., Bertoni et al, 2019; Geressu & Harou, 2015) show that the joint design of reservoir size and operation can benefit from the use of state aware control actions that are dynamic and adaptive to the system conditions being observed. These operating rules are generally conditioned on the reservoir level/storage only, while they do not account for other available information feedbacks, such as streamflow forecasts, which support more flexible and adaptive operations (e.g., Giuliani et al, 2019; Libisch-Lehner et al, 2019; Nayak et al, 2018). Reservoirs operated with respect to long-term objectives (e.g., irrigation water supply) might primarily benefit from seasonal forecasts
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