Designing With Information Feedbacks: Forecast Informed Reservoir Sizing and Operation

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.