Power system reliability is sensitive to climate-driven variations in both energy demand and water availability, yet the combined effect of these impacts is rarely evaluated. Here we show that combined climate change impacts on loads and hydropower generation may have a transformative effect on the nature and seasonality of power shortfall risk in the U.S. Pacific Northwest. Under climate change, potential shortfall events occur more readily, but are significantly less severe in nature. A seasonal reversal in shortfall risk occurs: winter shortfalls are eradicated due to reduced building heating demands, while summer shortfalls multiply as increased peak loads for day-time cooling coincide with impaired hydropower generation. Many of these summer shortfalls go unregistered when climate change impacts on loads and hydropower dispatch are analyzed in isolation—highlighting an important role of compound events.

Future rates of global groundwater depletion will depend on the economic and environmental viability of extracting water from increasingly stressed aquifers. Here we analyze global groundwater depletion by considering these factors explicitly. Global gridded groundwater availability and extraction cost data are aggregated to produce nonrenewable resource supply curves for 235 major river basins and geopolitical regions. These resources are then exposed to dynamically generated demands for water in a fully coupled, multisectoral, global simulation. As groundwater head levels drop, imposing greater capital and operating costs to bring water to the surface, modeled water use sectors are able to deploy a range of supply‐ and demand‐driven adaptive responses. Results demonstrate large sensitivity in global groundwater depletion rates to adjustments in resource exploitability. Extraction costs moderate demands for nonrenewable water substantially, resulting in the onset of a decline in global groundwater depletion rates within the twenty‐first century. New groundwater depletion hot spots may emerge as crop producers abandon overexploited basins and expand croplands in regions with cheaper, more plentiful water resources.

Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

There are over 52,000 dams in the contiguous US ranging from 0.5 to 243 meters high that collectively hold 600,000 million cubic meters of water. These structures have dramatically affected the river dynamics of every major watershed in the country. While there are national datasets that document dam attributes, there is no national dataset of reservoir operations. Here we present a dataset of historical reservoir inflows, outflows and changes in storage for 679 major reservoirs across the US, called ResOpsUS. All of the data are provided at a daily temporal resolution. Temporal coverage varies by reservoir depending on construction date and digital data availability. Overall, the data spans from 1930 to 2020, although the best coverage is for the most recent years, particularly 1980 to 2020. The reservoirs included in our dataset cover more than half of the total storage of large reservoirs in the US (defined as reservoirs with storage greater 0.1 km³). We document the assembly process of this dataset as well as its contents. Historical operations are also compared to static reservoir attribute datasets for validation.