The evaporative loss from global lakes (natural and artificial) is a critical component of the terrestrial water and energy balance. However, the evaporation volume of these water bodies—from the spatial distribution to the long-term trend—is as of yet unknown. Here, using satellite observations and modeling tools, we quantified the evaporation volume from 1.42 million global lakes from 1985 to 2018. We find that the long-term average lake evaporation is 1500 ± 150 km³ year⁻¹ and it has increased at a rate of 3.12 km³ year⁻¹. The trend attributions include an increasing evaporation rate (58%), decreasing lake ice coverage (23%), and increasing lake surface area (19%). While only accounting for 5% of the global lake storage capacity, artificial lakes (i.e., reservoirs) contribute 16% to the evaporation volume. Our results underline the importance of using evaporation volume, rather than evaporation rate, as the primary index for assessing climatic impacts on lake systems.

Reservoir storage information is essential for accurate flood monitoring and prediction. South Asia, however, is dominated by international river basins where communications among neighboring countries about reservoir storage and management are extremely limited. A suite of satellite observations were combined to achieve high‐quality estimation of reservoir storage and storage variations in South Asia from 2000 to 2012. The approach used water surface area estimations from the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices product and the area‐elevation relationship to estimate reservoir storage. The surface elevation measurements were from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud, and land Elevation Satellite (ICESat). In order to improve the accuracy of water surface area estimations for relatively small reservoirs, a novel classification algorithm was developed. In this study, storage information was retrieved for a total of 21 reservoirs, which represents 28% of the integrated reservoir capacity in South Asia. The satellite‐based reservoir elevation and storage were validated by gauge observations over five reservoirs. The storage estimates were highly correlated with observations (i.e., coefficients of determination larger than 0.9), with normalized root mean square error (NRMSE) ranging from 9.51% to 25.20%. Uncertainty analysis was also conducted for the remotely sensed storage estimations. For the parameterization uncertainty associated with surface area retrieval, the storage mean relative error was 3.90%. With regard to the uncertainty introduced by ICESat/GLAS elevation measurements, the storage mean relative error was 0.67%.

The potential of using Landsat for assessing long‐term water surface dynamics of individual reservoirs at a global scale has been significantly hindered by contaminations from clouds, cloud shadows, and terrain shadows. A novel algorithm was developed toward the automatic correction of these contaminated image classifications. By applying this algorithm to the data set by Pekel et al. (2016, https://doi.org/10.1038/nature20584), time series of area values for 6,817 global reservoirs (with an integrated capacity of 6,099 km³) were generated from 1984 to 2015. The number of effective images that can be used in each time series has been improved by 81% on average. The long‐term average area for these global reservoirs was corrected from 1.73 × 10⁵ km² to 3.94 × 10⁵ km². The results were proven to be robust through validation using observations, synthetic data, and visual inspection. This continuous reservoir surface area data set can provide benefit to various applications (both at continental and local scales).

Surface water reservoirs are increasingly being relied upon to meet rising demands in the context of growing population and changing climate. However, the amount of water available in reservoirs (and the corresponding trends) have not been well quantified at the global scale. Here we use satellite observations to estimate the storage variations of 7245 global reservoirs from 1999 to 2018. Total global reservoir storage has increased at a rate of 27.82 ± 0.08 km³/yr, which is mainly attributed to the construction of new dams. However, the normalized reservoir storage (NS)—the ratio of the actual storage to the storage capacity—has declined by 0.82 ± 0.01%. The decline of NS values is especially pronounced in the global south, while the global north mainly exhibits an NS increase. With predicted decreasing runoff and increasing water demand, these observed diminishing storage returns of reservoir construction will likely persist into the future.