Decadal Lake Volume Changes (2003–2020) and Driving Forces at a Global Scale

Abstract

Lakes play a key role in the global water cycle, providing essential water resources and ecosystem services for humans and wildlife. Quantifying long-term changes in lake volume at a global scale is therefore important to the sustainability of humanity and natural ecosystems. Yet, such an estimate is still unavailable because, unlike lake area, lake volume is three-dimensional, challenging to be estimated consistently across space and time. Here, taking advantage of recent advances in remote sensing technology, especially NASA’s ICESat-2 satellite laser altimeter launched in 2018, we generated monthly volume series from 2003 to 2020 for 9065 lakes worldwide with an area ≥ 10 km2. We found that the total volume of the 9065 lakes increased by 597 km3 (90% confidence interval 239–2618 km3). Validation against in situ measurements showed a correlation coefficient of 0.98, an RMSE (i.e., root mean square error) of 0.57 km3 and a normalized RMSE of 2.6%. In addition, 6753 (74.5%) of the lakes showed an increasing trend in lake volume and were spatially clustered into nine hot spots, most of which are located in sparsely populated high latitudes and the Tibetan Plateau; 2323 (25.5%) of the lakes showed a decreasing trend in lake volume and were clustered into six hot spots—most located in the world’s arid/semi-arid regions where lakes are scarce, but population density is high. Our results uncovered, from a three-dimensional volumetric perspective, spatially uneven lake changes that aggravate the conflict between human demands and lake resources. The situation is likely to intensify given projected higher temperatures in glacier-covered regions and drier climates in arid/semi-arid areas. The 15 hot spots could serve as a blueprint for prioritizing future lake research and conservation efforts.

Leveraging ICESat, ICESat‐2, and Landsat for Global‐Scale, Multi‐Decadal Reconstruction of Lake Water Levels

“…This improvement could be explained by the fact that the hypsometry of this study exhibits much stronger area-level correlations than that of Y. Feng et al (2022). For example, the median R 2 increased from 0.43 to 0.93 (Figure 9b).…”

“…Despite recent advances on documenting long-term changes in lake water storage (Y. Feng et al, 2022;Luo et al, 2022;Yao et al, 2023), water storage data are unavailable for most small water bodies and poorly constrained for some large lakes due to simplified hypsometries or empirical models (Table 1). The level reconstruction method here can be combined with lake area data sets (Pi et al, 2022;Yao et al, 2019;Zhao & Gao, 2018) to fill this data gap.…”

“…For comparison, we also validated the reconstructed water levels in two very recent studies (Y. Feng et al, 2022;. The accuracy of our reconstructed water levels was compared separately with each of these two studies due to the difference in reconstructed water levels using altimetry-derived hypsometry.…”

“…For example, Y. Feng et al. (2022) combined ICESat, ICESat‐2, and Landsat‐derived water areas from the GSW data set to estimate time‐varying water levels and volumes for 9,065 lakes globally over the period 2003–2020. They used water areas from the GSW and an overall area‐level slope based on bootstrapping simulations to reconstruct water levels.…”

The benefits of the water diversion on a densely populated fragmented lake area — A remote sensing view

“…The ICESat/GLAS data validation on Dongting Lake shows that the ICESat/GLAS data processing method is suitable for obtaining water level control points in large lakes [14]. A study of global lakes larger than 10 km2 has shown that ICESat and ICESat-2 measurement errors are lower than radar measurements such as Topex/Poseidon, ENVISAT, CryoSat-2, etc [15]. Although ICESat and ICESat-2 have been used to study lake levels, they have yet to be applied to studying the effects of water diversion on lakes, especially those in densely populated lake areas.…”