The Caspian Sea defines the recent global inland surface water storage decline

The quantification of inland surface water storage anomaly (SWSA) and its spatial-temporal variability across rivers, streams, lakes, reservoirs, floodplains, and wetlands is crucial for understanding the role of continental water in the global hydrological and biochemical cycles. Such knowledge is also essential for sustaining human societies and ecosystems. For more than a decade, significant efforts have been devoted to characterising SWSA in some major river basins and globally for only some types of water bodies. However, global SWSA for all surface water bodies simultaneously has not yet been quantified, and its long-term behavior has not yet been investigated. 

Here, we present the first global estimates of SWSA and investigate its long-term behaviour from 1992 to 2020. This is achieved by benefiting from the integration of multi-mission global satellite products, including satellite-derived Surface Water Height (SWH) from nadir altimeters and Surface Water and Ocean Topography (SWOT). Two methods have been coupled to estimate SWSA over each type of surface water body. The first one, a hypsometric curve method, consists of the combination of surface water extent (from the Global Inundation Extent from Multi-Satellite (GIEMS-2 dataset)) with topographic data from the global Digital Elevation Model (DEM), namely Forest And Buildings removed Copernicus DEM (FABDEM). The second one, based on the lake water level – area storage model, combined the simultaneous lake surface water extent and SWH. Our new SWSA dataset agrees well with other existing regional SWSA estimations.

Our results highlight the relevance of the Caspian Sea system in driving the recent global SWSA decline. At the global scale, results including the Caspian Sea provide a significant negative trend of -14 km3 yr-1. Conversely, the exclusion of the Caspian Sea shows a positive trend at 6 km3 yr-1. 

The newly developed global satellite observation-based SWSA dataset enables novel insights as a new source of information for hydrological and multidisciplinary sciences, including data assimilation, land–ocean exchanges, and water management. Moreover, this global dataset is a benchmark of SWOT-based storage products and their evaluation and validation.