Global Freshwater Storage Capability across Time Scales in the GRACE Satellite Era

Freshwater is recharged mainly by rainfall and stored inland for a period of time, which is directly affected by its storage capability. The storage capability of river basins has different spatiotemporal features that are important for the predictability of freshwater resources. However, the estimation of freshwater storage capability (FSC) remains a challenge due to the lack of observations and quantification indices. Here, we use a metric that characterizes hydrological inertia after rainfalls to analyze FSC over the 194 largest global major river basins based on satellite observations from the Gravity Recovery and Climate Experiment (GRACE) and simulations from the Community Land Model version 5 (CLM5). During 2003-16, the global land was observed to retain 28% of precipitation after one month based on GRACE observations, and the simulation depicts that the retained proportions decrease from 42% after one day to 26% after one month, with smaller FSC partly attributed to wetter conditions and higher vegetation densities. The root zone contributes about 40% to the global land FSC on daily to monthly time scales. As the time scale increases, the contribution from the surface soil decreases from 26% to 14%, while the contribution from the deep soil increases from 4% to 10%. Snow contributes over 20% of land FSC, especially over high latitudes. With six decades of CLM5 long-term simulations, it is revealed that the change of FSC in most basins is related to internal climate variability. The FSC of river basins which displays the proportion of precipitation retained on land is worthy of further attention regarding the predictability of water resources.

Automated summary

Freshwater storage capability in river basins is influenced by various factors, with the root zone contributing significantly to global land FSC. Long-term simulations indicate that changes in FSC in most basins are linked to internal climate variability, highlighting the importance of understanding the proportion of precipitation retained on land for water resource predictability.