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International virtual water (VW) trade helps to balance water stress across regions. However, it can be questioned whether such trade can remain sustainable as water resources are redistributed across regions resulting from changes in our climate. A conceptual framework to compare VW trade volumes with water fluxes within the water cycle is introduced. We evaluate the distribution of traded water surpluses and deficits associated with crop, animal, and industrial products over 157 countries and 182 global watersheds. About 7% of the countries are identified to conduct VW trade unsustainably. Regions within Africa, North America, central Asia, and Europe exhibit unfeasible VW trading resulting from higher appropriation of freshwater resources than availability influenced by precipitation and evaporation. Assessment at the watershed scale captures overexploitation at finer resolution, generally overlooked in country level analysis. An evaluation into the future reveals more watersheds becoming vulnerable to water storage depletion under future climate trends.

This study suggests a radical approach to hydrologic predictions in ungauged basins, addressing the long standing challenge of issuing predictions when in-situ river discharge does not exist. A simple but powerful rationale for measuring and modeling river discharge is proposed, using coupled advances in hydrologic modeling and satellite remote sensing. Our approach presents a Surrogate River discharge driven Model (SRM) that infers Surrogate River discharge (SR) from remotely sensed microwave signals with the ability to mimic river discharge in varying topographies and vegetation cover, which is then used to calibrate a hydrological model enabling physical realism in the resulting river discharge profile by adding an estimated mean of river discharge via the Budyko framework. The strength of SRM comes from the fact that it only uses remotely sensed data in prediction. The approach is demonstrated for 130 catchments in the Murray Darling Basin (MDB) in Australia, a region of high economic and environmental importance. The newly proposed SR (SR ^L , representing L-band microwave) boosts the Nash-Sutcliffe Efficiency (NSE) of modeled flow, showing a mean NSE of 0.54, with 70% of catchments exceeding NSE 0.4. We conclude that SRM effectively predicts high-flow and low-flow events related to flood and drought. Overall, this new approach will significantly improve catchment simulation capacity, enhancing water security and flood forecasting capability not only in the MDB but also worldwide.