Precipitation extremes are among the most serious consequences of climate change around the world. The observed and projected frequency and intensity of extreme precipitation in some regions will greatly influence the social economy. The frequency of extreme precipitation and the population and economic exposure were quantified for a base period (1986–2005) and future periods (2016–2035 and 2046–2065) based on bias corrected projections of daily precipitation from five global climatic models forced with three representative concentration pathways (RCPs) and projections of population and gross domestic product (GDP) in the shared socioeconomic pathways (SSPs). The RCP8.5‐SSP3 scenario produces the highest global population exposure for 2046–2065, with nearly 30% of the global population (2.97 × 10⁹ persons) exposed to precipitation extremes >10 days/a. The RCP2.6‐SSP1 scenario produces the highest global GDP exposure for 2046–2065, with a 5.56‐fold increase relative to the base period, of up to (2.29 ± 0.20) × 10¹⁵ purchasing power parity $‐days. Socioeconomic effects are the primary contributor to the exposure changes at the global and continental scales. Population and GDP effects account for 64–77% and 78–91% of the total exposure change, respectively. The inequality of exposure indicates that more attention should be given to Asia and Africa due to their rapid increases in population and GDP. However, due to their dense populations and high GDPs, European countries, that is, Luxembourg, Belgium, and the Netherlands, should also commit to effective adaptation measures.

Understanding the role of reservoirs in the terrestrial water cycle is critical to support the sustainable management of water resources especially for China where reservoirs have been extensively built nationwide. However, this has been a scientific challenge due to the limited availability of continuous, long‐term reservoir operation records at large scales, and a process‐based modeling tool to accurately depict reservoirs as part of the terrestrial water cycle is still lacking. Here, we develop a continental‐scale land surface‐hydrologic model over the mainland China by explicitly representing 3,547 reservoirs in the model with a calibration‐free conceptual operation scheme for ungauged reservoirs and a hydrodynamically based two‐way coupled scheme. The model is spatially calibrated and then extensively validated against streamflow observations, reservoir storage observations and GRACE‐based terrestrial water storage anomalies. A 30‐year simulation is then performed to quantify the seasonal dynamics of China’s reservoir water storage (RWS) and its role in China's terrestrial water storage (TWS) over recent decades. We estimate that, over a seasonal cycle, China's RWS variation is 15%, 16%, and 25% of TWS variation during 1981–1990, 1991–2000, and 2001–2010, respectively, and one‐fifth of China’s reservoir capacity are effectively used annually. In most regions, reservoirs play a growing role in modulating the water cycle over time. Despite that, an estimated 80 million people have faced increasing water resources challenges in the past decades due to the significantly weakened reservoir regulation of the water cycle. Our approaches and findings could help the government better address the water security challenges under environmental changes.

Ecosystems in alpine mountainous regions are vulnerable and easily disturbed by global environmental change. Alpine swamp meadow, a unique grassland type in the eastern Tibetan Plateau that provides important ecosystem services to the upstream and downstream regions of international rivers of Asia and other parts of the world, is undergoing severe degradation, which can dramatically alter soil hydraulic properties and water cycling processes. However, the effects of alpine swamp meadow degradation on soil hydraulic properties and the corresponding influencing mechanisms are still poorly understood. In this study, soil moisture content (SMC), field capacity (FC) and saturated hydraulic conductivity (K_s) together with several basic soil properties under lightly degraded (LD), moderately degraded (MD) and severely degraded (SD) alpine swamp meadow were investigated; the variations in SMC, FC and K_s with alpine swamp meadow degradation and their dominant influencing factors were analysed. The results showed that SMC and FC decreased consistently from LD to SD, while K_s decreased from LD to MD and then increased from MD to SD, following the order of LD > SD > MD. Significant differences in soil hydraulic properties between degradation degrees were found in the upper soil layers (0–20 cm), indicating that the influences of degradation were most pronounced in the topsoils. FC was positively correlated with capillary porosity, water-stable aggregates, soil organic carbon, and silt and clay content; K_s was positively correlated with non-capillary porosity (NCP). Relative to other soil properties, soil porosity is the dominant factor influencing FC and K_s. Capillary porosity explained 91.1 % of total variance in FC, and NCP explained 97.3 % of total variance in K_s. The combined effect of disappearing root activities and increasing sand content was responsible for the inconsistent patterns of NCP and K_s. Our findings suggest that alpine swamp meadow degradation would inevitably lead to reduced water holding capacity and rainfall infiltration. This study provides a more comprehensive understanding of the soil hydrological effects of vegetation degradation. Further hydrological modelling studies in the Tibetan Plateau and similar regions are recommended to understand the effects of degraded alpine swamp meadows on soil hydraulic properties.