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Human-induced climate change impacts the hydrological cycle and thus the availability of water resources. However, previous assessments of observed warming-induced changes in dryness have not excluded natural climate variability and show conflicting results due to uncertainties in our understanding of the response of evapotranspiration. Here we employ data-driven and land-surface models to produce observation-based global reconstructions of water availability from 1902 to 2014, a period during which our planet experienced a global warming of approximately 1 °C. Our analysis reveals a spatial pattern of changes in average water availability during the driest month of the year over the past three decades compared with the first half of the twentieth century, with some regions experiencing increased and some decreased water availability. The global pattern is consistent with climate model estimates that account for anthropogenic effects, and it is not expected from natural climate variability, supporting human-induced climate change as the cause. There is regional evidence of drier dry seasons predominantly in extratropical latitudes and including Europe, western North America, northern Asia, southern South America, Australia and eastern Africa. We also find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.Regional changes in dry-season water availability over recent decades can be attributed to human-induced climate change, according to analyses of global reconstructions.

Groundwater provides critical freshwater supply, particularly in dry regions where surface water availability is limited. Climate change impacts on GWS (groundwater storage) could affect the sustainability of freshwater resources. Here, we used a fully-coupled climate model to investigate GWS changes over seven critical aquifers identified as significantly distressed by satellite observations. We assessed the potential climate-driven impacts on GWS changes throughout the 21 st century under the business-as-usual scenario (RCP8.5). Results show that the climate-driven impacts on GWS changes do not necessarily reflect the long-term trend in precipitation; instead, the trend may result from enhancement of evapotranspiration, and reduction in snowmelt, which collectively lead to divergent responses of GWS changes across different aquifers. Finally, we compare the climate-driven and anthropogenic pumping impacts. The reduction in GWS is mainly due to the combined impacts of over-pumping and climate effects; however, the contribution of pumping could easily far exceed the natural replenishment. Climate change may impact groundwater storage and thus the availability of freshwater resources. Here the authors use climate models to examine seven aquifers and find that storage changes are primarily the result of enhancement of evapotranspiration, reduction in snowmelt, and over-pumping rather than long-term precipitation changes.

Trade-offs between tree planting programs and wetland conservation are unclear. Here, we employ satellite-derived inundation data and a process-based land surface model (ORCHIDEE-Hillslope) to investigate the impacts of tree planting on wetland dynamics in China for 2000–2016 and the potential impacts of near-term tree planting activities for 2017–2035. We find that 160,000–190,000 km 2 (25.3–25.6%) of historical tree planting over wetland grid cells has resulted in 1,300–1,500 km 2 (0.3–0.4%) net wetland loss. Compared to moist southern regions, the dry northern and western regions show a much higher sensitivity of wetland reduction to tree planting. With most protected wetlands in China located in the drier northern and western basins, continuing tree planting scenarios are projected to lead to a > 10% wetland loss relative to 2000 across 4–8 out of 38 national wetland nature reserves. Our work shows how spatial optimization can help the balance of tree planting and wetland conservation targets. Afforestation and reforestation programs aimed at enhancing carbon sequestration may have unintended effects on non-forest ecosystems and biodiversity. Here the authors use remote sensing and land surface modelling to quantify trade-offs between tree planting and wetland conservation in China

Human impacts on the terrestrial water cycle have the potential to influence hazards such as flooding and drought, so understanding the extent of our influence is an important research goal. A study utilizing estimates of evapotranspiration for different types of land cover and a database of changes in use now shows that the extent of land-cover change caused by people is already an important factor affecting the terrestrial water cycle. Floods and droughts cause perhaps the most human suffering of all climate-related events; a major goal is to understand how humans alter the incidence and severity of these events by changing the terrestrial water cycle. Here we use over 1,500 estimates of annual evapotranspiration and a database of global land-cover change 1 to project alterations of global scale terrestrial evapotranspiration (TET) from current anthropogenic land-cover change. Geographic modelling reveals that land-cover change reduces annual TET by approximately 3,500 km 3  yr −1 (5%) and that the largest changes in evapotranspiration are associated with wetlands and reservoirs. Land surface model simulations support these evapotranspiration changes, and project increased runoff (7.6%) as a result of land-cover changes. Next we create a synthesis of the major anthropogenic impacts on annual runoff and find that the net result is an increase in annual runoff, although this is uncertain. The results demonstrate that land-cover change alters annual global runoff to a similar or greater extent than other major drivers, affirming the important role of land-cover change in the Earth System 2 , 3 , 4 . Last, we identify which major anthropogenic drivers to runoff change have a mean global change statistic that masks large regional increases and decreases: land-cover change, changes in meteorological forcing, and direct CO 2 effects on plants.

Many maps of open water and wetlands have been developed based on three main methods: (i) compiling national and regional wetland surveys, (ii) identifying inundated areas via satellite imagery and (iii) delineating wetlands as shallow water table areas based on groundwater modeling. However, the resulting global wetland extents vary from 3 % to 21 % of the land surface area because of inconsistencies in wetland definitions and limitations in observation or modeling systems. To reconcile these differences, we propose composite wetland (CW) maps, combining two classes of wetlands: (1) regularly flooded wetlands (RFWs) obtained by overlapping selected open-water and inundation datasets; and (2) groundwater-driven wetlands (GDWs) derived from groundwater modeling (either direct or simplified using several variants of the topographic index). Wetlands are statically defined as areas with persistent near-saturated soil surfaces because of regular flooding or shallow groundwater, disregarding most human alterations (potential wetlands). Seven CW maps were generated at 15 arcsec resolution (ca. 500 m at the Equator) using geographic information system (GIS) tools and by combining one RFW and different GDW maps. To validate this approach, these CW maps were compared with existing wetland datasets at the global and regional scales. The spatial patterns were decently captured, but the wetland extents were difficult to assess compared to the dispersion of the validation datasets. Compared with the only regional dataset encompassing both GDWs and RFWs, over France, the CW maps performed well and better than all other considered global wetland datasets. Two CW maps, showing the best overall match with the available evaluation datasets, were eventually selected. These maps provided global wetland extents of 27.5 and 29 million km2, i.e., 21.1 % and 21.6 % of the global land area, which are among the highest values in the literature and are in line with recent estimates also recognizing the contribution of GDWs. This wetland class covers 15 % of the global land area compared with 9.7 % for RFW (with an overlap of ca. 3.4 %), including wetlands under canopy and/or cloud cover, leading to high wetland densities in the tropics and small scattered wetlands that cover less than 5 % of land but are highly important for hydrological and ecological functioning in temperate to arid areas. By distinguishing the RFWs and GDWs based globally on uniform principles, the proposed dataset might be useful for large-scale land surface modeling (hydrological, ecological and biogeochemical modeling) and environmental planning. The dataset consisting of the two selected CW maps and the contributing GDW and RFW maps is available from PANGAEA at https://doi.org/10.1594/PANGAEA.892657 (Tootchi et al., 2018).

Dry season rainfall in the Amazon is projected by constraining global climate models with simple models calibrated to observations. The results indicate a longer dry season over a larger area and a strengthening of the monsoon season this century. The vulnerability of Amazonian rainforest, and the ecological services it provides, depends on an adequate supply of dry-season water, either as precipitation or stored soil moisture. How the rain-bearing South American monsoon will evolve across the twenty-first century is thus a question of major interest. Extensive savanization, with its loss of forest carbon stock and uptake capacity, is an extreme although very uncertain scenario 1 , 2 , 3 , 4 , 5 , 6 . We show that the contrasting rainfall projections simulated for Amazonia by 36 global climate models (GCMs) can be reproduced with empirical precipitation models, calibrated with historical GCM data as functions of the large-scale circulation. A set of these simple models was therefore calibrated with observations and used to constrain the GCM simulations. In agreement with the current hydrologic trends 7 , 8 , the resulting projection towards the end of the twenty-first century is for a strengthening of the monsoon seasonal cycle, and a dry-season lengthening in southern Amazonia. With this approach, the increase in the area subjected to lengthy—savannah-prone—dry seasons is substantially larger than the GCM-simulated one. Our results confirm the dominant picture shown by the state-of-the-art GCMs, but suggest that the ‘model democracy’ view of these impacts can be significantly underestimated.

Understanding river flow intermittency remains a major challenge in data‐scarce regions such as Africa. This study presents the first high‐resolution, four‐class intermittency map of African rivers using a sequential modeling approach based on Random Forest. A binary model (BC‐UNS) distinguishes perennial from non‐perennial reaches across 15.5 million river reaches, while a multiclass model (MC‐WOR) further categorizes non‐perennial reaches as weakly intermittent, highly intermittent, or ephemeral. A reach was considered non‐perennial when the long‐term mean annual number of zero‐flow months exceeded one; otherwise, it was considered perennial. Models were trained on data from 1,269 gauging stations. BC‐UNS demonstrated substantial performance, correctly identifying 92% of perennial stations and 71% of non‐perennial stations. MC‐WOR achieved fair performance, correctly identifying 73% of weakly intermittent, 45% of highly intermittent, and 58% of ephemeral stations. Climate variables, particularly the aridity index, emerged as the dominant controls of intermittency, with catchment area, potential evapotranspiration, and permeability also playing important roles. Human influences, represented by indices such as the Human Footprint Index and dam storage, further affected intermittency, especially among non‐perennial subclasses. Results indicate that 69% of Africa's river length is non‐perennial, comprising 7% weakly intermittent, 16% highly intermittent, and 46% ephemeral reaches. Differences in definitions between this study and previous global assessments limit direct comparisons, although all studies consistently indicate that most African rivers are non‐perennial. This study advances previous global efforts by producing a fine‐scale, reach‐level classification map that distinguishes four flow intermittency classes, then offering actionable insights for water resource planning and ecosystem conservation.

Aridity is expected to increase globally in a warmer world. Research now suggests that this is substantially amplified by land–atmosphere feedbacks associated with the land surface’s response to climate and plant responses to increased atmospheric CO 2 . The response of the terrestrial water cycle to global warming is central to issues including water resources, agriculture and ecosystem health. Recent studies 1 , 2 , 3 , 4 , 5 , 6 indicate that aridity, defined in terms of atmospheric supply (precipitation, P ) and demand (potential evapotranspiration, E p ) of water at the land surface, will increase globally in a warmer world. Recently proposed mechanisms for this response emphasize the driving role of oceanic warming and associated atmospheric processes 4 , 5 . Here we show that the aridity response is substantially amplified by land–atmosphere feedbacks associated with the land surface’s response to climate and CO 2 change. Using simulations from the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment 7 , 8 , 9 , we show that global aridity is enhanced by the feedbacks of projected soil moisture decrease on land surface temperature, relative humidity and precipitation. The physiological impact of increasing atmospheric CO 2 on vegetation exerts a qualitatively similar control on aridity. We reconcile these findings with previously proposed mechanisms 5 by showing that the moist enthalpy change over land is unaffected by the land hydrological response. Thus, although oceanic warming constrains the combined moisture and temperature changes over land, land hydrology modulates the partitioning of this enthalpy increase towards increased aridity.

Accurate groundwater representation in land surface models (LSMs) is vital for water and energy cycle studies, water resource assessments, and climate projections. Yet, many LSMs do not consider key processes including lateral groundwater flow and aquifer pumping, especially at the global scale. This study simulates these processes using an enhanced version of the Community Land Model (CLM5) and evaluates their roles at three spatial resolutions (0.5°, 0.25°, 0.1°). Results show that lateral flow strongly modulates water table depth and capillary rise at all resolutions. The magnitude of mean lateral flow increases from 25 mm/year at 0.5° to 36 mm/year at 0.25°, and 52 mm/year at 0.1° resolution, with pumping inducing lateral flow even at 0.5° (∼50 km), a typical grid size in global LSMs. Further, lateral flow alters runoff in regions with high recharge and shallow water table (e.g., eastern North America and Amazon basin), and soil moisture and ET in regions with comparatively low recharge and deeper water table (e.g., western North America, central Asia, and Australia) through enhanced capillary rise. Runoff alteration by lateral flow increases substantially with resolution, from a maximum of 15 mm/month at 0.5° to 20 mm/month and 25 mm/month at 0.25° and 0.1°, respectively; the impact of resolution on soil moisture and ET is less pronounced. While the model does not fully capture deeper water tables—warranting further enhancements—it provides valuable insights on how lateral groundwater flow impacts land surface processes, highlighting the importance of lateral groundwater flow and pumping in global LSMs. Key Points Lateral groundwater flow increases substantially with spatial resolution and modulates water table in global land surface modeling Pumping‐induced lateral flow is significant even at coarse resolution (∼50 km) and alters hydrologic dynamics Lateral groundwater flow affects total runoff, soil moisture, and ET, but impacts of resolution are more pronounced for total runoff

Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture–atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature–precipitation correlations using simulations from the Global Land–Atmosphere Coupling Experiment–phase 5 of the Coupled Model Intercomparison Project (GLACE-CMIP5) multimodel experiment. The analyses are based on simulations with five climate models, which were integrated with prescribed (noninteractive) and with interactive soil moisture over the period 1950–2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture–atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature–precipitation correlation. On longer time scales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near-surface climate: in all models, in the regions of strongest temperature–precipitation anticorrelation on interannual time scales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil moisture–atmosphere interactions.