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Learn how water and wind shape the landscape of Earth.

Exploitation of groundwater has greatly increased since the 1970s to meet the increased water demand due to fast economic development in China. Correspondingly, the regional groundwater level has declined substantially in many areas of China. Water sources are scarce in northern and northwestern China, and the anthropogenic pollution of groundwater has worsened the situation. Groundwater containing high concentrations of geogenic arsenic, fluoride, iodine, and salinity is widely distributed across China, which has negatively affected safe supply of water for drinking and other purposes. In addition to anthropogenic contamination, the interactions between surface water and groundwater, including seawater intrusion, have caused deterioration of groundwater quality. The ecosystem and geo-environment have been severely affected by the depletion of groundwater resources. Land subsidence due to excessive groundwater withdrawal has been observed in more than 50 cities in China, with a maximum accumulated subsidence of 2–3 m. Groundwater-dependent ecosystems are being degraded due to changes in the water table or poor groundwater quality. This paper reviews these changes in China, which have occurred under the impact of rapid economic development. The effects of economic growth on groundwater systems should be monitored, understood and predicted to better protect and manage groundwater resources for the future.

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The exchange between surface water (SW) and groundwater (GW) influences water availability and ecosystems in stream networks. Assessing GW‐SW interactions can be based on various methods at different scales, such as point scale (e.g., local head differences, temperature profiles), reach scale (e.g., environmental tracers, water mass balance), and catchment scale (topographical‐driven groundwater flow), which all have distinct advantages and limitations. In this study, we combined the analysis of local hydraulic head differences with regional topographical‐driven groundwater flow to robustly reveal gaining and losing stream patterns in two study regions in Central Germany (Bode catchment and Free State of Thuringia). To evaluate local hydraulic gradients, we developed a method for estimating surface water levels across stream networks by modifying surface elevations from a coarse digital elevation model (25 m) and compared these to measured groundwater levels. Our results reveal prevalent occurrences of losing streams. Numerous stream locations are characterized by mismatching classifications from the two methods providing additional insights for understanding water cycles. The most notable discrepancy is the classification as losing based on head differences and gaining from topographic analyses accounting for 37% and 47% of the stream locations in Thuringia and in Bode catchment. This mismatch indicates anthropogenically lowered groundwater levels, typically occurring in urban and mining areas in the study areas. Our approach, combining local hydraulic head analysis and topographical‐driven groundwater flow enhances the understanding of gaining and losing stream patterns at catchment scale, revealing widespread occurrences of losing streams and highlighting the significance of anthropogenic influences on water cycles. Key Points A method was developed to estimate surface water levels along the stream network by correcting a digital elevation model with 25 m resolution Combining head gradients and topographic analysis reveals catchment‐scale patterns and uncertainties in stream gains and losses About 42% of streams indicate locally losing conditions despite being in a topographical discharge zone

Evaporation is a major pathway of surface water loss in wetlands, yet its influence on subsurface feedbacks remains poorly understood. Using an integrated surface–subsurface hydrologic and solute transport model, we show that evaporation can induce hysteresis between evaporative demand and the upwelling of groundwater and solutes, with the strength of this feedback governed by sediment permeability and shaped by site‐specific hydrologic and topographic conditions. Under low‐permeability (<1 × 10−12 m2) conditions, evaporation leads to lagged and prolonged groundwater and tracer upwelling, whereas high‐permeability sediments respond more directly to evaporative forcing. Ponded water depth, land surface slope, and evaporation rate regulate the magnitude of upwelling fluxes, while rainfall and fluctuating groundwater levels can reverse flow direction. These findings highlight evaporation as an indirect yet critical driver of wetland water and solute exchange, with important implications for biogeochemical cycling and the hydrologic resilience of wetland ecosystems under a changing climate.

Vegetation‐related processes, such as evapotranspiration (ET), irrigation water withdrawal, and groundwater recharge, are influencing surface water (SW)—groundwater (GW) interaction in irrigation districts. Meanwhile, conventional numerical models of SW‐GW interaction are not developed based on satellite‐based observations of vegetation indices. In this paper, we propose a novel methodology for multivariate assimilation of Sentinel‐based leaf area index (LAI) as well as in‐situ records of streamflow. Moreover, the GW model is initially calibrated based on water table observations. These observations are assimilated into the SWAT‐MODFLOW model to accurately analyze the advantage of considering high‐resolution LAI data for SW‐GW modeling. We develop a data assimilation (DA) framework for SWAT‐MODFLOW model using the particle filter based on the sampling importance resampling (PF‐SIR). Parameters of MODFLOW are calibrated using the parameter estimation (PEST) algorithm and based on in‐situ observation of the GW table. The methodology is implemented over the Mahabad Irrigation Plain, located in the Urmia Lake Basin in Iran. Some DA scenarios are closely examined, including univariate LAI assimilation (L‐DA), univariate streamflow assimilation (S‐DA), and multivariate streamflow‐LAI assimilation (SL‐DA). Results show that the SL‐DA scenario results in the best estimations of streamflow, LAI, and GW level, compared to other DA scenarios. The streamflow DA does not improve the accuracy of LAI estimation, while the LAI assimilation scenario results in significant improvements in streamflow simulation, where, compared to the open loop run, the (absolute) bias decreases from 75% to 6%. Moreover, S‐DA, compared to L‐DA, underestimates irrigation water use and demand as well as potential and actual crop yield. Key Points Using source code modification, SWAT‐MODFLOW is connected to sequential DA Multivariate assimilation of streamflow, GW‐level and leaf area index (LAI) shows the best results Streamflow data assimilation does not improve LAI simulation, while LAI data assimilation improves streamflow simulation

The Central Valley in California (USA) covers about 52,000 km 2 and is one of the most productive agricultural regions in the world. This agriculture relies heavily on surface-water diversions and groundwater pumpage to meet irrigation water demand. Because the valley is semi-arid and surface-water availability varies substantially, agriculture relies heavily on local groundwater. In the southern two thirds of the valley, the San Joaquin Valley, historic and recent groundwater pumpage has caused significant and extensive drawdowns, aquifer-system compaction and subsidence. During recent drought periods (2007–2009 and 2012-present), groundwater pumping has increased owing to a combination of decreased surface-water availability and land-use changes. Declining groundwater levels, approaching or surpassing historical low levels, have caused accelerated and renewed compaction and subsidence that likely is mostly permanent. The subsidence has caused operational, maintenance, and construction-design problems for water-delivery and flood-control canals in the San Joaquin Valley. Planning for the effects of continued subsidence in the area is important for water agencies. As land use, managed aquifer recharge, and surface-water availability continue to vary, long-term groundwater-level and subsidence monitoring and modelling are critical to understanding the dynamics of historical and continued groundwater use resulting in additional water-level and groundwater storage declines, and associated subsidence. Modeling tools such as the Central Valley Hydrologic Model, can be used in the evaluation of management strategies to mitigate adverse impacts due to subsidence while also optimizing water availability. This knowledge will be critical for successful implementation of recent legislation aimed toward sustainable groundwater use.

Shallow lakes are important ecosystems highly susceptible to water‐level fluctuations and desiccation caused by climate cycles and anthropogenic pressures. To better predict and manage the impacts of disturbance we examined the natural variability over a 20‐year period, that spans the range of long‐term (decadal) weather cycles, and the controls on water‐level deviation (WLD) of 26 shallow lakes that include all configurations of lake types and glacial landscapes typical in the Boreal Plains (BP) of Canada. Water budgets and hydrochemical analyses show that dominant lake water‐budget components vary spatially and temporally with different geological settings and land covers that influence the scale and magnitude of lake‐groundwater connectivity and surface‐water inflow. However, over decadal weather cycles similar ranges in WLD were observed across all glacial geologies and shallow lake types. Lake geometry and evaporation interacted with lake‐catchment characteristics to further impact the dynamics and memory of water levels to interannual and decadal weather patterns. In all lake‐catchment types, lake bathymetry and outflow sill elevation determined overall storage which controls maximum water level elevation during wet years and extent of desiccation during drought years. This research demonstrates that in sub‐humid glaciated continental landscapes, such as the BP, lake management strategies founded on lake permanence and fluctuation magnitudes are of limited value. Rather, focus should be placed on documenting the long‐term WLD and considering the interaction of landscape characteristics and internal lake mechanisms that enable different lake types in such heterogeneous landscapes to recover and persist over decadal meteorological cycles.

Current integrated modeling frameworks for simulating nutrient sources and dynamics are inadequate for large regional watersheds dominated by groundwater‐surface water interactions due to their simplistic representations of groundwater. In this study, we develop a coupled model that integrates comprehensive surface water, 3‐D groundwater, soil erosion, and nutrient processes. The model is intended to enhance the understanding of nutrient dynamics and sources in the Pearl River Basin (PRB). The model exhibits satisfactory performance in simulating streamflow and sediment transport patterns, capturing essential seasonal variations in water quality indicators. Hydrological budget assessments from 2002 to 2020 in the PRB reveal that 54% of precipitation drains into the South China Sea as surface water, while groundwater discharge as baseflow accounts for 18% of the streamflow. The nutrient budget for the PRB indicates that non‐point sources are the dominant contributors to both nitrogen (N) and phosphorus (P), ranging between 64% and 90%. Improved sewage collection and treatment have reduced point source nutrient contributions over the evaluation period. Groundwater remains a significant and consistent source of N, contributing between 11% and 19%. Natural disturbances and fertilization have led to an upward trend in river N inputs, while afforestation and sewage reduction efforts have resulted in a downward trend in river P inputs. Increased fertilization emerges as a central concern for the PRB, suggesting cost‐effective mitigation of fertilizer usage a pragmatic solution. The coupled simulation model developed in this study offers a novel systems approach for basin‐wide nutrient analysis and pollution control strategies, considering both natural and human‐induced disturbances. Plain Language Summary Water nutrient pollution is a global problem caused by both natural and human factors. To better understand nutrient pollution, a new model has been developed that combines water flow, soil erosion, and nutrient transport to simulate water and nutrient cycling on a regional scale. This model can assist in the management of water pollution by providing a better understanding of nutrient sources and quantifying the contribution of climate change and different human activities. Tested in the Pearl River Basin from 2002 to 2020, the model accurately simulated water flow and nutrient patterns. A key finding is that groundwater supplies 18% of water and 14% of nitrogen inputs of the Pearl River. The main sources of pollutants are non‐point agricultural sources, primarily from fertilization. Climate variability leads to more runoff and nutrient input, while improved sewage treatment and afforestation have reduced nutrient pollution. The model allows the exploration of different influencing factors to better control nutrient pollution. Understanding how human activities impact different regions is crucial for effective nutrient pollution management. Key Points A novel system model integrates water, soil, and nutrient dynamics for effective regional watershed management Non‐point source nutrients are the major contributors of nitrogen and phosphorus levels in the Pearl River Basin, accounting for 64%–90% The rise in fertilization poses a growing concern for the Pearl River Basin, underscoring the need for cost‐effective mitigation strategies

The inadequate availability of clean water presents systemic risks to human health, food production, energy generation and ecosystem functioning. Here we evaluate population exposure to current and future water scarcity (both excluding and including water quality) using a coupled global hydrological and surface water quality model. We find that 55% of the global population are currently exposed to clean water scarcity at least one month per year, compared with 47% considering water quantity aspects only. Exposure to clean water scarcity at least one month per year increases to 56–66% by the end of the century. Increases in future exposure are typically largest in developing countries—particularly in sub-Saharan Africa—driven by a combination of water quantity and quality aspects. Strong reductions in both anthropogenic water use and pollution are therefore necessary to minimize the impact of future clean water scarcity on humans and the environment. Polluted water contributes to water scarcity. Here the authors project water demands, availability and quality under climate and socio-economic changes and show that 56–66% of the global population will be exposed to clean water scarcity at the end of the century.