ABSTRACT Karst regions, where extensive fracture networks accelerate water and nitrogen losses, face severe challenges to ecological restoration, yet how fracture‐filling particle size regulates coupled water–nitrogen dynamics through nonlinear threshold behaviour remains poorly understood. Here, we conducted field soil column experiments under natural rainfall using three fracture‐filling particle size gradations (C0: 3–5 mm; C1: 6–13 mm; C2: 10–30 mm), coupled with PRA and RSS threshold identification. Medium‐sized fractures (C1) achieved the most favourable water retention through a hydraulic conductivity–capillary retention balance: although surface runoff increased relative to C0, the combined runoff and deep leakage loss was lowest in C1 (14.49 mm) versus C0 (16.45 mm) and C2 (16.43 mm). Runoff initiation thresholds consistently ranked C0 > C1 > C2 under both precipitation (124.68, 113.60, 103.27 mm) and antecedent soil moisture (14.79, 10.71, 8.70 mm), with precipitation as the stronger predictor, indicating that coarser fillings lower the activation threshold for preferential flow by enhancing network connectivity. A nitrogen transformation paradox emerged in C1: despite the highest leachate nitrate concentrations (18.34 μg mL −1 ), total nitrogen leaching was ~30% lower than C0, reflecting coupled nitrification–denitrification within its intermediate pore architecture. Runoff thresholds acted as switches for nitrogen loss: leaching increased stepwise only after threshold exceedance, creating nitrogen export hot moments that alternated with safe operating spaces wherein nitrification proceeded without connected leaching pathways. These findings establish fracture‐filling particle size as a structural control valve governing water–nitrogen dynamics through threshold‐mediated mechanisms, providing a mechanistic foundation for precision water and nitrogen management in karst regions.
ABSTRACT This study investigates long‐term streamflow changes in the Gediz River Basin, a climatically Mediterranean catchment in western Turkey, by employing a Budyko‐based water balance framework. Using multi‐decadal observations from 18 streamflow gauging stations and four meteorological stations, we analyse basin behaviour through (i) Budyko and Fu curves fitting, (ii) detection of regime shifts using time‐series segmentation and (iii) attribution of streamflow changes via both decomposition and sensitivity methods. A common hydrological regime shift was detected in 1984, after which streamflow consistently declines across most streamflow gauges. Post‐change periods exhibit elevated Fu parameters and increased evaporation ratios, indicating reduced runoff and intensified aridity. A high majority of gauging stations align closely with Budyko expectations, while deviations—particularly in high‐altitude headwaters—are attributed to karst geomorphology, snowmelt processes and data limitations. Attribution analysis reveals that climate variability, especially declining precipitation, accounts for 50%–75% of the total streamflow change, though local anthropogenic drivers also contribute significantly in specific sub‐basins. These findings mirror regional hydroclimatic patterns across the Mediterranean Basin and reinforce the Gediz River Basin's sensitivity to both climate stress and water management practices. The well‐established knowledge that humans are the main factor creating the streamflow decrease has been softened with our data‐limited results showing that the climate‐driven change in Western part of Turkey could be higher than the human effect. The study is a detailed basin‐scale understanding, rather than implying a methodological breakthrough or a definitive proof of persistent Budyko conformance. It emphasises that the hydrological character of Gediz River Basin provides an opportunity to develop Budyko‐based practical methodologies for the river basin‐scale water resources planning and management strategies that could potentially be transferable to data‐scarce, semi‐arid regions facing escalating water insecurity.
ABSTRACT Drought propagation across hydrological compartments is not a synchronous process, yet stage‐specific differences between the Stage 1 (meteorological‐to‐soil link) and the Stage 2 (soil‐to‐groundwater link) remain insufficiently understood. Using China as a hydroclimatically diverse test domain, this study established a two‐stage drought propagation framework linking SPI, SSI and GWSA‐DSI and combined propagation‐time analysis with AC1 (first‐order autocorrelation) and partial‐correlation diagnostics. Results showed that drought propagated rapidly from meteorological to soil conditions, with lag times of 1.2–4.1 months, whereas propagation from soil drought to groundwater drought was consistently slower, with lag times of 2.6–5.9 months. The slower Stage 2 was characterized by generally lower short‐term temporal persistence and weaker conditional associations with concurrent hydroclimatic forcing. Antecedent soil moisture showed a strong and spatially consistent association with current SSI, whereas its relationship with GWSA‐DSI was substantially weaker and regionally heterogeneous. These findings show that drought propagation is stage‐dependent across hydrological compartments, with deeper storage responding more slowly. This process‐based asymmetry implies that rapid changes in near‐surface indicators do not necessarily indicate equally rapid development or recovery of deeper hydrological drought.
ABSTRACT Climate variability and agricultural water use jointly regulate the transfer of surface inputs through vadose zones towards groundwater, yet this vertical pathway remains difficult to quantify in thick, heterogeneous profiles. We developed a physics‐informed neural network (PINN) for the pressure‐head form of the Richards equation with van Genuchten hydraulic relationships and evaluated it against an analytical benchmark and observations from a 45.2 m multilayer agricultural profile at the Luancheng Experimental Station. Across six monitoring depths, the PINN achieved a mean Nash–Sutcliffe efficiency of 0.916 ± 0.050, compared with 0.853 ± 0.109 for a finite‐difference method. The field simulation reproduced rapid near‐surface wetting–drying, delayed and attenuated responses at depth, and the partitioning of 887.5 mm of precipitation and irrigation among evapotranspiration, storage change and 247.32 mm of deep percolation below the 0–2 m root zone. Following a local hydraulic‐parameter update, the warm‐started PINN re‐converged with a mean relative error of 2.43% against paired pressure‐head observations. Although conditional on fixed hydraulic parameters, deterministic inputs and a one‐dimensional structure, the framework links climate‐driven and human‐managed surface forcing with vadose‐zone buffering and potential groundwater recharge. It also clarifies why deep percolation below the root zone should not be equated with contemporaneous recharge at a deep water table. These findings support process‐based interpretation of groundwater–surface water interactions and agricultural water management in irrigated, water‐limited regions.
ABSTRACT Mountain forests in arid regions are under long‐term water limitation, and different soil genetic horizons have distinct differences in water storage and root accessibility. Therefore, investigating the relationship between plant water uptake patterns and soil genetic horizons in arid mountain forests can help distinguish the hydrological functions of different soil horizons. In this study, we investigated Picea schrenkiana forests in the Tianshan Mountains at three elevations: 2200, 1800 and 1450 m. During the growing seasons over two consecutive years, soil water from the humus, eluvial and illuvial horizons, together with plant xylem water, was collected and the MixSIAR model was used to quantify the contributions of different soil genetic horizons to water uptake by P. schrenkiana . The results showed that during a wetter year and the early growing season, trees mainly used water from the humus horizon, whereas during a drier year or the late growing season, they increased their uptake of water from the eluvial and illuvial horizons. Along the elevational gradient, P. schrenkiana at 2200 and 1800 m mainly used water from the humus horizon. However, at 1450 m, influenced by root distribution and hydraulic connectivity, P. schrenkiana mainly used water from the eluvial horizon even when the humus horizon had relatively high soil water content. This study indicates that the humus horizon is an important water source for P. schrenkiana , and its role in maintaining forest hydrological health may exceed that of the eluvial and illuvial horizons. Higher soil water content does not necessarily indicate a higher contribution to plant water uptake, as plant water uptake is also related to root distribution, water availability and atmospheric drought stress. This study clarifies the important ecohydrological role of the humus horizon in arid mountain forests and helps improve our understanding of the mechanisms underlying tree water uptake in these ecosystems.
ABSTRACT High‐alpine, snow‐dominated karst catchments are among the most challenging environments for hydrological modelling due to complex topography, heterogeneous snow distribution, and limited discharge observations. The representation of snow processes has significant implications for simulated runoff generation and water balance partitioning, yet direct comparisons in karst settings remain scarce. Two model configurations are compared for the Partnach Spring Catchment (PSC), a single‐outlet karst system at Mt. Zugspitze (Northern European Alps, Germany), over the hydrological years 2015–2025. A fully conceptual CemaNeige–GR4H setup is evaluated against a hybrid configuration combining Alpine3D with GR4H routing. Alpine3D snow simulations are independently validated using point‐scale snow depth and snow water equivalent (SWE) measurements, as well as Sentinel‐2‐derived snow‐covered area (87 scenes). Both configurations achieve strong discharge performance (calibration Kling‐Gupta Efficiency (KGE): 0.92 ± 0.01 vs. 0.91 ± 0.01; validation KGE: 0.82 ± 0.07 vs. 0.87 ± 0.03), though 41.3% of discharge observations are missing, concentrated in winter months, limiting seasonal evaluation. The hybrid configuration shows improved temporal transferability despite requiring fewer calibration parameters (2 vs. 5). Annual water balances align within 0.16%, yet the conceptual configuration compensates through up to 78% greater routing storage capacity, masking structural differences in internal process representation. These results show that lumped routing structures can reproduce discharge dynamics in complex, snow‐dominated karst systems regardless of snow and boundary layer model complexity. However, the hybrid approach provides clear advantages for representing spatial snow dynamics and for gaining process‐level understanding of high‐alpine hydrology.
ABSTRACT Soil hydraulic properties govern the movement and storage of water in soils and are essential inputs for hydrological and land surface models, influencing water‐holding capacity, matter and energy transport, erosion susceptibility and plant water availability. However, direct measurement of these properties is labour‐intensive and thus often limited in spatial coverage. Therefore, pedotransfer functions (PTFs) are widely used to estimate soil hydraulic properties from readily available soil characteristics. We present a spatial dataset of soil hydraulic properties for Europe at 0–20 cm depth, developed using harmonised soil property maps derived from the LUCAS dataset and the improved PTFs (EUPTFv2) proposed by Szabó et al., which are developed on the European Hydropedological Data Inventory. The derived dataset includes water content at saturation, field capacity (at −10 and −33 kPa), wilting point (−1500 kPa), saturated hydraulic conductivity and their associated uncertainty maps. In addition, we derived available water capacity and air capacity (air‐filled porosity) from the predicted properties. The input datasets (LUCAS‐based soil maps) used in this study are derived from harmonised data in terms of measurement methods and spatial consistency. This is expected to improve the reliability of the resulting maps compared with existing products. The generated dataset is freely available and can therefore support a wide range of environmental and modelling applications.
ABSTRACT Multilayer aquifer systems beneath the urbanising plains of Latin America combine intensive abstraction with a strong geological inheritance, and at their coastal margins the origin of groundwater salinity is a recurrent, often unresolved question. The Gran La Plata multilayer system, Argentina, is characterised here from 111 water samples along an inland‐to‐coastal transect, through a process‐based reading of the major‐ion signatures. Cation exchange is the dominant control (negative Chloro‐Alkaline Indices in 93.2% of the 103 groundwater samples), coupled with carbonate dissolution, yielding a sodium–bicarbonate composition more advanced in the semi‐confined Puelche than in the phreatic Pampeano. Within each unit, the few coastal samples ( n = 4 in the Pampeano, n = 7 in the Puelche) are far more saline than inland ones (median EC roughly six times higher in the Puelche) while the exchange signature shows no matching shift, remaining a property of the unit, so salinity tracks geomorphic position, not flow domain. The coastal composition, contrasted against published isotopic and hydrodynamic evidence for the system, is most consistent with a relict palaeo‐marine origin rather than active seawater intrusion from the present‐day fresh estuary. These processes leave a predictable imprint on quality metrics: the sodium adsorption ratio rates nearly all samples suitable for irrigation, yet the sodium‐dominance and carbonate‐balance indices reveal a latent hazard, and an adjusted sodium ratio confirms its direction. The weighted drinking‐water quality index, in turn, tracks geogenic mineralisation rather than direct health risk. Correctly diagnosing the dominant process is therefore a prerequisite for interpreting any quality metric. This process‐first framework is transferable across the urbanising multilayer loessic aquifers of the Chaco‐Pampean plain.
ABSTRACT Water scarcity arises from the complex interplay between socioeconomic water demand and hydrological water availability, yet most global assessments represent these components separately or through one‐way coupling. This limits their ability to capture dynamic feedbacks between socioeconomic and hydrological processes. In this study, we developed a two‐way coupled socioeconomic–hydrological framework linking the Global Change Analysis Model and the Integrated Land Simulator. The framework dynamically exchanges land‐use and hydrological water‐availability information between the two models, enabling internally consistent representation of water demand and hydrological water availability through bidirectional feedbacks. We performed century‐scale simulations from 2020 to 2100 under SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5, with ILS at 0.5° resolution and Global Change Analysis Model operating over 32 geopolitical regions. Benchmark evaluation showed that the coupled configuration maintained statistically consistent performance in reproducing global water withdrawals and agricultural prices while modestly improving river‐discharge consistency. Using this framework, we decomposed future changes in water stress into socioeconomic and hydrological contributions. Across all four Shared Socioeconomic Pathways and Representative Concentration Pathways scenarios, roughly 80% of global geopolitical sub‐basin area exhibits increases in water stress. Areas where hydrological change is the dominant contribution account for about 20% under SSP1–2.6 and SSP2–4.5, rising to roughly 30% under SSP3–7.0 and SSP5–8.5. Regionally, Africa's future water‐stress intensification remains largely socioeconomic because of sustained demand growth, whereas Central Asia increasingly exhibits hydrologically driven water stress as water availability declines. These results demonstrate that future water scarcity cannot be explained by climate or socioeconomic demand alone, but is shaped by coupled socioeconomic–hydrological feedbacks. The proposed framework provides a foundation for dynamic, region‐specific water resources management under future Shared Socioeconomic Pathways and Representative Concentration Pathways scenarios.
ABSTRACT Streambed sediment transport, scour and deposition create spatiotemporal variability in streambed properties, contributing to uncertainty in hyporheic zone characterization. Accurate statistical characterization of this variability is further complicated by spatial dependence among measurements, which must be explicitly accounted for. To examine the potential effects of mobile sediments on streambed characterization, this study evaluated year‐to‐year changes in streambed properties including point measurements of streambed hydraulic conductivity ( K v ), hydraulic head gradients, seepage flux, and dissolved mercury ( Hg ) stream concentration and mass flux (of Hg into the stream) along a reach of East Fork Poplar Creek in Tennessee, USA, over three consecutive years under baseflow conditions. Anomalously high streamflow events were recorded prior to the 2019 measurements, contributing to year‐over‐year changes in streambed properties. Mean log‐transformed K v and inverse‐square‐root‐transformed Hg concentration differed significantly among years, with 2019 measurements having a lower mean than those from 2017 and 2018. A comparison between a one‐dimensional spatial mixed‐effects model and a model assuming independence showed that ignoring spatial autocorrelation led to downwardly biased standard error estimates and inflated statistical significance. Standard errors (SEs) from models that accommodate spatial autocorrelation can be substantially larger than those from models that assume independence. This study highlights both the temporal sensitivity of streambed properties to hydrological disturbance and the importance of using statistical frameworks that explicitly account for spatial dependence when evaluating changes in hyporheic exchange and contaminant transport.
ABSTRACT Assessing flood risk under climate change in data‐scarce tropical mountain watersheds requires transparent, reproducible frameworks that explicitly address methodological uncertainties. This study introduces an integrated methodology to evaluate green infrastructure's hydrological role across land‐cover and climate scenarios. It combines Coupled Model Intercomparison Project Phase 6 (CMIP6) projections with Quantile Mapping bias correction, Generalized Extreme Value (GEV) analysis, physically informed intensity–duration–frequency (IDF) curve development, and spatially explicit Hydrologic Engineering Center–Hydrologic Modeling System (HEC‐HMS). Designed for regions with limited gauging infrastructure, the framework leverages satellite‐derived precipitation from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), open‐access climate data. Applied to the Güanguiltagua Metropolitan Park in Quito, Ecuador, the approach reveals context‐specific responses: under projections from the Max Planck Institute Earth System Model version 1.2 Low Resolution (MPI‐ESM1‐2‐LR), extreme events (return periods T ≥ 50 years) exhibit a saturation signal converging towards ~95 mm/day—a pattern consistent with documented shifts in Andean convective regimes yet contingent on model resolution and requiring validation with convection‐permitting simulations. Critically, conservation of natural cover (Curve Number, CN = 45) consistently reduces peak flows by 73%–85% across all scenarios and return periods, demonstrating green infrastructure's dependable buffering capacity. Urbanized sub‐basins (CN = 85) show minimal climate sensitivity, underscoring persistent vulnerability. Findings are explicitly contextualized within methodological constraints (single general circulation model [GCM], coarse resolution, Soil Conservation Service Curve Number [SCS‐CN] assumptions), avoiding overgeneralization. The framework's modular design enables adaptation across Global South contexts, offering a transparent template for region‐specific flood risk assessment where climate projections and green infrastructure intersect.
The critical zone (CZ) evolves through coupled physical and chemical processes that drive subsurface weathering and mass loss. Quantifying these processes is commonly based on borehole geochemistry, which provides robust but spatially limited constraints, while near-surface geophysical methods offer broader coverage but are often interpreted qualitatively. In this study we integrate borehole and surface geophysical data with the bulk mass transfer coefficient (bulk tau) to develop Geophysical Tau (), a geophysics-based proxy for subsurface weathering that better constrains weathering patterns than directly converting ERT to bulk tau. The method is demonstrated using coincident borehole geochemical, borehole geophysical and surface resistivity datasets collected in volcanic rock in Johnston Draw, a subwatershed of the Reynolds Creek Experimental Watershed and Critical Zone Observatory, Idaho. is calibrated at the borehole by linking bulk tau to geophysical indicators of weathering and is extended spatially using surface electrical resistivity tomography data. The resulting reveals laterally extensive, clay-rich weathered zones that are not explained by meteoric infiltration alone and are consistent with interpretations of bottom-up weathering driven by convection of geothermally influenced fluids. Geophysical Tau provides a quantitative framework for integrating geochemical and geophysical observations to interpret subsurface mass loss and weathering and is transferable to analogous volcanic settings worldwide.
Hydrological processes that drive basin-scale flood generation in semi-arid river systems remain poorly constrained, limiting effective basin management under an increasingly variable monsoon regime. Using a historic monsoon flood in a regulated semi-arid basin, we show that the synchronisation of hydrometeorological perturbations (or extremes) with reservoir operations activates distinct hydrological pathways responsible for extreme downstream flooding in semi-arid river basins. A systematic change in rainfall intensity distribution from light to moderate and heavy events as the monsoon progressed altered the basin-scale hydrological balance. The rainfall sequencing, from widespread early-season events to intense, localised late-season extremes, transitioned the basin from an infiltration-dominated behaviour to a runoff-dominated response. These transitions produced an atypical dual-peak reservoir discharge pattern-an unprecedented hydrological response in a semi-arid basin, where high reservoir outflows are rare and, when they occur, are confined to a single seasonal peak. Consequently, basin buffering capacity was progressively reduced during the staggered first discharge peak, promoting runoff concentration during the subsequent highly synchronised peak release. The late-season occurrence of dynamically driven mesoscale convective systems intensified this hydrological response by delivering concentrated rainfall when antecedent storage and hydrological loading were already elevated. The conceptual framework developed from the extreme monsoon event demonstrates that flood generation in regulated semi-arid basins is also governed by the spatio-temporal organisation of rainfall, antecedent hydrological pressure and the transition of reservoir systems from buffering to synchronising behaviour. These previously undocumented characteristics of the regional hydrometeorology and flood response serve as a basis for improved process-level understanding of semi-arid river basin hydrology. The findings of this study provide actionable insights for anticipatory flood management, adaptive reservoir operations and climate-resilient basin-scale planning in dryland river systems experiencing intensifying hydroclimatic extremes.
Evapotranspiration (ET) links vegetation and soils to the atmosphere and can be the dominant water flux in many areas. Whilst the estimation of ET can be constrained by different observations (e.g., discharge, stable water isotopes, remote sensing products etc.), their information content differs and their trade-offs in model calibration are usually unknown. This is particularly the case in ET-dominated, intensively managed catchments where ET strongly affects water supply and ecosystem services. Here, we investigated the heavily-managed Middle Spree catchment (MSC, similar to 2800 km(2)) in NE Germany, a sub-basin of the River Spree that includes the large Spreewald wetland (similar to 472 km(2)) and serves as a key water resource for Berlin. The catchment is strongly impacted by groundwater abstraction and drainage. We applied multiple calibration schemes that combined different observations in a tracer-aided, spatially distributed catchment model (STARR) over a 20-year period, to investigate linkages between ecohydrological functioning and ET processes. Importantly, trade-offs among performance metrics were subsequently analysed in the solution space of multi-variable calibrations using Shapley additive explanation (SHAP) analysis. We found that discharge and temporal ET patterns can constrain water balance volumes, though their influence was modulated by ET-dominated wetlands and human management. In contrast, incorporating spatial ET patterns and isotopic observations led to more plausible spatial representations of hydrological processes (i.e., ET and subsurface storage). Isotopic data uniquely captured relative contributions of evaporation and transpiration to total ET (ET partitioning). However, the constraining power of these observations was limited by trade-offs, which were reflected in contrasting hydrological processes. The wetlands and human management could also influence these constraints. Although multiple calibration schemes revealed competing hypotheses of local hydrological functioning, they collectively provided richer and more integrated insights into how human management influences ecohydrological functioning in complex ET-dominated catchments.
ABSTRACT Since the 1960s, continental serpentinization‐influenced environments have served as natural laboratories for investigating low‐temperature aqueous geochemistry involving dissolved H 2 and CH 4 , with broad implications for deep Earth elemental cycles, energy resources, and astrobiology. Here, we compiled, homogenised, and analysed geochemical data (aqueous and dissolved gas) from 34 studies focused exclusively on hyperalkaline spring seepage manifestations. The resulting database includes 2309 individual measurements spanning 16 physical and chemical variables. Tropical environments exhibited higher median values in Fe, Ni, CO 3 2− , dissolved inorganic carbon, and dissolved CH 4 . Dissolved H 2 presented the highest median values in arid and cold continental settings. The arid environment also showed the highest median values in electrical conductivity (EC) and major ions (Na + , K + , Ca 2+ , Cl − ). PCA dimension 1 (49.7%) was dominated by major ions, EC, Fe, Ni, CH 4 , and H 2 , reflecting strong controls on solute and redox‐related chemistry, while Dimension 2 (8.7%) was primarily associated with water temperature. Tropical sites clustered toward Ni, Fe, oxidation–reduction potential, and Mg 2+ , reflecting oxidising conditions and elevated metal concentrations, which are potentially derived from intense rock and soil monsoonal weathering. Arid sites trend toward OH − , Cl − , Ca 2+ , Na + , EC, and H 2 , consistent with higher surface evaporative concentration and salinity in more evolved groundwater flows. Cold and temperate sites show greater variability, with hyperalkaline fluids tending toward higher pH and H 2 . Our global comparison provides a systematic synthesis and framework for identifying both common patterns and site‐specific differences in low‐temperature continental serpentinization, underscoring the potential influence of regional hydrology, particularly groundwater flow and residence times, and water availability, in regulating conditions for H 2 and CH 4 production.
Monitoring studies have identified the occurrence of hundreds of contaminants of emerging concern (CECs) throughout water, sediments, and biota. Despite their ubiquitous presence, relatively few studies explore how environment and land use affect CEC occurrence. In this work, we performed temporal sampling across proximal watersheds, which provided a unique opportunity to study influences on regional CEC presence and to identify overarching patterns in CEC behaviour. We collected grab samples in twenty mixed-use watersheds around central New York throughout 2018 and 2019 across diverse hydrologic and environmental conditions. Samples were analysed using liquid chromatography-high resolution mass spectrometry and quantified with reference standards producing CEC concentrations. A total of 79 CECs were identified; their concentrations were analysed using correlation analysis and Ordinary Least Square (OLS) modelling to assess relationships between their concentrations, land use, and environmental factors. Our results show that in addition to varying water quality levels among different sites, CEC behaviour is highly variable among compounds. In addition, we show that urban and agricultural land cover can be highly useful in predicting the number and concentration of detected compounds. These findings can be used to support data-driven CEC models as well as inform future mitigation and monitoring strategies.
Effective and balanced management of economic and environmental concerns in groundwater-irrigated basins is a world-wide challenge. Environmental flow modification is increasingly influenced by groundwater-supported irrigation in these heavily irrigated regions, yet the ability to rigorously quantify how groundwater-based irrigation influences ecological surface-water flows remains limited, leaving resource managers with difficult and opaque decisions regarding resource allocation. This work presents a generic and generalised framework to programmatically evaluate how groundwater use for irrigation has altered surface-water flow characteristics by using an integrated surface-subsurface modelling system paired with rigorous ensemble-based data assimilation. As an example, we demonstrate the mechanisms linking groundwater dynamics to environmental flow alteration in groundwater-dependent river systems, utilising the Mississippi Alluvial Plain (MAP), USA, as a representative study. Specifically, a coupled SWAT+gwflow model was applied across six HUC-8 watersheds and calibrated using an iterative ensemble smoother, incorporating both monthly streamflow and groundwater head observations. Model performance was evaluated using multiple hydrologic metrics and independent datasets, including streamflow, groundwater levels and basin-scale evapotranspiration. Environmental flow alteration was quantified using the IAHRIS framework under managed and naturalised conditions. Results reveal that while annual discharge volumes remain near stable, substantial degradation occurs in low-flow magnitude, duration and seasonal structure. Groundwater abstraction-induced baseflow reduction emerged as the primary driver of low-flow collapse, particularly during the irrigation season. The proposed framework provides a transferable, process-oriented methodology for diagnosing groundwater-driven environmental flow alteration in intensively irrigated basins and offers a robust basis for evaluating sustainable groundwater-surface water management strategies under increasing water demand.
This study investigates the statistical association between hydroclimatic stress and reported industrial discharge loads from Spain's agri-food industry between 2020 and 2025. Utilizing a panel dataset linked to regulatory and climate data, specifically the Standardized Precipitation Evapotranspiration Index (SPEI) at 6, 12 and 24 month windows, we examine the association between SPEI-based hydroclimatic variability and annual reported loads of Chemical Oxygen Demand (COD), total Nitrogen and total Phosphorus. Results show a statistically significant association between SPEI and reported annual discharge loads. In the aggregate models, higher SPEI values, corresponding to wetter conditions, are associated with higher reported annual discharge totals. Therefore, these estimates should not be interpreted as evidence that drought increases absolute reported loads. Rather, drought is relevant because reduced streamflow can lower the dilution and assimilative capacity of receiving water bodies, increasing environmental pressure for a given discharge load. The response of phosphorus is more variable, influenced by operational decisions and treatment technologies. Spatial analysis identifies provinces exhibiting combined recurrent drought and high discharge loads, creating an operational vulnerability map shaped by local industrial pressure and hydroclimatic conditions. Food and beverage subsectors indicate differing sensitivities to hydroclimatic stress conditions, with the beverage industry showing greater sensitivity in the tested specifications. The findings establish a reproducible empirical basis for operational planning, water risk management and climate resilience strategies in the agri-food sector. This research highlights the importance of integrating regulatory and climate data for effective decision making within Spain's agri-food industry.
