Search Results (202)

Interactions between surface water and groundwater in arid regions regulate their response to climate and human impacts. In the salar systems of the Altiplano-Puna plateau (Bolivia, Chile, Argentina), understanding how surface waters connect to groundwater is crucial for accurate modeling and assessment. This study introduces new data and analysis using subsurface thermal profiles and modeling to identify flow patterns and possible surface water links. We document, to our knowledge, for the first time in the literature, deep-seated cooling of the subsurface caused by extreme evaporation rates. The subsurface is cooled by 4–5 degrees Celsius below the mean annual air temperature to depths greater than 50 m, even though groundwater inflow waters are elevated by 10 degrees °C due to geothermal heating. Three thermal zones are observed along the southern edge of Salar de Atacama, with temperature dropping from 28 °C to about 12 °C over 2.5 km. A 2D numerical model of groundwater and heat flow was developed to test various hydrological scenarios and understand the factors controlling the thermal regime. Two flow scenarios at the southern margin were examined: a diffuse flow model with uniform flow and flux to the surface and a focused flow model with preferential discharge at a topographic slope break. Results indicate that the focused flow scenario matches thermal data, with warm inflow water discharging into a transition zone between freshwater and brine, cooling through evaporation, re-infiltration, and surface flow, then re-emerging near lagoons at the halite nucleus margin. This research offers valuable insights into the groundwater hydraulics in the Salar de Atacama and can aid in monitoring environmental changes causally linked to lithium mining and upgradient freshwater extraction. Full article

As exposed bedrocks commonly interface with the soil directly, lacking a transition layer, cracks at rock–soil interface cracks (RSI-Cracks), are well-developed, particularly following wet–dry alternation in karst critical zones. However, inadequate understanding of the influence of RSI-Cracks on multi-path runoff generation around bedrocks has hindered an in-depth comprehension of subsurface-dominated hydrological processes in karst areas. To address this gap, we developed micro-slope models replicating rock–soil interfacial configurations by building upon field investigations. Two conditions, namely, the presence and absence of RSI-Cracks, were incorporated, with rain intensity and rock surface inclination as experimental conditions. Our results indicate that RSI-Cracks significantly alter the runoff output (p < 0.05), exacerbating subsurface water leakage. Compared with that on slopes without RSI-Cracks, the proportion of surface runoff on slopes with RSI-Cracks is reduced, with a reduction range of 4 to 46%. Conversely, RSI-Cracks promote an increase in the proportion of outflow at the rock–soil interface (RSI flow), with an increase range of 7 to 38%. This is an important reason for the aggravation of subsurface water leakage through RSI-Cracks. However, there is no significant change in the water loss caused by internal soil seepage on slopes with or without RSI-Cracks. These findings provide novel insights into underground water loss, with valuable implications for the construction and improvement of hydrological models in karst areas. Full article

Understanding how water-quality models perform across different hydrological and biogeochemical contexts is essential for managing nutrient losses in agricultural catchments. This study evaluated SimplyP, a parsimonious phosphorus model, adapted to better represent Irish agricultural catchments and implemented within the flexible Mobius2 framework. Long-term, high-frequency monitoring data from the Agricultural Catchments Programme (ACP) were used for two sites: Ballycanew, a grassland catchment dominated by surface runoff, and Castledockrell, an arable, groundwater-driven catchment. Model calibration and validation were performed for streamflow (Q), suspended sediment (SS), and multiple phosphorus (P) fractions, with performance assessed using Kling–Gupta efficiency (KGE). In Ballycanew, the model reproduced Q, SS, and total P load well, with weaker agreement for total reactive phosphorus (TRP), likely reflecting unaccounted point sources during low flows. In Castledockrell, performance was moderate for Q and SS, but TRP and other P fractions were not adequately captured, highlighting the need for more detailed representation of subsurface P pathways in groundwater-dominated systems. Overall, SimplyP is well-suited to surface-runoff-dominated catchments with conventional phosphorus mobilisation. Its flexible implementation in Mobius2 allows relatively straightforward modifications, such as including groundwater-mediated P processes, to extend applicability to more complex systems. High-resolution ACP datasets were crucial for identifying model strengths and limitations, supporting refinement for improved nutrient management across diverse agricultural landscapes. Full article

Oil and gas fields in subsidence-prone regions face multiple hazards that threaten the resilience of their infrastructure. This study presents an integrated risk mapping framework for the Yibal field in the Sultanate of Oman, utilizing remote sensing and geophysical data. Multi-temporal PS-InSAR analysis from 2010 to 2023 revealed cumulative surface deformation and tilt anomalies. Micro-seismic and fault proximity data assessed subsurface stress, while a flood risk map-based surface deformation-adjusted elevation captured hydrological susceptibility. All datasets were standardized into five risk zones (ranging from very low to very high) and combined through a weighted overlay analysis, with an emphasis on surface deformation and micro seismic factors. The resulting risk map highlights a central corridor of high vulnerability where subsidence, seismic activity, and drainage pathways converge, overlapping critical infrastructure. The results demonstrate that integrating geomechanical and hydrological factors yields a more accurate assessment of infrastructure risk than single-hazard approaches. This framework is adaptable to other petroleum fields, enhancing infrastructure protection (e.g., pipelines, flowlines, wells, and other oil and gas facilities), and supporting sustainable field management. Full article

This study investigates the hydraulic connection of surface karst features within the Northern segment of the Edwards Balcones Fault Zone Aquifer, using a combination of 2D and pseudo-3D Electrical Resistivity Tomography (ERT) at an outcrop near Salado, Texas. The study site features several surface fractures whose hydrological functions are not well understood. Nine ERT profiles and two pseudo-3D models were used to evaluate the connection between surface fractures and subsurface karst conduits. Karst features at the study site were physically evaluated using characteristics such as morphology, which resulted in the identification of three surface fractures (F1, F2, and F3). The ERT results showed several high-resistivity anomalies interpreted as a poorly fractured zone and low-resistivity water-filled conduits within the Edwards Formation. Furthermore, the result reveals that slow hydraulic connectivity exists in F1 and F2; however, F3 presents a low-resistivity zone that extends vertically into the subsurface, which suggests that F3 may serve as a potential recharge feature to the Edwards Aquifer. These findings are corroborated by a water percolation test, as water penetrated more at F3 compared to F1 and F2. This study showed that the combined application of 2D and pseudo-3D ERT can successfully delineate potential recharge pathways in an exposed karst system, thereby constituting a supportive approach providing critical insight into recharge and the vulnerability of karst aquifers to contamination. Full article

Groundwater resources in Jordan are under severe stress due to rapidly increasing water demand and over-abstraction that far exceeds natural replenishment. In addition, water quality is threatened by pollution from the misuse of fertilizers and pesticides, leakage from septic tanks, and illegal waste disposal. This study focuses on the Aqeb, Corridor, and Special Economic Zone wellfields, where hydrological and hydrochemical investigations were carried out. A total of 36 groundwater samples were collected and analyzed for hydrochemical composition, stable isotopes of oxygen (δ¹⁸O) and hydrogen (δ²H), and trace elements. In addition, two exploration 2D seismic profiles crossing the study area were interpreted, providing critical insights into the activity of the subsurface Fuluk Fault zone and its relationship with the wellfields. The hydrochemical results reveal elevated total dissolved solids and nitrate concentrations, accompanied by more depleted δ¹⁸O and δ²H values in wells located in the central part of the study area. Three distinct hydrochemical groups were identified within the same aquifer, indicating heterogeneity in groundwater chemistry that reflects variations in recharge conditions, flow paths, and geochemical processes. The first group (high Na/Cl with low salinity) likely represents recently recharged waters with limited rock–water interaction. The second group (intermediate Na/Cl and moderate salinity) may be influenced by evaporation, irrigation return flow, or cation exchange. The third group (low Na/Cl with high salinity) suggests the dissolution of sulfate minerals or mixing with deeper mineralized groundwater, possibly facilitated by structural features such as the Fuluk Fault. Seismic interpretation indicates several active near-surface fault systems that are likely to serve as preferential pathways for salinity and nitrate enrichment, linked to intensive agricultural activities and wastewater leakage from nearby septic tanks. The findings emphasize the combined influence of geochemical processes, excessive groundwater abstraction, and structural features in controlling water quality in the region. Full article

Monitoring groundwater dynamics and basin-scale water budget closure is critical for sustainable water resource management, especially in regions facing climate stress and overexploitation. This study examines the temporal variability of total water storage and groundwater trends in Türkiye’s Kızılırmak River Basin by integrating GRACE/GRACE-FO satellite gravimetry, GLDAS-Noah land surface model outputs, ERA5-Land reanalysis products, and local meteorological observations. Groundwater storage anomalies (GWSAs) were derived from the difference between GRACE-based total water storage anomalies (TWSAs) and GLDAS-modeled surface storage components, revealing a long-term groundwater depletion trend of −9.55 ± 2.6 cm between 2002 and 2024. To investigate the hydrological drivers of these changes, lagged correlation analyses were performed between GRACE TWSA and ERA5-Land variables (precipitation, evapotranspiration, runoff, soil moisture, and temperature), showing time-shifted responses from −3 to +3 months. The strongest correlations were found with soil moisture (CC = 0.82 at lag −1), temperature (CC = −0.70 at lag −3), and runoff (CC = 0.71 at lag 0). A moderate correlation between GRACE TWSA and ERA5-based water storage closure (CC = 0.54) indicates partial alignment. These findings underscore the value of satellite gravimetry in tracking subsurface water changes and support its role in basin-scale hydrological assessments. Full article

Understanding the impact of climate change and altered hydrologic cycles on regional water storage trends is crucial for predicting changes in recharge and streamflow and informing decisions regarding drought resilience and flood mitigation. While many regions have become drier under global climate change, the northeast United States has experienced an increased precipitation intensity, driving groundwater rise. This study integrates terrestrial water storage data from NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites and soil moisture data from Soil Moisture Active Passive (SMAP), as well as long-term instrumental groundwater records from USGS groundwater monitoring wells, to understand the nature of storage trends. The results show that while aquifer-wide groundwater storage anomalies have stabilized in recent years, shallow groundwater and certain surface water bodies have accumulated about 0.6 cm of water annually, adding over 10 cm to the landscape, since 2005. These findings indicate that excess water from heavy rainfall is mainly stored in the shallow subsurface as perched aquifers and temporary wetlands rather than deep (5–30 m) aquifers. Understanding this change in storage is crucial for improving water resource management and adapting more effectively to a changing climate in the region. Full article

In semi-arid regions of Morocco, where the majority of water withdrawals are devoted to irrigation, optimizing irrigation practices in agriculture is a national priority in the face of recurring droughts and growing pressure on groundwater resources. However, the hydrological impacts of different drip-irrigation systems in the soil–plant–atmosphere continuum remain insufficiently understood. We monitored the stable isotope composition (δ²H, δ¹⁸O) across the two agricultural plots in Marrakech (Morocco) with surface drip and subsurface drip irrigation treatments for a complete hydrologic year (June 2022 to June 2023). Weekly to daily samples of rainfall, irrigation water, groundwater, and soil at various depths (5–50 cm) were sampled, and water from branch xylem was extracted using the cryogenic vacuum distillation method. We found that the subsurface irrigation treatment, which delivered water directly to the root zone, maintained narrow isotopic ranges in water of soils beyond 30 cm, as well as in branch xylem and leaf water. By contrast, surface irrigation treatment plots showed pronounced evaporative isotopic enrichment: summer topsoil water δ¹⁸O peaked at −1.1‰ (vs. −8.7‰ in subsurface irrigation treatment), and leaf water reached +13‰ (vs. +8‰ in subsurface). Despite this larger isotopic heterogeneity in surface irrigation site, branch xylem water δ¹⁸O remained within −6 to 2.5‰ across all soil depth, similar to subsurface irrigation treatment, which ranged between −5 and 0‰. This suggests that olive roots accessed soil water uniformly from the upper 50 cm under both irrigation treatments. Seasonal xylem isotopic enrichment in spring and midsummer mirrored shifts towards shallow, evaporatively altered soil water under surface irrigation, but not under the subsurface. The results suggest that subsurface drip irrigation can significantly improve drought resilience and water-use efficiency in the expanding olive sector of the Maghreb, while continuous isotope monitoring serves as a practical approach to enhance sustainable and adaptive water management in water-limited regions. Full article

Northern Taiwan is a tectonically and volcanically active region shaped by plate convergence, active faulting, and subsurface hydrological processes. To investigate surface deformation across this complex setting, we applied Persistent Scatterer InSAR (PSInSAR) to Sentinel-1A imagery acquired from 2017 to 2022. Using data from ascending and descending tracks, and removing GNSS-derived northward motion, we decomposed line-of-sight velocities into vertical and eastward components. The resulting deformation fields, validated by dense precision leveling and continuous GNSS observations, reveal consistent but minor (less than 1 cm/year) land subsidence in the Taipei Basin, spatially variable uplift near the Tatun Volcano Group, and a previously vaguely documented uplift zone in northeastern Taoyuan. InSAR-derived eastward motion is consistent with expected kinematics along the southern Shanchiao Fault and supports broader patterns of clockwise tectonic rotation near Keelung. Our InSAR results show the effectiveness of PSInSAR in resolving multidirectional surface motion and exemplifies the value of integrating satellite-based and ground-based geodetic data for fault assessment, hydrologic monitoring, and geohazard evaluation in northern Taiwan. Full article

Partial Differential Equation (PDE)-based hydrologic models demand extensive preprocessing, creating a bottleneck and slowing down the model setup process. Mesh generation typically lacks integration with hydrological features like river networks. We present GHOST Mesh (GMesh), an automated, watershed-oriented mesh generator built within the Watershed Modeling Framework (WMF), to address this. While primarily designed for the GHOST hydrological model, GMesh’s functionalities can be adapted for other models. GMesh enables rapid mesh generation in Python by incorporating Digital Elevation Models (DEMs), flow direction maps, network topology, and online services. The software creates Voronoi polygons that maintain connectivity between river segments and surrounding hillslopes, ensuring accurate surface–subsurface interaction representation. Key features include customizable mesh generation and variable refinement to target specific watershed areas. We applied GMesh to Iowa’s Bear Creek watershed, generating meshes from 10,000 to 30,000 elements and analyzing their effects on simulated stream flows. Results show that higher mesh resolutions enhance peak flow predictions and reduce response time discrepancies, while local refinements improve model performance with minimal additional computation. GMesh’s open-source nature streamlines mesh generation, offering researchers an efficient solution for hydrological analysis and model configuration testing. Full article

Permafrost degradation, driven by the thawing of ground ice, results in the progressive thinning and eventual loss of the permafrost layer. This process alters hydrological and ecological systems by increasing surface and subsurface water flow, changing vegetation density, and destabilising the ground. The thermal and hydraulic conductivity of permafrost are strongly temperature-dependent, both increasing as the soil warms, thereby accelerating thaw. In addition, thawing permafrost releases large quantities of greenhouse gases, establishing a feedback loop in which global warming both drives and is intensified by permafrost loss. This paper reviews the mechanisms and consequences of permafrost degradation, including reductions in strength and enhanced deformability, which induce landslides and threaten the structural integrity of foundations and critical infrastructure. Permafrost has been investigated and modelled extensively, and various approaches have been devised to address the consequences of thawing permafrost on communities and the built environment. Some techniques focus on keeping the ground frozen via insulation, while others propose local replacement of permafrost with more stable materials. However, given the scale and pace of current changes, systematic remediation appears unfeasible. This calls for increased efforts towards adaptation, informed by interdisciplinary research. Full article

Groundwater–surface water interactions play a critical role in regulating river temperature and flow, particularly in northern regions affected by climate change. This study evaluates the influence of climate warming on groundwater discharge for two rivers in Quebec: the Sainte-Marguerite River, located in a humid continental zone without permafrost, and the Berard River, situated in a subpolar continental zone with discontinuous permafrost. Using two-dimensional hydrothermal modeling supported by field data, the analysis reveals that climate warming will increase groundwater seepage into both river systems. The effect is notably more pronounced in permafrost regions, where thawing accelerates subsurface flow. Model projections indicate that permafrost near the Berard River may vanish by 2040 under high-emission scenarios or by 2070 under low-emission scenarios. This transition is expected to result in more than a thirtyfold increase in groundwater discharge by the end of the century. These findings highlight the growing influence of groundwater in shaping river hydrology under changing climatic conditions and underscore the need to incorporate subsurface flow dynamics into future water resource management and habitat conservation strategies in northern environments. Full article

Accurate real-time information about soil moisture (SM) at a large scale is essential for improving hydrological modeling, managing water resources, and monitoring extreme weather events. This study presents a framework using convolutional long short-term memory (ConvLSTM) network to produce short- (1, 3, and 7 days ahead) and mid-term (14 and 30 days ahead) forecasts of SM at surface (0–10 cm) and subsurface (10–40 and 40–100 cm) soil layers across the contiguous U.S. The model was trained with five-year period (2018–2022) datasets including Soil Moisture Active Passive (SMAP) level 3 ancillary covariables, North American Land Data Assimilation System phase 2 (NLDAS-2) SM product, shortwave infrared reflectance from Moderate Resolution Imaging Spectroradiometer (MODIS), and terrain features (e.g., elevation, slope, curvature), as well as soil texture and bulk density maps from the Soil Landscape of the United States (SOLUS100) database. To develop and evaluate the model, the dataset was divided into three subsets: training (January 2018–January 2021), validation (2021), and testing (2022). The outputs were validated with observed in situ data from the Soil Climate Analysis Network (SCAN) and the United States Climate Reference Network (USCRN) soil moisture networks. The results indicated that the accuracy of SM forecasts decreased with increasing lead time, particularly in the surface (0–10 cm) and subsurface (10–40 cm) layers, where strong fluctuations driven by rainfall variability and evapotranspiration fluxes introduced greater uncertainty. Across all soil layers and lead times, the model achieved a median unbiased root mean square error (ubRMSE) of 0.04 cm³ cm⁻³ with a Pearson correlation coefficient of 0.61. Further, the performance of the model was evaluated with respect to both land cover and soil texture databases. Forecast accuracy was highest in coarse-textured soils, followed by medium- and fine-textured soils, likely because the greater penetration depth of microwave observations improves SM retrieval in sandy soils. Among land cover types, performance was strongest in grasslands and savannas and weakest in dense forests and shrublands, where dense vegetation attenuates the microwave signal and reduces SM estimation accuracy. These results demonstrate that the ConvLSTM framework provides skillful short- and mid-term forecasts of surface and subsurface soil moisture, offering valuable support for large-scale drought and flood monitoring. Full article

Understanding spatial variability in crop yields across fields is critical for developing precision agricultural strategies that optimize productivity while reducing negative environmental impacts. This variability often arises from a complex interplay of topographic features, soil characteristics, and hydrological conditions. This study investigates the influence of hydro-topographic factors on corn and soybean yield variability from 2016 to 2023 at the well-managed experimental sites in Beltsville, Maryland. A high-resolution surface digital elevation model (DEM) and subsurface DEM derived from ground-penetrating radar (GPR) were used to quantify topographic factors (elevation, slope, and aspect) and hydrological factors (surface flow accumulation, depth from the surface to the subsurface-restricting layer, and distance from each crop pixel to the nearest subsurface flow pathway). Topographic variables alone explained yield variation, with a relative root mean square error (RRMSE) of 23.7% (r² = 0.38). Adding hydrological variables reduced the error to 15.3% (r² = 0.73), and further combining with remote sensing data improved the explanatory power to an RRMSE of 10.0% (r² = 0.87). Notably, even without subsurface data, incorporating surface-derived flow accumulation reduced the RRMSE to 18.4% (r² = 0.62), which is especially important for large-scale cropland applications where subsurface data are often unavailable. Annual spatial yield variation maps were generated using hydro-topographic variables, enabling the identification of long-term persistent yield regions (LTRs), which served as stable references to reduce spatial anomalies and enhance model robustness. In addition, by combining remote sensing data with interannual meteorological variables, prediction models were evaluated with and without hydro-topographic inputs. The inclusion of hydro-topographic variables improved spatial characterization and enhanced prediction accuracy, reducing error by an average of 4.5% across multiple model combinations. These findings highlight the critical role of hydro-topography in explaining spatial yield variation for corn and soybean and support the development of precise, site-specific management strategies to enhance productivity and resource efficiency. Full article