Groundwater Model Research Articles

Joint inversion of induced polarization and hydraulic tomography data for hydraulic conductivity imaging

SUMMARY For accurate modelling of groundwater flow and transport processes within an aquifer, precise knowledge about hydraulic conductivity K and its small-scale heterogeneities is fundamental. Methods based on pumping tests, such as hydraulic tomography (HT), allow for retrieving reliable K-estimates, but are limited in their ability to image structural features with high resolution, since the data from time-consuming hydraulic tests are commonly sparse. In contrast, geophysical methods like induced polarization (IP) can potentially yield structural images of much higher resolution, but depend on empirical petrophysical laws that may introduce significant uncertainties to the K-estimation. Therefore, this paper presents a joint inversion procedure for both HT and IP data, which allows for combining the complementary abilities of both methods. Within this approach, a traveltime inversion is applied to the HT data, while the IP inversion is based on a full-decay time-domain forward response, as well as a reparametrization of the Cole–Cole model to invert for K directly. The joint inversion is tested on a synthetic model mimicking horizontally layered sediments, and the results are compared with the individual HT and IP inversions. It is shown that jointly inverting both data sets consistently improves the results by combining the complementary sensitivities of the two methods, and that the inversion is more robust against changes in the experimental setups. Furthermore, we illustrate how a joint inversion approach can correct biases within the petrophysical laws by including reliable K-information from hydraulic tests and still preserving the high-resolution structural information from IP. The different inversion results are compared based on the structural similarity index (SSIM), which underlines the robustness of the joint inversion compared to using the data individually. Hence, the combined application of HT and IP within field surveys and a subsequent joint inversion of both data sets may improve our understanding of hydraulically relevant subsurface structures, and thus the reliability of groundwater modelling results.

Hydrochemical evolution of groundwater in a river corridor: the compounded impacts of various environmental factors

Various environmental factors could induce groundwater hydrochemical evolution, which should be considered when addressing groundwater environmental issues. However, the complex interactions among the environmental controls remain unknown for a groundwater flow system spanning multiple geological units. To fill this gap, we conducted a study on the groundwater hydrochemical evolution in the fluvial corridor of the Fen River, Northern China, utilizing a combination of hydrogeochemical and multiple isotope methods. Results reveal that the groundwater in the corridor has significantly degraded due to high concentrations of SO42-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{SO}}_{4}^{2 - }$$\\end{document}, NO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{NO}}_{3}^{ - }$$\\end{document}, Cl−, or F−. We find an unordered evolution of the hydrochemical composition of groundwater along this corridor. These evolutions are driven by mineral dissolution/precipitation, dedolomitization, and cation exchange processes. Human activities play a significant role, with notable contributions including NO3-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{NO}}_{3}^{ - }$$\\end{document} fluxes from agricultural fertilizers, manure, and sewage, as well as SO42-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{SO}}_{4}^{2 - }$$\\end{document} fluxes arising from coal mining activities. The combination between karst spring areas and faults/uplifts, between coal-bearing strata and mining activities fosters the mixing of karst water/mine water with shallow groundwater, promoting dramatic hydrochemical evolution of groundwater. The flat terrain and the natural blockage formed by mountains significantly enhance water–rock interactions and groundwater evaporation by slowing groundwater flow. The contribution of evaporation on groundwater salinity ranges from ~ 0.2% to 4.8%, highlighting its importance in the groundwater hydrochemical evolution. This study unravels the multifaceted nature of groundwater hydrochemical evolution. It emphasizes the four types of environmental controls, including hydrogeochemical processes, climate factors, human activities, and variations in geological settings, can be equally important, which is usually ignored. The findings enrich our understanding of groundwater evolution and highlight the challenges encountered in regions composed of diverse geological units.

The Hydraulic Evolution of Groundwater-Fed Pit Lakes After Mine Closure.

Open pit mining frequently requires regional water tables to be lowered to access ore deposits. When mines close, dewatering ceases allowing the water table to recover. In arid and semi-arid mining regions, the developing pit lakes are predominantly fed by groundwater during this recovery phase and pit lakes develop first into "terminal sinks" for the surrounding groundwater system. With time, the re-establishment of regional hydraulic gradients can cause pit lakes to develop into throughflow systems, in which pit lake water outflows into adjacent aquifers. In this study, we use numerical groundwater modeling to aid process understanding of how regional hydraulic gradients, aquifer properties, net evaporation rates, and pit geometry determine the hydraulic evolution of groundwater-fed pit lakes. We find that before the recovery of the regional water table to its new equilibrium, pit lakes frequently transition to throughflow systems. Throughflow from pit lakes to downstream aquifers can develop within two decades following cessation of dewatering even under low hydraulic gradients (e.g., 5 × 10-4) or high net evaporation rates (e.g., 2.5 m/year). Pit lakes remain terminal sinks only under suitable combinations of high evaporation rates, low hydraulic gradients, and low hydraulic conductivities. In addition, we develop an approximate analytical solution for a rapid assessment of the hydraulic status of pit lakes under steady-state conditions. Understanding whether pit lakes remain terminal sinks or transition into throughflow systems largely determines the long-term water quality of pit lakes and downstream aquifers. This knowledge is fundamental for mine closure and planning post-mining land use.

Reduced Geostatistical Approach With a Fourier Neural Operator Surrogate Model for Inverse Modeling of Hydraulic Tomography

AbstractIn this study, we propose a new approach for inverse modeling of hydraulic tomography (HT) using the Fourier neural operator (FNO) as a surrogate forward model. FNO is a deep learning model that directly parameterizes the integral kernel in Fourier space to learn solution operators for parametric partial differential equations (PDEs). We trained a highly accurate FNO to learn the solution operators of PDEs in HT, which can efficiently generate multiple channels of hydraulic head fields corresponding to specific pumping tests in new parameter fields through a single forward pass. The trained FNO surrogate model is integrated with the reduced geostatistical approach (RGA) to provide a powerful tool, named RGA‐FNO, for inverse modeling of Gaussian random fields. RGA utilizes principal components to effectively reduce problem dimensions and encode geostatistical information. FNO benefits from deep learning automatic differentiation, enabling efficient backpropagation of gradients during inverse modeling. Our results show that RGA‐FNO can efficiently produce satisfactory estimations for random transmissivity fields with an exponential covariance function, which is non‐differentiable and visually non‐smooth. The RGA‐FNO application on steady‐state multi‐well HT is better than the single‐well transient pumping test for inverse modeling. The data required for inverse modeling applications of RGA‐FNO increases with the variance of the random transmissivity fields. FNO and other neural operator models have the potential to play an important role in groundwater modeling, especially in inverse modeling and experimental design, which often requires a large number of forward simulations.

Characteristics and genesis of groundwater salinization in coastal areas of the Lower Reaches of Oujiang Basin

Characteristics and genesis of groundwater salinization in coastal areas of the Lower Reaches of Oujiang Basin

Developing three-dimensional groundwater flow modeling for the Erbil Basin using Groundwater Modeling System (GMS)

Developing three-dimensional groundwater flow modeling for the Erbil Basin using Groundwater Modeling System (GMS)

A Comprehensive Assessment of Climate Change and Anthropogenic Effects on Surface Water Resources in the Lake Urmia Basin, Iran

In recent decades, the depletion of surface water resources within the Lake Urmia Basin (LUB), Iran, has emerged as a significant environmental concern. Both anthropogenic activities and climate change have influenced the availability and distribution of surface water resources in this area. This research endeavors to provide a comprehensive evaluation of the impacts of climate change and anthropogenic activities on surface water resources across the LUB. Various critical climatic and anthropogenic factors affecting surface water bodies, such as air temperature (AT), cropland (CL), potential evapotranspiration (PET), snow cover, precipitation, built-up areas, and groundwater salinity, were analyzed from 2000 to 2021 using the Google Earth Engine (GEE) cloud platform. The JRC-Global surface water mapping layers V1.4, with a spatial resolution of 30 m, were employed to monitor surface water patterns. Additionally, the Mann–Kendall (MK) non-parametric trend test was utilized to identify statistically significant trends in the time series data. The results reveal negative correlations of −0.56, −0.89, −0.09, −0.99, and −0.79 between AT, CL, snow cover, built-up areas, and groundwater salinity with surface water resources, respectively. Conversely, positive correlations of 0.07 and 0.12 were observed between precipitation and PET and surface water resources, respectively. Notably, the findings indicate that approximately 40% of the surface water bodies in the LUB have remained permanent over the past four decades. However, there has been a loss of around 30% of permanent water resources, transitioning into seasonal water bodies, which now account for nearly 13% of the total. The results of our research also indicate that December and January are the months with the most water presence over the LUB from 1984 to 2021. This is because these months align with winter in the LUB, during which there is no water consumption for the agriculture sector. The driest months in the study area are August, September, and October, with the presence of water almost at zero percent. These months coincide with the summer and autumn seasons in the study area. In summary, the results underscore the significant impact of human activities on surface water resources compared to climatic variables.

Identification of deep Czech Republic–Austria transboundary aquifer discharge and associated river chloride loading

The deep transboundary aquifer of regional scale along the Czech Republic–Austria border in Central Europe serves as a thermal-mineral water resource for balneotherapy and plays an important role in the region’s development. The aquifer is composed mostly of Jurassic carbonates at depths from 160 to − 3000 masl. Despite more than two decades of exploitation, no complex analysis of groundwater flow directions and groundwater fluxes ever took place. Now, cross-border cooperation enabled the research team to gather crucial information on the Jurassic aquifer. For a better understanding of the groundwater flow system, a numerical model was developed. To simulate the effect of variable density and viscosity occurring in such a deep aquifer, the SEAWAT numerical model was used. The simulation shows that there is an inflow of low mineralised groundwater from the crystalline outcrops in the northwest and inflow of saline groundwater from southeast. Aquifer discharge was identified along the zone partly corresponding to the course of the Dyje River. To check the model’s accuracy, the river water was sampled together with streamflow measurements. Detected sections of increasing chloride concentration indicate zones of the Jurassic aquifer discharge into the Dyje River. The discharge rate of 85 L/s derived from streamflow and chloride concentrations matches the value computed by the model. The relatively high discharge of the Jurassic aquifer contributes significantly to the high chloride loading observed in the Dyje River.

Flux tracking of groundwater via integrated modelling for abstraction management

In systems where surface water and groundwater interact, management of the water resource often involves conflicting objectives between water supply and baseflow maintenance. Balancing such objectives requires understanding of the role of groundwater in integrated water systems to inform the design of an efficient strategy to minimise abstraction impacts. This study first develops a reduced-complexity, processed-based groundwater model within the water systems integration modelling framework (WSIMOD). This model is applied to the Lea catchment, UK, as a case study and evaluated against monitored groundwater level and river flow data. A flux tracking approach is developed to reveal the origins of both river baseflow at a critical assessment point and abstracted groundwater across the systems. The insights obtained are used to design two strategies for groundwater abstraction reduction. Results show that the model has good performance in simulating the groundwater and river flow dynamics. Three aquifer bodies that contribute the most to the river baseflow in the dry season at the assessment point are identified; contributions being 17 %, 15 %, and 5 %. The spatial distribution of abstracted groundwater originating from these aquifer bodies is illustrated. Compared to the default equal-ratio reduction, the strategy prioritising abstraction reduction in these three aquifer bodies increases a similar amount of baseflow (13 %) by reducing much less abstraction (23 %). The other strategy, which further decreases abstraction in the adjacent aquifer bodies, increases more baseflow (16 %) with a similar abstraction reduction (30 %). Both strategies can more efficiently improve the baseflow. The flux tracking approach can be further implemented to trace water from other origins, including runoff, stormwater, and wastewater, to enable coordinated management for better systems-level performance.

Machine learning for faster estimates of groundwater response to artificial aquifer recharge

Groundwater models are a valuable tool in optimising the decisions influencing groundwater flow. Spatially distributed models represent the groundwater level in the entire area from where essential information can be extracted, directly aiding in the decision-making process. However, these models are time-consuming, limiting the number of scenarios that can be considered. This study explores different machine learning (ML) models as faster alternatives to predict the increase in steady-state groundwater head due to artificial recharge in the unconfined aquifer while considering a wider spatial extent (832 columns x 1472 rows totalling 765 km2) than previous ML groundwater models. We trained three ML models (encoder-decoder, U-Net, and attention U-Net) with various hypothetical artificial recharge sites (100, 300, 500, and 1000 sites) in the Baakse Beek catchment (the Netherlands), using a detailed numerical groundwater model, AMIGO. The applied recharge rate along with geo-hydrological properties from the AMIGO baseline run were used as inputs to the ML models. The properties’ permutation importance indicated that all properties of the first aquifer were important to predicting the response and were included when training the ML models. All three ML models improved with additional training sites but showed limited benefits from more than 500 recharge sites. Of the three ML models, U-Net and Attention U-Net outperformed the encoder-decoder. These two models achieved Nash-Sutcliffe efficiency (NSE) of more than 0.8 when trained with 300 or more recharge sites. U-Net trained on 1000 recharge sites had the highest overall NSE of 0.95. U-Net better captures input features with highly variable spatial characteristics, such as rivers and drains which influence the maximum height of the groundwater response. The model captured the influence of the input features on the response, reproducing the response patterns across the entire catchment. Finally, we showed that the trained ML models are faster than the numerical model, predicting within 0.24 s (97th percentile), making it ideal for optimising decisions.

Estimating Increased Transient Water Storage with Increases in Beaver Dam Activity

Dam building by beaver (Castor spp.) slows water movement through montane valleys, increasing transient water storage and the diversity of residence times. In some cases, water storage created by beaver dam construction is correlated to changes in streamflow magnitude and timing. However, the total amount of additional surface and groundwater storage that beaver dams may create (and, thus, their maximum potential impact on streamflow) has not been contextualized in the water balance of larger river basins. We estimate the potential transient water storage increases that could be created at 5, 25, 50, and 100% of maximum modeled beaver dam capacity in the Bear River basin, USA, by adapting the height above nearest drainage (HAND) algorithm to spatially estimate surface water storage. Surface water storage estimates were combined with the MODFLOW groundwater model to estimate potential increases in groundwater storage throughout the basin. We tested four scenarios to estimate potential transient water storage increases resulting from the construction of 1179 to 34,897 beaver dams, and estimated surface water storage to range from 57.5 to 72.8 m3 per dam and groundwater storage to range from 182.2 to 313.3 m3 per dam. Overall, we estimate that beaver dam construction could increase transient water storage by up to 10.38 million m3 in the Bear River basin. We further contextualize beaver dam-related water storage increases with streamflow, reservoir, and snowpack volumes.

Complex unstructured-grid groundwater modeling using centroidal Voronoi tessellation refinement and curve fitting

An unstructured grid is a powerful data structure for a proper depiction of various geological features such as faults and pinch-outs and for groundwater simulation in a complex aquifer system. This study presents a mesh generation methodology based on 2.5D centroidal Voronoi tessellations (CVTs), which provides a great flexibility in specifying grid connections in 3D, matching irregular geometries, and adding high levels of refinement in areas of interest. Lloyd relaxation approximation is introduced to effectively guarantee the generation of centroidal Voronoi grids. A curve-fitting Voronoi gridding approach is developed to construct Voronoi cell edges conforming to intricated geological traces in the horizontal 2D projection with unstructured vertical discretization. A controlled refinement in spatial grid resolution has been demonstrated to prevent adverse impacts on groundwater flow simulations. The methodology is applied to the Southern Hills aquifer system in the Capital Area of Louisiana, USA. Significant groundwater depletion has occurred due to continuous and excessive withdrawals over decades for public supplies and industries. The Baton Rouge fault and the Denham-Springs Scotlandville fault are leaky barriers and have a significant influence on groundwater flow. A curve-fitting centroidal Voronoi grid is developed to simulate the effects of the two faults as leaky barriers. CVT-based high-fidelity unstructured multi-model groundwater modeling is conducted using MODFLOW 6 to allow more flexibility in model design. Complex groundwater flow in the Southern Hills aquifer system was revealed through the centroidal Voronoi unstructured grid.

Unravelling the influence of heterogeneities and abstraction on groundwater flow and solute transport in a fractured carbonate aquifer, Sicily, Italy

The migration of a groundwater contaminant plume consisting of light nonaqueous phase liquids (LNAPLs) along the Ionian coastline of Sicily, Italy, has been reported to follow a trajectory that is inconsistent with the regional hydraulic gradient. The influence of several faults affecting the fractured carbonate bedrock aquifer, and groundwater abstraction from a well, were hypothesized to be responsible for the anomalous trajectory of the contaminant plume. A conceptual hydrogeological model was developed for the study area that incorporated structural information derived from geophysical surveys and the mapping of fractures in bedrock outcrops. This conceptual model was incorporated into numerical groundwater flow and solute transport models to simulate the groundwater transport of the light nonaqueous phase liquids. Four model scenarios representing different levels of complexity were tested to assess the relative influence of geological heterogeneity and groundwater abstraction on the migration of the contaminant plume. Results show that underground major discontinuity systems, invoking the presence of the faults in the model domain accounted for the observed migration of the contaminant plume, act as conduits for groundwater flow. Conversely, groundwater abstraction from a well was found to result in relatively minor, localized impacts to the migration of the contamination plume. This study demonstrates the importance of incorporating geological heterogeneity into groundwater modelling and environmental risk assessments associated with the storage of LNAPLs.

Climate change impact on groundwater resources in sandbar aquifers in southern Baltic coast

Shallow coastal aquifers are vulnerable hydrosystems controlled by many factors, related to climate, seawater-freshwater interactions and human activity. Given on-going climate change, sea level rise and increasing human impact, it is especially true for groundwater resources situated in sandbars. We developed numerical models of unsaturated zone water flow for two sandbars in northern Poland: the Vistula Spit and the Hel Spit using HYDRUS-1D. The simulations were performed for three types of land use: pine forest, grass cover and bare soil, for 2024–2100 based on weather data and sea level rise forecasts for two emissions scenarios (RCP 4.5 and RCP 8.5). The results present prognosis of groundwater recharge, water table level and water content changeability in near-term (2023–2040), mid-term (2041–2060), and long-term period (2081–2100). Expected sea level rise and decreasing hydraulic gradient of the sandbar aquifers will probably cause in-land movement of the freshwater–saltwater interface, leading to significant decrease or complete salinization of groundwater resources. The study shows that holistic monitoring including groundwater level and salinization, sea level rise, and metheorological data (precipitation amount and variability, temperature) is crucial for sustainable management of vulnerable aquifers located in sandbars.

The contraction of freshwater lenses in barrier island: A combined geophysical and numerical analysis

Coastal aquifers, vital for supplying freshwater to over one billion people worldwide, often face saltwater intrusion, with barrier island aquifers playing a crucial role in this coastal system. Despite the proliferation of studies exploring the impacts of sea-level rise, storm surges, and over-pumping, the effect of droughts on barrier island aquifers salinization remains largely under-investigated. This lack of attention is particularly concerning given the heightened vulnerability of barrier island aquifers; most ultimately rely solely on aerial recharge compared to continental coastal aquifers. An in-depth understanding of recharge and salinization processes is important for sustainably managing these islands' marginal freshwater resources, especially considering climate change impacts. This study presents an evaluation approach for the response of a freshwater lens (FWL) to drought conditions, incorporating in-situ observations, geophysical measurements, and numerical modeling. The study examines the response of a shallow unconfined aquifer on an Atlantic coast barrier island to the 2020 Northeast extreme hydrological drought. It encompasses a density-driven flow model informed by time-lapse electrical resistivity imaging and in-situ measurements, including groundwater head and salinity collected from monitoring wells. Results from our approach indicate that FWL volume is reduced by 11% during the drought, but it returns to its previous volume over the following spring season, indicating that the net volume of the FWL remains unchanged on an annual scale. The mean groundwater residence time on the island is approximately a year, indicating that the barrier island aquifer is a hydrodynamically active coastal zone. These findings highlight the vulnerability and resilience of shallow unconfined barrier island aquifers to droughts and climate change.

Predictive analysis of groundwater balance and assessment of safe yield using a probabilistic groundwater model for the Dead Sea Basin

Predictive analysis of groundwater balance and assessment of safe yield using a probabilistic groundwater model for the Dead Sea Basin

Mechanism controlling groundwater chemistry in the hyper-arid basin with intermittent river flow: insights from long-term observations (2001–2023) in the lower Heihe River, Northwest China

The geochemical processes of groundwater in arid regions are generally influenced by both natural hydrological processes and human activities. However, impacts of water-rock interactions on groundwater recharge via hydrological processes, controlled by both intermittent river water flow and groundwater withdrawals, is still poorly understood. In this study, 327 groundwater chemistry datasets collected from the upper, middle (including Gobi and riparian zones), and lower regions of the Ejina Delta in Northwest China from 2001 to 2023 were analyzed. Our results revealed that the total dissolved solids (TDS) concentration of groundwater in Ejina Delta ranged from approximately 881.5 ± 331.6 mg/L in the upper regions to 1,953.6 ± 1,208.5 mg/L in the lower regions, with an increasing trend observed. Ecological water conveyance (EWC), recharging aquifer through intermittent river water flow, resulted in a decrease in TDS concentrations from 2001 to 2023 mainly in the upper region. While irrigation notably affected groundwater chemistry in the lower region, resulting in a substantial increase in groundwater salinity. Groundwater chemistry in the Middle Gobi region remained relatively stable over the study period. Generally, the hydrochemical composition shifted from the Na-Mg-SO4-HCO3 and Na-Mg-Ca-SO4-HCO3 types in the upper region to Na-Mg-SO4-HCO3 and Na-Mg-SO4-Cl types in the lower region, with Na-SO4-Cl predominant in the Middle Gobi. These shifts were likely be attributed to the interplay of water-rock interactions, coupled with evaporation-crystallization processes. Inverse modeling using PHREEQC revealed that in the upper-middle region, primary water-rock interactions involved calcite dissolution and the precipitation of dolomite, gypsum, halite, and sylvite salts, as well as cation exchange reactions (2NaX+Ca2+→CaX2+2Na+). In contrast, the hydrogeological system in the middle-lower region exhibited an opposite pattern of water-rock interactions. Overall, ecological water conveyance partially facilitated water-rock interactions during lateral groundwater flow, while irrigation disrupted the natural hydrogeochemical equilibrium, involving halite dissolution and opposite cation exchange reactions compared to other regions.

Alternate use of fresh and saline waters to improve water productivity and soil sustainability of drip irrigated wheat in a semi-arid region

Severe problems of rising groundwater and secondary soil salinization demand holistic agricultural water management in canal command areas. Drip irrigation with alternate use of fresh and saline waters is an excellent irrigation approach to mitigate salinity stress caused by highly saline ground water and also to avoid soil sodicity hazards from canal water. Therefore, a study on cyclic mode conjunctive use of good quality surface water (SW) and highly saline ground water (GW) having average electric conductivity 0.3 and 7.6 dS m−1, respectively was carried out in wheat with five treatments of drip viz. 1SW1GW (1:1 :: SW:GW), 1SW2GW (1:2 :: SW:GW), 2SW1GW (2:1 :: SW:GW), SW (all SW), GW (all GW), and one treatment of conventional border ­irrigation method (BI). Highest grain yield was observed in SW (2.99 t ha−1) in 2017–2018 and BI (3.83 t ha−1) in 2018–2019 season. However, yield of SW and BI were statistically at par in both seasons. Grain yield of 1SW1GW, in which only 50% freshwater was used was found statistically at par with SW and BI. Physical Water Productivity was highest for SW, amounting 9.34 and 14.13 kg ha−1.mm−1 during 2017–2018 and 2018–2019, respectively. Soil salinity build up was highest for GW and lowest for SW, whereas it was almost similar for BI and 1SW1GW. Thus, 1SW1GW showed added benefits as its grain yield was statistically at par with SW and BI along with 50% fresh water saving over SW and higher water productivity than BI for similar salinity levels.

Introducing a novel approach for assessment of groundwater salinity hazard, vulnerability, and risk in a semiarid region

The application of machine learning approaches to improve groundwater salinity risk mapping is limited despite all potential advantages. Therefore, there is an ongoing need for investigations that present new techniques, like machine learning, validated against conventional methods. These advances are particularly important for arid and semiarid regions, such as the Bakhtegan Basin (southern Iran), where groundwater use may far outweigh recharge, but groundwater management improvements are essential. To address these needs, groundwater salinity hazard, vulnerability, and risk maps were investigated using an integrated application of statistical (i.e., frequency ratio and statistical index models), machine learning (i.e., random forest and classification and regression trees algorithms), and decision-making models (fuzzy analytic hierarchy process (FAHP)). Results showed that the risk of groundwater salinity was high in the central areas of the region as well as at the margins of Bakhtegan Lake and irrigated farming lands. Based on the modeling results in the testing phase, it was found that the frequency ratio and random forest models exhibited better performance, with Nash–Sutcliffe efficiency metrics of 0.73 and 0.70, respectively, compared to the classification and regression trees and statistical index models, which had Nash–Sutcliffe efficiency metrics of 0.65 and 0.63, respectively. The innovative techniques developed in the current work accurately identified variables such as normalized difference salinity index, distance from mines, and land use associated with the highest weight values (0.59, 0.14, and 0.11, respectively) compared to other variables to identify groundwater salinity areas of vulnerability. The application of the fuzzy analytic hierarchy process method in developing vulnerability maps, integrating them with hazard maps, and developing groundwater salinity risk maps was innovative in this study. The innovative approach is transferrable for groundwater salinity susceptibility, vulnerability, and risk assessments globally in the study area and similar settings.

Geochemistry of Arsenic and Salinity-Contaminated Groundwater and Mineralogy of Sediments in the Coastal Aquifers of Southwest Bangladesh

This study aimed to develop a geochemical database by thoroughly analyzing groundwater and sediments from coastal aquifers of southwest Bangladesh. Moreover, we investigated the source of sediment deposition and the mechanisms behind the presence of arsenic and salinity in groundwater. The seasonal distribution patterns of arsenic among the shallow and deep coastal aquifers were found to be 45.12 µg/l and 20.65 µg/l during dry and wet seasons, respectively. Moreover, the groundwater salinity distribution ranged from 3262.88 mg/l to 1930.88 mg/l during the dry and wet seasons. Cored sediment samples showed fine to medium sands of 92%, with silt and clay particles. The petrographic study of authigenic and heavy minerals revealed that the mineral grains were subangular to angular, indicating their textural immaturity of coastal sediments. The reactivity of goethite (FeOOH) and siderite (FeCO3) minerals suggests that the aquifers were subjected to slightly oxidized to moderately reducing conditions, with ORP values ranging from +50.40 mv to −149.5 mv. Such redox conditions could potentially result in the enrichment and mobility of arsenic in the groundwater. Although arsenic concentrations in deep aquifers are relatively low, higher salinity values are found in both shallow and intermediate coastal aquifers.