Groundwater Model Research Articles

Hydrogeochemical characteristics of shallow groundwater and salinization evaluation in the coastal aquifers of Cangzhou, China

To investigate the hydrogeochemical characteristics of shallow groundwater and evaluate groundwater salinization state in Cangzhou, China, two sampling campaigns have been conducted. In summer, 33 groundwater samples, 3 seawater samples and 5 river water samples were collected. In winter, 22 groundwater samples were collected. The hydrochemical type was determined by the Piper diagram. Evolution mechanisms of groundwater were analyzed by the Gibbs diagram. The trend of de-salinization or salinization of groundwater was determined by the hydrochemical facies evolution diagram. The groundwater salinization grade was evaluated by both the seawater intrusion groundwater quality index (GQISWI) and the attribute recognition model based on entropy weight (ARMEW). The Piper diagram shows that Na+ is the dominant cation and Cl- is the dominant anion in shallow groundwater, and the groundwater in this area is mainly of Cl-Na type followed by Cl-Ca·Mg type. The evaporation-crystallization process has significant influence on the evolution of saline groundwater. In summer, most brackish groundwater exhibit compositions of the freshening stage with direct cation exchange, and most saline groundwater is mainly at the seawater intrusion stage with reverse cation exchange. In winter, compared to the summer season, more groundwater samples in the middle of study area exhibit intrusion trend, and without obvious Na-HCO3 facies. In summer, values of GQISWI range from 20.47 to 75.38 with an average of 59.31. The GQISWI gradually increases from east to west, denoting the degree of groundwater salinization is alleviated from coast to inland. In winter, values of GQISWI range from 54.47 to 79.09 with an average of 66.00, slightly higher than that in summer. The proportion of no salinization (Grade I), minor salinization (Grade II) and serious salinization (Grade III) of groundwater samples in Cangzhou identified by ARMEW is 3.0%, 21.2% and 75.8% in summer, respectively. In winter, the proportion is 9.1% for Grade II and 90.9% for Grade III. The GQISWI index shows the largest area of Grade II, and ARMEW presents the largest area of Grade III in both seasons. Compared with GQISWI index, ARMEW model gives more conservative evaluation results of groundwater salinization. The results provide useful information on the groundwater salinization status for the local area, and help for the management of groundwater resources in Cangzhou.

Assessing the suitability of desalination techniques for hydraulic barriers

Seawater intrusion is a worldwide increasing challenge, which lowers the freshwater availability by salination of fresh groundwater resources in coastal areas. The abstraction-desalination-recharge (ADR) methodology can combat seawater intrusion, whereby desalination is hereby the key factor for the overall efficiency of aquifer remediation. Which desalination technique is suitable within ADR depends on several factors and was not discussed before. We use a multi-criteria decision analysis and cost analysis to compare nanofiltration, reverse osmosis, electrodialysis, and (membrane) capacitive deionization and show for three case scenarios which desalination technique is most suitable within ADR. Overall, electrodialysis, nanofiltration, and reverse osmosis have shown the best utility value for saline groundwater salinity of 1–10 g L−1, whereby electrodialysis is more suitable for lower salinities. The lowest desalination costs are calculated for nanofiltration and reverse osmosis with 0.3–0.6 € m−3 depending on specific energy costs. Even capacitive deionisation can be a suitable alternative for low, slightly saline groundwater (1 g L−1) if the technology readiness level and a lifetime of electrodes increase and material costs decrease. These new insights provide a data analysis, costs, and decision support for desalination which are needed for the holistic approach to counteract seawater intrusion.

Short rotation willow to restore degraded marginal land and enhance climate resiliency within the Prairie Pothole Region: A potential nature-based solution

Short rotation willow (SRW) is a land management strategy involving the cultivation of rapidly growing, biomass-rich herbaceous-woody plants. This practice holds promise for renewable energy production, water quality preservation, carbon sequestration, greenhouse gas (GHG) mitigation, enhancement of soil extracellular enzyme activities (EEAs), and promotion of overall soil health. The rapid growth of SRW demands substantial water and nutrient resources, posing concerns when cultivated in marginal riparian lands within the Prairie Pothole Region (PPR), potentially leading to alterations in groundwater table (GWT) depth fluctuations, elevated soil salinity levels, and disruptions to biogeochemical cycles. Hence, this study comprehensively evaluated the effects of establishing SRW as a degraded marginal riparian land use practice in the PPR and attempted to answer several vital questions in the field and microcosm scale on soil hydrology, salinity, nutrients, soil organic carbon (SOC), GHG emissions, and EEAs involved in biogeochemical cycling. In a field experiment, the effects of SRW were evaluated by measuring the depth to GWT, groundwater and soil electrical conductivity (EC), macronutrients (N, P, K, and S), and SOC content in different fractions and chemical compositions during the first rotation (3-year cycle) compared with adjacent annual crop and pasture in two semi-arid PPR sites. In a microcosm experiment, GHG (CO2, CH4, and N2O) emissions and EEAs [β-glucosidase (BG), N-acetyl glucosaminidase (NAG), and alkaline phosphatase (AP)] were measured in intact soil cores treated with declining water tables and different groundwater salinity levels. No consistent land use impacts on GWT or soil EC were observed between sites. Land use in site B significantly impacted GWT depth, implying site-specific factors, such as topography and soil characteristics, may be dominant over land use effects. Under SRW, the levels of macronutrients in the soil varied but did not significantly reduce the overall nutrient content of the soil. Total SOC was highest in pasture; light fraction organic carbon and particulate organic carbon followed a similar land use pattern, i.e., pasture > SRW = annual crop. Land uses affected GHG emissions significantly in the order of pasture > annual crop = SRW. GHG emission varied with salinity and GWT but there was no interaction with land use practices. Soil EEAs were significantly impacted by different land uses, i.e., pasture > annual crop = SRW, suggesting that the effects resulted from associated SOC. Our microcosm experiment suggests that the SRW land use practice holds promise as a sustainable Nature-Based Solution for enhancing climate resiliency in PPR. It exhibits a lower global warming potential compared to annual crop and pasture. Therefore, widespread implementation of the SRW land use practice in degraded marginal land could help mitigate the effects of climate change in the region.

A millennium-long perspective on recent groundwater changes in the Iberian Peninsula

Groundwater dynamics are often overlooked within historical climatology because of their complexity and the influence of multiple factors. This study presents a groundwater model for Spain, using an existing tree-ring based summer drought reconstruction to estimate the groundwater depth in Castile and León (northwestern Spain) over the 1056–2020 CE period. Spanish groundwater volume fluctuations are found to be associated with quasi-decadal variations in the North Atlantic and Pacific Oceans. The reconstructed annual groundwater depth shows significant oscillations around a mean value of 123 m. Changes in groundwater depths include a wet medieval period ( ~ 1056–1200 CE), recurring megadroughts during parts of the Little Ice Age (~1471–1600 CE), and unprecedentedly large variations during recent decades. Aligning with previous studies for the Iberian Peninsula, our new modelling approach highlights the need to enhance groundwater resilience in anticipation of potentially worsening future drought trends across the Mediterranean.

The Effect of Saltwater Stress on the Performance of Cherry Tomatoes

Rising sea levels and saltwater intrusion in aquifers pose significant challenges for South Florida agriculture, leading to increased groundwater salinity and potential crop losses. Utilizing salttolerant crop species presents a potential solution for saline soils and regions with active saltwater intrusion. However, the effects of soil salinization through groundwater alone remains less studied. This research investigates the impact of short-term, below-ground saltwater stress on the growth, survival, and overall health of commonly grown cherry tomatoes (Solanum lycopersicum). The objectives of the study are to: 1) determine the impact of saline groundwater on tomato plant health and 2) compare the nutrient content of soil and tomato plant tissue exposed to varying concentrations of saline water. Established cherry tomato plants were exposed to varying concentrations of NaCl solution, simulating saltwater intrusion into groundwater. Over 28 days, plant height, leaf chlorophyll levels, and disease occurrences were monitored. It was found that the NaCl treatments did not significantly affect cherry tomato performance under the parameters of height, chlorophyll levels, or leaf nutrition when compared to the control group. This study suggests that cherry tomatoes can tolerate short-term exposure to NaCl in groundwater. Further exploration of more intense salt stress conditions from groundwater could be beneficial for utilizing this crop in areas with saline soils or polluted groundwater. Identification of salt-tolerant cherry tomato varieties can provide alternative crop options for non-arable land affected by high soil salinity.

Assessing salinity hazards in coastal aquifers: implications of temperature boundary conditions on aquifer–ocean interaction

Investigating the repercussions of climate change and irrigation timing on groundwater contamination necessitates thorough examination of the fluctuations in seawater and groundwater recharge temperature. This study introduces an innovative numerical approach to analyze groundwater salinity and temperature dynamics across three distinct scenarios using the SEAWAT code based on Henry's problem. The first scenario delves into the impact of seawater temperature, the second focuses on the consequences of aquifer freshwater recharge temperature, and the third amalgamates the effects of both scenarios. Remarkably, the study reveals that saltwater intrusion (SWI) experiences a decline attributable to the aquifer's heightened seawater temperature and the diminished inland freshwater temperature. Furthermore, combining these two scenarios has a more pronounced effect on aquifer pollution; the temperature-induced changes in SWI for this third scanrio reach + 8.10%, + 12.70%, + 16.20%, + 24.90%, + 28.30%, and + 31.80% compared to the case without considering the temperature effect. Notably, our results propose a potential strategy to mitigate SWI by introducing cold freshwater recharge into aquifers, such as irrigation at night time when water temperature is low. This innovative approach underscores the interconnectedness of various environmental factors. It provides a practical avenue for proactive intervention in safeguarding groundwater quality against the adverse impacts of climate change and irrigation practices.

Joint identification of groundwater pollution source information, model parameters, and boundary conditions based on a novel ES-MDA with a wheel battle strategy

Groundwater pollution source identification (GPSI) is an important prerequisite for pollution remediation and risk assessment. However, an accurate GPSI is usually difficult to achieve due to the need to simultaneously consider practical problems and theoretical research. For practical problems, the boundary conditions, especially the concentration boundary, are often given as known constants through prior information. However, in most practical situations, the boundary conditions are complex and cannot be accurately estimated in advance, which leads to the distortion of the final identification results. Therefore, this study focused on the concentration boundary, and first proposed to jointly identify three types of unknown variables (source information, model parameters, and boundary conditions) to ensure that the identification results had more practical value. For theoretical research, as the number of unknown variable types increases, the difficulty of solving the inverse problem often increases, which may lead to inaccurate inversion results. Thus, a novel ensemble smoother with multiple data assimilation (ES-MDA) with a wheel battle strategy was proposed, enhancing the identification accuracy. We designed two cases to verify the effectiveness and practicality of the above ideas: a low-dimensional Case 1 (including four different synthetic scenarios: three scenarios with unknown boundary conditions under three concentration boundary modes and a scenario with known boundary conditions) and a high-dimensional complex Case 2. Identifying the boundary conditions in GPSI was found to be of great significance. Compared to the standard ES-MDA method, the ES-MDA with a wheel battle strategy proposed here could improve the inversion accuracy, and had certain effectiveness and practicality.

Co-occurrence of elevated arsenic and fluoride concentrations in Wuliangsu Lake: Implications for the genesis of poor-quality groundwater in the (paleo-)Huanghe (Yellow River) catchment, China

The co-occurrence of high As and F concentrations in saline groundwater in arid and semi-arid regions has attracted considerable attention. However, the factors determining the elevated concentrations of the two elements in surface water in these regions have not been sufficiently studied, and their implications for the poor-quality of local groundwater (high levels of As, F, and salinity) are unknown. A total of 18 water samples were collected from Wuliangsu Lake, irrigation/drainage channels, and the Huanghe (i.e., Yellow River) in the Hetao Basin, China. The pH, concentrations of As and F as well as those of other major elements, and stable isotope (H and O) compositions were analyzed. The water samples had a high pH (7.85–9.01, mean 8.25) and high TDS (402–9778 mg/L, mean 1920 mg/L) values. In six of the 10 lake samples, As concentration was above 10 μg/L (maximum 69.1 μg/L) and, in one of them, F concentration was above 1.5 mg/L. Interestingly, the high As, F, and TDS values simultaneously detected in the lake water were similar to those previously reported in local groundwater, and all water samples showed a significant positive correlation between As and F concentrations (R2 = 0.96, p < 0.01), except for two samples with abnormally high Ca2+ levels. The results of stable isotope analysis and Cl/Br ratios suggested that the lake experienced strong evaporation, which is consistent with the high TDS values. Evaporative concentration is suggested as the main factor contributing to the elevated As and F concentrations in the lake water. In addition, the major ions (e.g., Na+, Cl−, HCO3−, and OH−) and pH in the lake water increased during evaporation, leading to desorption of As and F. Thus, the evaporation process, including evaporative concentration and desorption, was considered primarily responsible for the elevated As and F in the lake water. Based on the results of this study, we presume that the paleolakes in the study area have experienced intense evaporation process. As a result, As, F, and major elements accumulated in sediments (or residual lake water) and were buried in the fluvial basins; then, they were released into the groundwater through multiple (bio)hydrogeochemical processes. By combining the results of this study with those obtained from previous groundwater analyses, we propose a new hypothesis explaining the origin of elevated As and F concentrations in saline groundwater in arid and semi-arid regions.

Groundwater salinization risk in coastal regions triggered by earthquake-induced saltwater intrusion

Anthropogenic factors such as over-pumping and natural events such as earthquakes impact coastal aquifers by reducing freshwater recharge, aquifer water budgets, and increasing saltwater intrusion (SWI). This study investigates the impact of hydrodynamic forces induced by earthquakes on SWI in one hypothetical case, namely, the Henry problem, and a real case of the Biscayne aquifer located in Florida, USA. The analysis was carried out using the analytical solution of estimating the earthquake’s induced hydrodynamic pressure and applying the SEAWAT code to investigate the SWI for the base case and three scenarios, namely for the horizontal acceleration (αh) by 0.10 g, 0.20 g, and 0.30 g. The results show that earthquakes might considerably increase the SWI in coastal aquifers. Moreover, the rise in salinity across expansive land areas significantly threatens agricultural productivity and jeopardizes food security. Namely, in the case of Biscayne aquifer, salinity was increased by 12.10%, 21.90%, and 45.70% for the horizontal seismic acceleration of 0.1 g, 0.20 g, and 0.30 g, respectively. Hence, the conclusions drawn from this study underscore the need for carefull consideration of earthquake impacts in future planning and water management strategies for coastal regions. This proactive approach is crucial to preemptively address and mitigate the groundwater salinization hazard associated with SWI fluctuations due to earthquakes.

Transferability of Machine Learning Models for Geogenic Contaminated Groundwaters.

Machine learning models show promise in identifying geogenic contaminated groundwaters. Modeling in regions with no or limited samples is challenging due to the need for large training sets. One potential solution is transferring existing models to such regions. This study explores the transferability of high fluoride groundwater models between basins in the Shanxi Rift System, considering six factors, including modeling methods, predictor types, data size, sample/predictor ratio (SPR), predictor range, and data informing. Results show that transferability is achieved only when model predictors are based on hydrochemical parameters rather than surface parameters. Data informing, i.e., adding samples from challenging regions to the training set, further enhances the transferability. Stepwise regression shows that hydrochemical predictors and data informing significantly improve transferability, while data size, SPR, and predictor range have no significant effects. Additionally, despite their stronger nonlinear capabilities, random forests and artificial neural networks do not necessarily surpass logistic regression in transferability. Lastly, we utilize the t-SNE algorithm to generate low-dimensional representations of data from different basins and compare these representations to elucidate the critical role of predictor types in transferability.

Enhanced groundwater availability through rainwater harvesting and managed aquifer recharge in arid regions

Climate change in desert areas and semi-arid watersheds may offer a promising solution for the water scarcity problem that Bedouins and local inhabitants face. This study investigated the integrated water resources management in arid and semi-arid regions using rainwater harvesting in combination with the managed aquifer recharge (RWH-MAR) technique. The study also used recharge wells and storage dams to achieve the sustainability of groundwater supplies in the context of climate change and management of the flow to the Gulf of Suez. Therefore, different return periods of 10, 25, 50, and 100 years were considered for the annual flood volume resulting from those watersheds. Moreover, hydrologic modeling was carried out for the El Qaa plain area, South Sinai, Egypt, using the Watershed Modeling System (WMS) and the groundwater modeling of SEAWAT code. Our findings show that for different scenarios of climate change based on return periods of 10, 25, 50, and 100 years, the aquifer potentiality reached 24.3 MCM (million cubic meters) per year, 28.8 MCM, 36.7 MCM, and 49.4 MCM compared to 21.7 MCM at 2014 with storage of groundwater ranges 11.8%, 32.1%, 69%, and 127.4%, respectively. These findings have significant implications for the system of RWH-MAR and groundwater sustainability in El Qaa Plain, South Sinai. The RWH-MAR proved to be an effective approach that can be applied in different water-stressed and arid regions to support freshwater resources for sustainable future development and food security, as well as protect communities from extreme flash flood events.

Groundwater recharge potential zone modeling in the Wadi Al-Lith Basin, Saudi Arabia

The management of groundwater resources is crucial in arid and semi-arid regions such as Al-Lith Basin, and therefore, the identification of suitable areas for groundwater recharge is important in solving the problem of water scarcity and ensuring the long-term sustainability of aquifers. In this study, the Analytic Hierarchy Process (AHP) technique, in conjunction with GIS, was applied to locate potential zones for groundwater recharge in the Al-Lith basin. The research methodology includes collecting the essential data, including lineament density, slope, rainfall, drainage density, LU/LC, soil, elevation, and TWI. AHP is used to assign relative weights to different qualities, considering their significance in influencing groundwater recharge. The ArcGIS was employed to process and analyze the weighted layers, which resulted in the creation of a comprehensive map illustrating the potential for groundwater recharge. The study results suggested that the Al-Lith Subbasin has several zones that exhibit different levels of groundwater recharge capability. The results obtained from this study indicated that 12.83% of the basin area has significant groundwater recharge potential zones (GWPZ), ranging from high to very high levels. The groundwater recharge potential zones in the basin are categorized as very poor to poor, covering 19.4% of the area, while the moderate groundwater recharge potential zones represent 67.77% of the basin area. The groundwater protection zones were validated using 19 wells distributed across the basin. The validation findings indicate there is an overlap between the GWPZ classes and the wells in the specified location. Overall, the findings of this study can enhance groundwater resource management and inform policy development for targeted interventions aimed at enhancing groundwater recharge.

Enhancing hydrological insight: isotopic methods revealing groundwater–surface water interactions in the Lower Quang Tri River Group, Vietnam

ABSTRACT The Lower Quang Tri River Group, situated in central Vietnam, faces a myriad of challenges, notably the decline in groundwater levels and the salinisation of both groundwater and surface water, significantly impacting water availability for domestic, agricultural, and industrial purposes. To address these pressing concerns, this study adopts a comprehensive methodology integrating hydrogeological measurements, isotopic techniques, and chemical analyses of various water sources, including local precipitation, surface water bodies, reservoirs, and groundwater samples. Utilising the deuterium and oxygen-18 signatures (δ 2H and δ 18O) in water molecules as environmental tracers for the assessment of base flow and water sources enables a nuanced understanding of the intricate interaction between surface water and groundwater. Research findings elucidate that during the dry season, groundwater recharge primarily stems from water in the reservoirs over approximately seven months. Base flow contributes between 80 and 85 % of streamflow during the rainy season, escalating to 100 % during the dry season. The mean travelling time of the base flow is estimated at 120 ± 10 days using the sine curve model developed by Rodgers et al. The insights gleaned from this study are poised to play a pivotal role in guiding the local water resources managers in licensing for the exploitation of a right quantities of groundwater as sustainable management strategies in the region.

Water, Salt, and Ion Transport and Its Response to Water-Saving Irrigation in the Hetao Irrigation District Based on the SWAT-Salt Model

Soil salinization is one of the main hazards affecting the sustainable development of agriculture in the Hetao Irrigation District (HID) of Inner Mongolia. To grasp the water and salt transport patterns and spatial–temporal distribution characteristics of the HID at the regional scale, the improved Soil and Water Assessment Tool with a salinity module (SWAT-Salt) model was used to establish the distributed water and salt transport model for the watershed in this study. The results demonstrated that the modified model could more accurately represent the process of water and salt changes in the HID. The coefficient of determination (R2) in the simulation of streamflow and discharge salt loading was 0.83 and 0.86, respectively, and the Nash–Sutcliffe efficiency (NSE) was 0.80 and 0.74, respectively. Based on this, different hydrological processes (surface runoff, lateral flow, groundwater, soil seepage) as well as spatial–temporal distribution characteristics of water salinity in groundwater and soil were analyzed in the HID. Differences in groundwater and soil salinity in different land uses and soil types were also compared. Of these, surface runoff and lateral flow salt discharge loading are concentrated in the southwestern portion of the basin, while groundwater salt discharge loading is concentrated in the eastern as well as southwestern portions of the basin. The salt discharge loading from groundwater accounts for about 98.7% of the total salt discharge loading from all hydrological pathways and is the major contributing part of salt discharge from the irrigation area. Soil salinity increases gradually from west to east. Groundwater salinity (2946 mg/L) and soil water electrical conductivity (0.309 dS/m) were minimized in the cropland. Meanwhile, rational allocation of irrigation water can appropriately increase the amount of salt discharge loading. In conclusion, the model could provide a reference for the investigation of soil salinization and water–salt management measures in irrigation areas.

Experimental-based groundwater salinization from the carbonate aquifer of eastern Saudi Arabia: Insight into machine learning coupled with meta-heuristic algorithms

Groundwater (GW) salinization of coastal aquifers has become a serious problem for attaining sustainable water resource management in Saudi Arabia and other parts of the world. Therefore, it is crucial to assess the extent of this salinization to protect and manage our water resources effectively. This research proposed real fieldwork GW samples at several locations supported with experimental based on chromatography (IC) and inductively coupled plasma mass spectrometry (ICP-MS) to analyze several GW physical, chemical, and hydro-geochemical elements. In this study, we model GW salinization with machine learning algorithms such as support vector regression, gaussian process regression, artificial neural networks, and least squares ensemble boosting regression tree. The performance of the standalone models was optimized with metaheuristic optimization-based algorithms such as fuzzy hybridized genetic algorithm (ANFIS-GA) and particle swarm optimization (ANFIS-PSO). The outcomes based on three variable input combinations were validated using several performance indicators and graphical methods. The quantitative analysis indicated that GPR-Combo1(MAE = 0.006 mg/L), Ensm- Combo2 (MAE = 0.025 mg/L), and GPR- Combo3 (MAE = 0.078 mg/L) proved merit among the standalone combinations. Where combo 1, 2, and 3 stand for model combinations derived from feature selection. The cumulative probability function (CPF) demonstrated that heuristic optimization ANFIS-GA (MAE = 0.0025 mg/L, MAPE = 0.19183) and ANFIS-PSO (MAE = 0.0018 mg/L, MAPE = 0.0723) outperformed the standalone error accuracy and served reliable approach. Both the standalone models and heuristic algorithms used for GW salinization modeling have demonstrated promising results in accurately predicting salinity. This approach could aid in effectively managing the GW resources for sustainable development.

Soil Organic Matter Input Promotes Coastal Topsoil Desalinization by Altering the Salt Distribution in the Soil Profile

Organic amendment is an effective method to reclaim salt-affected soil. However, in coastal land with shallow saline groundwater, it is limited known about the mechanism of organic amendment on soil desalinization. Thus, to examine the effect of topsoil organic matter content on soil water/salt transport and distribution, two-year field observations in Bohai coastal land, North China, and soil column experiments simulating salt accumulation and salt leaching were conducted, respectively. There were different organic fertilizer amendment rates in 0–20 cm topsoil, 0% (CK), 50% (OA 0.5), and 100% (OA 1.0) (w/w) for soil column experiments. Field observation showed that after organic amendment (OA), the soil’s physical structure was improved, and less of the increase in topsoil salt content was observed, with more salt accumulated in deep soil layers during the dry season. In addition, OA greatly promoted salt leaching during the rainy seasons. The results of the soil column tests further indicated that OA treatments significantly inhibited soil evaporation, with less salt accumulated in the topsoil. Although there was no difference in soil water distribution between the CK and OA 0.5 treatment, the topsoil EC for the OA 0.5 treatment was significantly lower than that for CK. During soil water infiltration, the OA 0.5 and OA 1.0 treatments significantly increased the infiltration rates, enhanced the wetting front, and promoted salt leaching to deeper soil layers, compared with CK. The improvement of soil organic amounts could make the soil more self-resistant to the coastal salinization. The findings of this study provide some insights into soil water/salt regulation in heterogeneous soil masses and on the permanent management of coastal saline farmland.

Groundwater salinization risk assessment using combined artificial intelligence models.

Assessing the risk of groundwater contamination is of crucial importance for the management of water resources, particularly in arid regions such as Menzel Habib (south-eastern Tunisia). The aim of this research is to create and validate artificial intelligence models based on the original DRASTIC vulnerability methodology to explain groundwater salinization risk (GSR). To this end, several algorithms, such as artificial neural networks (ANN), support vector regression (SVR), and multiple linear regression (MLR), were applied to the Menzel Habib aquifer system. The results obtained indicate that the DRASTIC Vulnerability Index (VI) ranges from 91 to 141 and is classified into two categories: low and moderate vulnerability. However, the correlation between groundwater total dissolved solids (TDS) and the Vulnerability Index is relatively weak (r < 0.5). Indeed, the original DRASTIC index needs some improvements. To improve it, some adjustments are required, notably by incorporating the TDS-groundwater salinization risk (GSR) indicator. The seven parameters of the original DRASTIC model were used as inputs for the artificial intelligence models, while the GSR values were used as outputs. Performance indicators, such as the correlation coefficient (r) and the Willmott Agreement Index (d), showed that the ANN model outperformed the SVR and MLR models. Indeed, during the training phase, the ANN model obtained r values equal to 0.89 and d values of 0.4, demonstrating the superiority, robustness, and accuracy of ANN-based methodologies over the original DRASTIC model. The findings could provide valuable information to guide management of groundwater contamination risks, especially in arid regions.

Water Resource Management of Salalah Plain Aquifer Using a Sustainable Approach

A sustainable approach is proposed for managing the effects of salinity ingression in Salalah coastal aquifer, Oman. This paper aims to analyze and compare the groundwater levels and salinity of the aquifer from 1993 to 2027, considering both predictive and actual transient scenarios. Two novel scenarios were proposed, established, and examined in this study to bring back the aquifer to steady-state condition. The first scenario entails ceasing groundwater pumping from both Salalah and Saada wellfields, while compensating for the groundwater supply from these sources with surplus desalinated water. This scenario is projected to occur during the predictive period spanning from 2023 to 2027, denoted Scenario A. The second scenario is business as usual and involves continuing pumping from both wellfields during the same predictive period, denoted Scenario B. A numerical model for 3D flow simulation and advective transport modeling showed that on the eastern side of the Salalah coastal aquifer, the extent of seawater intrusion (SWI) was identified stretching from the shoreline to a distance of 1800 m, 1200 m, 0 m, and 600 m, in years 2011, 2014, 2018, and 2022 under the transient period, whereas SWI was delineated in land up to 0 m and 700 m in the predictive year 2027 under Scenarios A and B, respectively. In the western side of Salalah coastal aquifer, SWI was delineated in land up to 2000 m, 1700 m, 0 m, and 800 m, in years 2011, 2014, 2018, and 2022 under the transient period, whereas SWI was delineated in land up to 0 m and 750 m in the predictive year 2027 under Scenarios A and B, respectively. This study claims that Scenario A effectively pushed the seawater interface back to the coastline, projecting its reach to the shoreline (0 m) by 2027. In contrast, in baseline Scenario B, the wedge of saline intrusion in the Salalah coastal aquifer was delineated from the shoreline, up to 800 m inland, which accounted for continuation of pumping from both wellfields during the predictive period. The study concludes that Scenario A has the capability to efficiently reduce the impact of saline inflows from the coast, while Scenario B results in a more pronounced impact of salinity intrusion.

Pore fluid salinity effects on post-stabilization performance of cement-treated Marl

Soil improvement using chemical admixtures has been extensively investigated in the recent past and these admixtures are abundantly being used on various construction projects. However, there is a need to elucidate the long-term performance of stabilized geomaterials under aggressive pore fluid environments such as high salinity of groundwater in coastal areas. This study presents the effects of the concentration of pore fluid salinity on the post-stabilization behavior of cement-treated Marl specimens to brine solution from Sabkha deposits and rejected water from a water treatment plant. Unconfined compressive strength (UCS), mineralogy, chemical, and microstructural evaluations have been carried out in this regard. minerals like albite and muscovite completely leached out of the samples after 28 days of soaking in a saline environment. A new mineral Attapulgite was formed at various concentration levels of the pore fluid. Significant changes in the chemical composition were also observed in various phases of the experiments. Moreover, at all salinity levels, the UCS initially increased to a maximum of 75 % which later reduced to a value less than the original strength whereas the elastic modulus (E50) increased as the soaking period progressed. Lastly, it is emphasized that the engineering properties of treated soils exposed to aggressive pore fluids should be carefully assessed for a reliable prediction of the long-term performance of geotechnical structures.

Improving land surface feedbacks to the atmosphere in convection-permitting climate simulations for Europe

We investigated positive temperature (warm) and negative precipitation (dry) biases in convection-permitting model (CPM) simulations for Europe (2.2 km grid spacing) that were considerably larger than in equivalent regional climate model (RCM) simulations (12 km grid spacing). We found that improvements in dry biases could be made by (1) using a more complex runoff scheme which takes into account topography and groundwater, (2) delaying the onset of water stress in vegetation to enhance transpiration, (3) changing the microphysics scheme to CASIM (Cloud AeroSol Interacting Microphysics) which also decreases heavy rainfall and increases light rainfall. Increasing soil moisture to the critical point can remove dry precipitation biases in southern Europe but not in northern areas, indicating that soil moisture limitation is a key contributor to precipitation biases in the south only. Instead, in the north, changing the cloud scheme of the model has more impact on precipitation biases. We found that the more intense and intermittent nature of rainfall in the CPM, which is more realistic leads to different canopy interception compared to the RCM. This can impact canopy evaporation, evapotranspiration and feed back on precipitation. Increasing rainfall storage in the canopy only leads to small improvements in warm biases, since it still fills rapidly with intense CPM rainfall, suggesting the need for an additional moisture store via improved groundwater modelling or surface pooling. Overall, this work highlights the challenge of correctly capturing land surface feedbacks in CPMs, which play an important role in future climate projections in some regions.