Search Results (53)

The distribution of fresh and salty groundwater is a critical factor affecting the coastal wetlands. However, the dynamics of groundwater flow and salinity in river deltas remain unclear due to complex hydrological settings and impacts of human activities. The uniqueness of the Yellow River Delta (YRD) lies in its relatively short formation time, the frequent salinization and freshening alternation associated with changes in the course of the Yellow River, and the extensive impacts of oil production and underground brine extraction. This study employed a detailed hydrogeological modeling approach to investigate groundwater flow and the impacts of oil field brine leakage in the YRD. To characterize the heterogeneity of the aquifer, a sediment texture model was constructed based on a geotechnical borehole database for the top 30 m of the YRD. A detailed variable-density groundwater model was then constructed to simulate the salinity distribution in the predevelopment period and disturbance by brine extraction in the past decades. Probabilistic particle tracking simulation was implemented to assess the alterations in groundwater flow resulting from brine resource development and evaluate the potential risk of salinity contamination from oil well fields. Simulations show that the limited extraction of brine groundwater has significantly altered the hydraulic gradient and groundwater flow pattern accounting for the less permeable sediments in the delta. The vertical gradient increased by brine pumping has mitigated the salinization process of the shallow groundwater which supports the coastal wetlands. The low groundwater velocity and long travel time suggest that the peak salinity concentration would be greatly reduced, reaching the deep aquifers accounting for dispersion and dilution. Further detailed investigation of the complex groundwater salinization process in the YRD is necessary, as well as its association with alternations in the hydraulic gradient by brine extraction and water injection/production in the oilfield. Full article

Morocco’s Témara Plain relies heavily on its aquifer system as a critical resource for drinking water, irrigation, and industrial activities. However, this essential groundwater reserve is increasingly threatened by over-extraction, seawater intrusion, and complex hydrogeochemical processes driven by the region’s geological characteristics and anthropogenic pressures. This study aims to assess groundwater quality and its vulnerability to pollution risks and map the spatial distribution of key hydrochemical processes through an integrated approach combining Geographic Information System (GIS) techniques and multivariate statistical analysis, as well as applying the DRASTIC model to evaluate water vulnerability. A total of fifty-eight groundwater samples were collected across the plain and analyzed for major ions to identify dominant hydrochemical facies. Spatial interpolation using Inverse Distance Weighting (IDW) within GIS revealed distinct patterns of sodium chloride (Na-Cl) facies near the coastal areas with chloride concentrations exceeding the World Health Organization (WHO) drinking water guideline of 250 mg/L—indicative of seawater intrusion. In addition to marine intrusion, agricultural pollution constitutes a major diffuse pressure across the aquifer. Shallow groundwater zones in agricultural areas show heightened vulnerability to salinization and nitrate contamination, with nitrate concentrations reaching up to 152.3 mg/L, far surpassing the WHO limit of 45 mg/L. Furthermore, other anthropogenic pollution sources—such as wastewater discharges from septic tanks in peri-urban zones lacking proper sanitation infrastructure and potential leachate infiltration from informal waste disposal sites—intensify stress on the aquifer. Principal Component Analysis (PCA) identified three key factors influencing groundwater quality: natural mineralization due to carbonate rock dissolution, agricultural inputs, and salinization driven by seawater intrusion. Additionally, The DRASTIC model was used within the GIS environment to create a vulnerability map based on seven key parameters. The map revealed that low-lying coastal areas are most vulnerable to contamination. Full article

Inland saline wetlands in the Ebro Basin (Spain) are protected by international regulations but are also threatened by the expansion of animal farms. We studied the input–output budgets of N from animal farms in four catchments of wetlands in the central Ebro Basin designated as Nitrate Vulnerable Zones. We used the N produced in animal farms as inputs and the N extracted by the crops on which manures and slurries are applied as outputs in each catchment. The balances considered the regulations concerning the slope of land where animal excreta may be applied and the doses of application. At a detailed scale, we applied the Water Erosion Prediction Program (WEPP) to the Farnaca catchment to assess the runoff and nutrients arriving to its wetland. While the Bujaraloz-Sástago basin showed a high excess of N load, in the Gallocanta basin, N extraction by crops was significantly higher than the N produced by the animal farms. Despite this lack of surplus of N from animal excreta, the groundwaters in the Gallocanta catchment are polluted by nitrates. The emphasis on N from animal farms in plans to prevent water pollution is missing the role of mineral fertilizers as the sources of pollution in basins with small N loads from animal farms. Agricultural plots in the Farnaca catchment produce significant amounts of sediments and nutrients that eventually pollute the wetland. Modelling approaches at detailed scales are required to assess the flows of materials to individual wetlands. Full article

The unique anticline geological structure in the central region of Yingjisha County results in significant spatial variations in groundwater quality. The study shows that the recoverable groundwater reserves account for 13.5% of the natural groundwater supply, and the development potential is considerable. Therefore, this study conducts an in-depth analysis of the spatial distribution characteristics of multiple water sources, integrates agricultural cropping patterns, and delineates irrigation districts accordingly. A water quality-based optimized allocation model for water resources is established. After optimization, the total irrigation water demand is reduced from 3685.8 million m³ to 3229.9 million m³, with total groundwater extraction controlled at 694.0 million m³. The total water shortage rate is 12%, and the decline in groundwater levels has been effectively controlled. Additionally, 116.4 million m³ of saline water is utilized, achieving an 83% utilization rate, which accounts for 16.8% of total groundwater extraction. Consequently, the utilization rate of freshwater decreases from 127% to 64%, while the overall water supply reliability reaches 87.6%. The sequence of water supply and consumption in the model remains consistent with the existing supply structure, demonstrating the rationality of the model parameter settings. This study proposes an optimal freshwater–saline water allocation model, which mixes saline water with reservoir water for dilution and subsequent agricultural irrigation. The approach aims to exploit the potential of saline groundwater and enhance the utilization efficiency of groundwater systems, thereby providing an innovative solution to alleviate water supply-demand conflicts in arid regions. Full article

Extensive and unregulated groundwater extraction for irrigation in the arid inland basins of Northwest China has led to a continuous increase in groundwater depth in agricultural irrigation areas. This has significantly altered the distribution of soil ions, making it difficult to predict their evolution and dynamic patterns. In this study, we used a space-for-time substitution approach to elucidate the evolution of the soil ion distribution under changing groundwater depths. Experiments were conducted in three typical irrigation areas with varying groundwater depths, that is, below 5 m, 5–10 m, and above 10 m in Korla, Xinjiang, China. Soil samples were collected from five profiles at depths of 0–180 cm to measure the soil moisture, salinity, and major ion content. An innovative research framework was developed to examine the relationship between groundwater depth and soil ion distribution using ion ratios, principal components, hierarchical clustering, and correlation analyses. This framework aims to reveal the dynamics, correlations, and mechanisms of soil moisture, salinity, ion distribution, and representative ion composition as groundwater depth increases in the arid agricultural irrigation areas of Northwest China. The results showed that as groundwater depth increased, the soil chemical type shifted from Ca-SO₄ to Na-SO₄ and mixed types, with an increase in SO₄²⁻ and Na⁺ content in the soil profile. Soil moisture, salinity, sodium adsorption ratio (SAR), and total dissolved solids (TDS) were significantly higher in shallow groundwater than in deep groundwater. Groundwater depth was negatively correlated with soil moisture, salinity, and major cations and anions (K⁺, Na⁺, Ca²⁺, Mg²⁺, Cl⁻, SO₄²⁻, and NO₃⁻). Meanwhile, a positive correlation exists between groundwater depth and CO₃²⁻. The dynamic distribution of soil ions is primarily governed by groundwater depth and is influenced by multiple factors. Evaporation is the dominant factor in shallow groundwater areas, whereas the mineral composition of rocks plays a crucial role in deep groundwater areas. These findings provide scientific support for strategic agricultural water-resource management policies and sustainable development strategies in arid regions. Full article

Alluvial aquifers are vital for agricultural communities in semiarid regions, where groundwater quality is often constrained by seasonal and spatial salinity variations. This study employed geostatistical methods to analyze the spatial and temporal variability of electrical conductivity (EC) and the sodium adsorption ratio (SAR) and elaborate an indicative quality map in the Mimoso Alluvial Aquifer, Pernambuco, Brazil. Groundwater samples were collected and analyzed for cations, total hardness (TH), and the percentage of sodium (PS). Moreover, the relation between EC and the SAR was used to determine the groundwater quality for irrigation. Cation concentrations followed the order Ca²⁺ > Mg²⁺ > Na⁺ > K⁺. EC and the SAR exhibited medium to high variability, with spatial dependence ranging from moderate to strong, and presented a strong cross-spatial dependence. Results showed that sequential Gaussian simulation (SGS) provided a more reliable groundwater classification for agricultural purposes compared to kriging methods, enabling a more rigorous evaluation. Based on the strong geostatistical cross correlation between EC and RAS, a novel water quality index was proposed, properly identifying regions with lower groundwater quality. The resulting spatial indicator maps classified groundwater as suitable (64.7%), restricted use (2.08%) and unsuitable (2.38%) for irrigation. The groundwater quality maps indicated that groundwater was mostly suitable for agriculture, except in silty areas, also corresponding to regions with low hydraulic conductivity at the saturated zone. Soil texture, rainfall, and water extraction significantly influenced spatial and temporal patterns of groundwater quality. Such correlations allow a better understanding of the groundwater quality in alluvial valleys, being highly relevant for water resources management in semiarid areas. Full article

This study investigates the complex interaction of biophysical and meteorological factors that drive evapotranspiration (ET) in saline environments. Leveraging a total of 182 cloud-free Landsat 5/8 time-series data from 1988 to 2019, we employed the Surface Energy Balance System (SEBS) model to quantify ET and investigate its relationships with soil salinity, vegetation cover, groundwater depth, and landscape metrics. We validated the predicted ET at two experimental sites using ET observation calculated by a water balance model. The result shows an R² of 0.78 and RMSE of 0.91 mm for the SEBS predicted ET, indicating high accuracy of the ET estimation. We detected abandoned saline farmland patches across Hetao and extracted the normalized difference vegetation index (NDVI), salinization index (SI), and the predicted ET for analysis. The results indicate that ET is negatively correlated with SI with a Pearson correlation coefficient (r) up to −0.7, while ET is positively correlated with NDVI (r = 0.4). In addition, we designed a control-variable experiment in the Yichang subdistrict to investigate the effects of groundwater depth, land aggregation index, soil salinity index, and the area of abandoned saline farmland patches on ET. The results indicate that increased NDVI could significantly enhance ET, while smaller saline farmland patches exhibited greater sensitivity to groundwater recharge, with higher averaged ET than larger patches. Moreover, we analyzed factor importance using Lasso regression and Random Forest (RF) regression. The result shows that the ranking of the importance of the features is consistent for both methods and for all the features, with NDVI being the most important (with an RF importance score of 0.4), followed by groundwater table depth (GWTD), and the influence of the surface area of abandoned saline farmland being the weakest. We found that smaller patches of abandoned saline farmland were more sensitive to changes in groundwater levels induced by nearby irrigation, affecting their averaged ET more dynamically than larger patches. Decreasing patch size over time indicates ongoing changes in land management and ecological conditions. This study, through a multifactor analysis of ET in abandoned saline farmland and its intrinsic factors, provides a reference for evaluating the dry drainage efficiency of abandoned saline farmland in a dry drainage system. Full article

The objective of this study was to compare the effects of biochar extract (BE) and mineral potassium fulvic acid (MPFA) on the salt tolerance and growth of Bok Choy (Shanghai Bok Choy) under saline conditions, aiming to utilize saline groundwater resources in the Yellow River Delta region. Based on the mineralization level of saline groundwater in the Yellow River Delta region, all the treatments were cultured in a nutrient solution containing 6 g·L⁻¹ NaCl. Nine treatments were set up: BE (C1: 1 g, C2: 5 g, C3: 10 g, C4: 15 g·L⁻¹), MPFA (H1: 0.2 g, H2: 0.4 g, H3: 0.6 g, H4: 0.8 g·L⁻¹), and a control (CK). The results showed that both the BE and MPFA reduced MDA accumulation, increased SOD and CAT enzyme activities, thereby increasing the number of effective leaves, the maximum leaf length, and the maximum leaf width of Shanghai Bok Choy. However, MPFA was better than the BE at increasing the antioxidant enzyme activities and total chlorophyll content. Correlation analysis revealed that the hydrogen peroxide content and CAT enzyme activity were the most important factors affecting Shanghai Bok Choy yield. Compared to the CK, the BE treatments reduced the hydrogen peroxide content by 1.1–46.4% and increased the CAT enzyme activity by 4.1–68.0%, while the MPFA treatments increased the hydrogen peroxide content and decreased the CAT enzyme activity. Consequently, the fresh weight of Shanghai Bok Choy treated with the BE was 11.01–112.21% higher than the MPFA treatments and 5.17–49.70% higher than the CK. Overall, C3 had significantly lower hydrogen peroxide content than the CK and the highest CAT enzyme activity, which was markedly better than the MPFA treatments. This suggests that C3 may be an effective method for improving the salt tolerance and growth of Shanghai Bok Choy under salt stress. This study provides favorable data to support the solution to the problem of agricultural water use and the realization of sustainable development in the Yellow River Delta. Full article

In many projects, it is important to monitor the direction of groundwater flow, but conventional methods make it difficult. Through streaming potential detection technology, under the action of external pressure, liquid can be forced to flow through solid pores to generate directional flow, and a flow potential can be generated at both ends of solid pores. The phenomenon of different streaming potentials can help engineers determine the direction of fluid flow. In this study, tests were conducted using a core injection system and a streaming potential tester to carry out injections on sandstone samples of two different structures to study the effects of different injection pressures and different salinities on the variation in the streaming potential in sandstone. Moreover, a small-scale field water injection monitoring experiment was also carried out to observe the actual situation of the streaming potential generated during water injection in the field formation structure. The laboratory test results show that the flow potential is accompanied by the liquid injection process in the sandstone sample, and the flow potential produced by the sandstone with different porosities is obviously different, Therefore, the flow potential associated with the actual rock injection process can be used to infer porosity and permeability. This study provides a new method for monitoring underground fluids and is expected to improve the efficiency of oil extraction and geothermal development. Full article

In the context of global warming, rising sea levels are intensifying seawater intrusion in coastal areas. Due to the complex hydrodynamic conditions and increasing groundwater over-extraction in these regions, understanding the patterns of seawater intrusion is crucial for effective prevention and control. This study employed a sandbox model to investigate both vertical and horizontal seawater intrusion into a coastal unconfined aquifer with an impermeable dam under varying conditions of sea level rise, coastal slope, and groundwater pumping rate. Additionally, a two-dimensional SEAWAT model was developed to simulate seawater intrusion under these experimental conditions. The results indicate that sea level rise significantly increases the extent and intensity of seawater intrusion. When sea level rises by 3.5 cm, 4.5 cm, and 5.5 cm, the areas of the saline wedge reached 362 cm², 852 cm², and 1240 cm², respectively, with both horizontal and vertical intrusion ranges expanding considerably. When groundwater extraction is superimposed, vertical seawater intrusion is notably intensified. At an extraction rate of 225 cm³/min, the vertical intrusion areas corresponding to sea level rises of 3.5 cm, 4.5 cm, and 5.5 cm were 495 cm², 1035 cm², and 1748 cm², respectively, showing significant expansion, and this expansion becomes more pronounced as sea levels rise. In contrast, slope variations had a significant impact only on vertical seawater intrusion. As the slope decreased from tanα = 1/5 to tanα = 1/9, the upper saline wedge area expanded from 525 cm² to 846 cm², considerably increasing the vertical intrusion range. Finally, the combined effects of groundwater extraction and sea level rise exacerbate seawater intrusion more severely than either factor alone, presenting greater challenges for coastal water resource management. Full article

Sindh is in the lower reaches of the Indus River; it is most vulnerable to a variety of upstream water development challenges. The aim of this research was to determine aquifer characteristics in the command area of Tando Allahyar-II distributary within the culmination of underground water potential. The hydraulic properties of the aquifer as well as the susceptibility of the formation to tedious extraction and saltwater upcoming were recognized. Three pumping tests were performed at head, middle, and tail reaches along the selected distributary. The drawdowns were measured at head reach (5.1667 h), at middle reach (6.0 h), and at tail reach (19.667 h) of the selected distributary by performing the pumping tests. Groundwater levels were lower at the tail reach compared to those at the head and middle reaches, likely due to a higher concentration of tubewells in the lower reach. The head and middle reaches showed higher groundwater levels, possibly due to constant head conditions promoting infiltration and recharge. The pumping test versus drawdown analysis revealed that the tubewells should be run with 7-h (on) and 4-h (off) operation. Further, the tubewells at all reaches (head, middle, and tail) should be closed for a minimum of 4 h between operations. This strategy would allow safe groundwater extraction, maintain water quality, and prevent water table depletion in the study area. The hydrodynamic and hydro-salinity behaviors were scrutinized in PWMIN 5.3 (version) by means of the MODFLOW mode. The results were estimated to compare the calibration and validation simulation outcomes using measured data. The model was successfully calibrated, and the root mean square (RMS) value of the head tubewell varied between 0.024 and 0.108, whereas it speckled between 0.0166 and 0.0349 for the middle tubewell and between 0.0659 and 0.0069 for the tail tubewell. The RMS values for hydrodynamic behavior for the head, middle, and tail reaches were less than 10%. These values represent a suitable match between the observed and simulated heads when a water table depletion of 1 to 2 m was observed due to extreme pumping. However, the average relative error values, for all validated procedures, were less than 10%. Full article

The need for controlling salinity in arid zones is essential for sustainable agricultural production and irrigation water use. A case study performed for two years in Hetao, Inner Mongolia, China, is used herein to rethink the contradictory issues of arid lands represented by water saving and controlling soil and water salinity. Two sets of static lysimeters, where water table depths (WTDs) were fixed at 1.25, 150, 2.00, and 2.25 m, were continuously monitored, and soil water and solute data were used to calibrate and validate two models: the soil water balance model SIMDualKc and the deterministic soil water and salt dynamics model HYDRUS-1D. Once accurately calibrated, the models were used to simulate maize water use, percolation, and capillary rise, along with the observed variables for the actual WTD and the autumn irrigation applied. Simulation scenarios also considered agricultural system degradation and dynamic water table behavior. Results have shown that large leaching efficiencies (Lefs) were obtained for large irrigation depths in cases of shallow water tables, but higher Lefs corresponded to high application depths when the water table was deeper. Agricultural system degradation, particularly increased groundwater salinity, lowered Lef, regardless of WTD. Conversely, water savings were minimal and only achievable when considering the dynamic nature of groundwater. These results indicate that there is a need to define different WTDs based on soil characteristics that influence fluxes and root zone storage, as well as the impacts of newly installed drainage systems aimed at salt extraction. Full article

The southern Gabès aquifer in southeastern Tunisia faces significant stress due to unsustainable groundwater extraction. This study employs a SEAWAT model to evaluate groundwater losses, salinization mechanisms, and the interaction between the confined aquifer and the Mediterranean Sea. The model, incorporating well pumping rates, regional freshwater inflows from the Matmata Mountain Range, and the Mediterranean Sea boundary, demonstrated high accuracy in simulating hydraulic heads. Findings reveal that regional inflow is only half of the current pumping rate, indicating unsustainable groundwater use. The study also assessed salinity dynamics by modeling the Mediterranean Sea as a constant head and salinity boundary. Results suggest limited exchange between the aquifer and the sea, challenging previous assumptions. While the immediate risks of salinization are low, continued over-extraction could compromise the aquifer’s long-term sustainability. This research highlights the need for stricter local groundwater management, offers insights into regional coastal aquifer interactions, and contributes to global discussions on managing stressed aquifer systems. Full article

Groundwater salinization poses a critical threat to sustainable development in arid and semi-arid rurbanizing regions, exemplified by Kerman Province, Iran. This region experiences groundwater ecosystem degradation as a result of the rapid conversion of rural agricultural land to urban areas under chronic drought conditions. This study aims to enhance Groundwater Pollution Risk (GwPR) mapping by integrating the DRASTIC index with machine learning (ML) models, including Random Forest (RF), Boosted Regression Trees (BRT), Generalized Linear Model (GLM), Support Vector Machine (SVM), and Multivariate Adaptive Regression Splines (MARS), alongside hydrogeochemical investigations, to promote sustainable water management in Kerman Province. The RF model achieved the highest accuracy with an Area Under the Curve (AUC) of 0.995 in predicting GwPR, outperforming BRT (0.988), SVM (0.977), MARS (0.951), and GLM (0.887). The RF-based map identified new high-vulnerability zones in the northeast and northwest and showed an expanded moderate vulnerability zone, covering 48.46% of the study area. Analysis revealed exceedances of WHO standards for total hardness (TH), sodium, sulfates, chlorides, and electrical conductivity (EC) in these high-vulnerability areas, indicating contamination from mineralized aquifers and unsustainable agricultural practices. The findings underscore the RF model’s effectiveness in groundwater prediction and highlight the need for stricter monitoring and management, including regulating groundwater extraction and improving water use efficiency in riverine aquifers. Full article

In response to economic and environmental challenges like sea-level rise, salinity intrusion, groundwater extraction, sand mining, and sinking delta phenomena, the demand for solutions to adapt to changing conditions in riverine environments has increased significantly. High-quality analyses of land use and land cover (LULC) dynamics play a critical role in addressing these challenges. This study introduces a novel high-spatial resolution satellite-based approach to identify sub-seasonal LULC dynamics in the Mekong River Delta (MRD), employing a three-year (2021–2023) Sentinel-1 and Sentinel-2 satellite data time series. The primary obstacle is discerning detailed vegetation dynamics, particularly the seasonality of rice crops, answered through quantile mapping, harmonic regression with Fourier transform, and phenological metrics as inputs to a random forest machine learning classifier. Due to the substantial data volume, Google’s cloud computing platform Earth Engine was utilized for the analysis. Furthermore, the study evaluated the relative significance of various input features. The overall accuracy of the classification is 82.6% with a kappa statistic of 0.81, determined using comprehensive reference data collected in Vietnam. While the purely pixel-based approach has limitations, it proves to be a viable method for high-spatial resolution satellite image time series classification of the MRD. Full article