Anthropogenic Effects on Hydrogeochemical Characterization of the Shallow Groundwater in an Arid Irrigated Plain in Northwestern China

Groundwater Salinity Across India: Predicting Occurrences and Controls by Field-Observations and Machine Learning Modeling

Elevated groundwater salinity is unsuitable for drinking and harmful to crop production. Thus, it is crucial to determine groundwater salinity distribution, especially where drinking and agricultural water requirements are largely supported by groundwater. This study used field observation (n = 20,994)-based machine learning models to determine the probabilistic distribution of elevated groundwater salinity (electrical conductivity as a proxy, >2000 μS/cm) at 1 km2 across parts of India for near groundwater-table conditions. The final predictions were made by using the best-performing random forest model. The validation performance also demonstrated the robustness of the model (with 77% accuracy). About 29% of the study area (including 25% of entire cropland areas) was estimated to have elevated salinity, dominantly in northwestern and peninsular India. Also, parts of the northwestern and southeastern coasts, adjoining the Arabian Sea and the Bay of Bengal, were assessed with elevated salinity. The climate was delineated as the dominant factor influencing groundwater salinity occurrence, followed by distance from the coast, geology (lithology), and depth of groundwater. Consequently, ∼330 million people, including ∼109 million coastal populations, were estimated to be potentially exposed to elevated groundwater salinity through groundwater-sourced drinking water, thus substantially limiting clean water access.

Evaluating hydrogeochemical characteristics of groundwater and surface water in the Upper Pearl River Watershed, USA

The groundwater quality of the Upper Pearl River Watershed (UPRW) and surface water quality of the basin's outlet, Ross Barnett Reservoir (RBR), are critically important because of growing demands for drinking, agriculture, and industrial use in the region. To identify factors affecting water quality and characterize the surface water outlet and the watershed's groundwater, geochemical and statistical analyses were performed using results from various hydrogeochemical parameters. Based on surface geology, groundwater samples analyzed (n = 51) within the watershed were partitioned into three recharge zones: North, Mid, and South. Precipitation and rock-water interactions were identified to dominantly influence the groundwater chemistry in the region. The chemistry of the surface water samples (n = 9), on the other hand, was influenced more by precipitation with minor contribution from the proximal aquifer system. Principal component analysis (PCA) revealed that two groundwater recharge zones and RBR samples exhibited significant clustering. The groundwater had a complex array of parameters influencing its chemistry owing to diverse properties, including Na, Ca, Mg, alkalinity, and conductivity. Comparing land use at the sub-watershed level with the water quality parameters showed that agriculture and development could have contributed nitrate, especially to the groundwater in the south zone. However, a general lack of distinct relationship between land use and water quality, along with detection of excess nitrate in select wells suggested that the water in the region was likely affected by point sources, such as poultry farms. The research recommends evaluating point sources of pollution to cater to future water management in the region.

Hydrogeochemical evaluation, suitability, and health risk assessment of groundwater in the watershed of Godavari basin, Maharashtra, Central India

In this investigation, the geochemical progression of a total of 31 groundwater samples of pre-monsoon season was assessed with categorization based on entropy weight water quality index and risk assessment on public health in the semi-arid area of Godavari basin, Maharashtra, Central India. Graphically, the major groundwater types identified were Ca-HCO₃, mixed Ca-Mg-Cl, and mixed Ca-Na-HCO₃. Based on [Mg²⁺/Na⁺] with [Ca²⁺/Na⁺] and [HCO₃^-/Na⁺] with [Ca²⁺/Na⁺] plots, carbonate and silicate weathering were identified as a major geochemical process governing groundwater chemistry. The presence of reverse ion exchange process was authenticated by (Ca²⁺ + Mg²⁺) vs. (HCO₃^- + SO₄^2-) and Na⁺ + K⁺-Cl^- vs. (Ca²⁺ + Mg²⁺)-(HCO₃^- + SO₄^2-) plots. The saturation index values for calcite and dolomite showed that these minerals were in dissolution state. The dissolution of gypsum, dolomite, and anhydrite increased Ca²⁺ load in groundwater which accelerated the precipitation of calcite. The high toxic level of NO₃^- (> 45 mg/L) was identified in 64.5% of the 31 groundwater samples, whereas F^- concentration exceeded the threshold value in 12.9% of samples. Based on the entropy weight water quality index values, 70% of the samples were found to have moderate quality for drinking. In addition, health risk evaluation showed that the total hazard, due to fluoride and nitrate through oral pathways, was much higher than that through the dermal pathway. Children were found to be at high risk due to the consumption of NO₃^- and F^- contaminated water. The calculated irrigation water quality index (IWQI) diverge from 7.4-89.2, expressing excellent to good quality for irrigation. Based on the irrigation water quality index, 90.3% of samples were found excellent for irrigation and 6.4% of good quality for irrigation. Authors recommend that continuous water quality monitoring programs along with effective management practices should be developed to avoid excessive extraction of groundwater.

Estimation of nitrate pollution sources and transformations in groundwater of an intensive livestock-agricultural area (Comarca Lagunera), combining major ions, stable isotopes and MixSIAR model

The identification of nitrate (NO₃^-) sources and biogeochemical transformations is critical for understanding the different nitrogen (N) pathways, and thus, for controlling diffuse pollution in groundwater affected by livestock and agricultural activities. This study combines chemical data, including environmental isotopes (δ²H_H2O, δ¹⁸O_H2O, δ¹⁵N_NO3, and δ¹⁸O_NO3), with land use/land cover data and a Bayesian isotope mixing model, with the aim of reducing the uncertainty when estimating the contributions of different pollution sources. Sampling was taken from 53 groundwater sites in Comarca Lagunera, northern Mexico, during 2018. The results revealed that the NO₃^- (as N) concentration ranged from 0.01 to 109 mg/L, with more than 32% of the sites exceeding the safe limit for drinking water quality established by the World Health Organization (10 mg/L). Moreover, according to the groundwater flow path, different biogeochemical transformations were observed throughout the study area: microbial nitrification was dominant in the groundwater recharge areas with elevated NO₃^- concentrations; in the transition zones a mixing of different transformations, such as nitrification, denitrification, and/or volatilization, were identified, associated to moderate NO₃^- concentrations; whereas in the discharge area the main process affecting NO₃^- concentrations was denitrification, resulting in low NO₃^- concentrations. The results of the MixSIAR isotope mixing model revealed that the application of manure from concentrated animal-feeding operations (∼48%) and urban sewage (∼43%) were the primary contributors of NO₃^- pollution, whereas synthetic fertilizers (∼5%), soil organic nitrogen (∼4%), and atmospheric deposition played a less important role. Finally, an estimation of an uncertainty index (UI90) of the isotope mixing results indicated that the uncertainties associated with atmospheric deposition and NO₃^--fertilizers were the lowest (0.05 and 0.07, respectively), while those associated with manure and sewage were the highest (0.24 and 0.20, respectively).

Hydrochemical Characteristic of Groundwater and Its Impact on Crop Yields in the Baojixia Irrigation Area, China

While irrigated crops produce much higher yields than rain-fed crops, the ionic components of irrigation water have important effects on crop yield. Groundwater is widely used for irrigation in the Baojixia irrigation area in China. The chemical characteristics and water quality of groundwater in the Baojixia irrigation area were analyzed and evaluated to study the impact of groundwater quality on crop yield. Results showed cations in the groundwater to mainly be Na+, Ca2+, and Mg2+, whereas the anions are mainly HCO3−, SO42−, and Cl−. Water-rock interaction and cation exchange were identified as the main factors affecting hydrogeochemical properties from west to east. The study found salinity and alkalinity of groundwater in the western region of the study area to be low, and therefore suitable for irrigation. Groundwater in the eastern part of the study area was found to have a medium to high salinity and alkalinity, and is therefore not recommended for long-term irrigation. The groundwater irrigated cultivation of wheat and corn in the research area over 2019, for example, would have resulted in a drop in the annual crop output and an economic loss of 0.489 tons and 0.741 × 104 yuan, respectively. Irrigation using groundwater was calculated to result in the cumulative loss of crop yields and an economic loss of 49.17 tons and 80.781 × 104 yuan, respectively, by 2119. Deterioration of groundwater quality will reduce crop yields. It is recommended that crop yields in the study area be increased by strengthening irrigation water management and improving groundwater quality.