Spatiotemporal variability of groundwater chemistry, source identification and health risks in the southern Chinese Loess Plateau.

Groundwater pollution of the loess plateau regions has become a global concern due to its vulnerability to natural and anthropogenic influences. In this study, 146 water samples were investigated to identify the spatiotemporal variability in groundwater chemistry, pollution sources and nitrate health risks in two interconnected river basins of a typical loess region. The results showed that except for bicarbonate, spatiotemporal variability of hydrochemical components in Malian River Basin (ML) was generally greater than that in Upper Jinghe River basin (JH-U) due to the hydrogeological conditions, and the hydrochemical facies in two river basins transformed from SO4·Cl and Cl·SO4 types to HCO3 and HCO3·SO4 types. The results of integrated-weight quality index (IWQI) showed that 77.8 % (1970s), 33.3 % (2004), 34.3 % (2015) of samples in ML exceeded the standard limits of Class IV groundwater quality, displaying a high pollution level with an improvement trend, while groundwater quality in JH-U indicated a very low pollution level with a deterioration trend. The geogenic source was identified as a main factor affecting groundwater quality, with contributions of 59.2 % and 48.7 % in JH-U and ML (2015), respectively. The anthropogenic sources including agricultural activities (20.7 % and 21.8 % in JH-U and ML) and coal mining activities (20.1 % and 29.5 % in JH-U and ML) also played a role in affecting groundwater quality. The nitrate health risk assessment demonstrated that 39.1 % and 20.3 % of groundwater samples (2015) significantly exceeded the standard threshold (Hazard Index = 1), implying a higher health risk to children than adults, and the nitrate health risk in ML was obviously greater than that in JH-U. This study provides novel insight into the spatiotemporal variability in groundwater chemistry, quality and health risk in loess regions under the influence of geogenic and anthropogenic factors.

Li Z ，Yang Q ，Xie C ，Ma H ，Wu B ，Wang Y ... -  《-》

Geospatial mapping and entropy-based analysis for groundwater evaluation with estimation of potential health risks due to nitrate and fluoride exposure.

Groundwater is a vital source of freshwater, but its quality is often compromised by various physiochemical factors. In the Mid-Gangetic Plains, there is a concerning escalation in the degradation of groundwater quality due to anthropogenic interventions. However, there remains a paucity of comprehensive knowledge concerning groundwater quality and the associated health hazards it poses. In response to this gap, the current study focuses on Nalanda district (Bihar), where 78 groundwater samples were collected across district in the month of May 2022 and their various water quality parameters were quantified as per standard methods. The adequacy of groundwater for human use was assessed using an entropy-based water quality index (EWQI), which also evaluated the potential human health risk stemming from nitrate and fluoride contamination. Furthermore, an empirical Bayesian kriging (EBK) driven geostatistical approach was utilized to predict water quality parameters at ungauged sites. The analysis of results disclosed that the ionic dominance in groundwater followed the sequence as cations Ca2+  > Mg2+, and anions HCO3- > SO42- > Cl- > NO3- > F- > PO43-. The concentration of NO3- and F- exceeded the permissible BIS levels by 11.5% and 6.5% of the samples respectively. The analysis of EBK models suggested K-Bessel as the best-fit model for pH, Mg2+, TH, F-, NO3-, and SO42- spatial interpolation while exponential EBK model for EC, Cl-, and PO43- and whittle EBK model for TDS, Ca2+, and HCO3- spatial interpolation. Spearman's correlation analysis revealed that elevated TDS and EC levels, coupled with correlations between NO3-, SO42-, and Cl-, suggest anthropogenic influences. The EWQI of the groundwater samples ranged from 36.28 to 180.80. The analysis of EWQI values revealed predominantly fair to good groundwater quality across the study area, suitable for drinking purposes. The hazard quotients for NO3- and F- indicate that non-carcinogenic health risks are more significant with nitrate pollution. The combined health impact was assessed using total hazard index (HI), ranging from 0.20 to 3.29 for children, 0.19 to 3.05 for males, and 0.17 to 2.70 for females. The cumulative probability distribution revealed total hazard index (HI) > 1 in 41.56%, 34.62%, and 28.21% of samples for children, males, and females. The HI analysis indicated a substantially higher risk for children compared to adults within the study area. This study offers a novel combination of entropy-based water quality assessment and geostatistical EBK modeling to evaluate groundwater quality and health risks in ungauged areas. The findings provide valuable insights for improved groundwater management and health risk mitigation.

Kumar A ，Singh A 《-》

Evaluation of groundwater quality and health risk assessment in Dawen River Basin, North China.

Groundwater is the principal water source of drinking and irrigation in the Dawen River Basin of Shandong Province. Thus, its investigations and evaluations are of significant importances. Based on collected groundwater samples, this study employed a combination of the entropy-weighted water quality index(EWQI), Nitrate Pollution Index(NPI) and the human health risk assessment(HHRA) model to evaluate groundwater quality and associated health risks. The combination of EWQI and NPI provides a more refined classification of groundwater quality in the Dawen River Basin. Geostatistical and GIS spatial analysis methods are employed to analyze the spatial characteristics of groundwater quality and its relationship with geomorphology. Results indicate that the region generally enjoys good water quality, with Entropy Water Quality Index (EWQI) values ranging from 20.32 to 302.37, and an average of 70.88. Downstream quality is poorer than upstream, and flat terrains typically exhibit poorer water quality. The major indicators affecting groundwater quality include Na⁺, Cl⁻, SO₄2⁻, and NO₃⁻. The NPI results show that due to differences in anthropogenic sources, 38.1%, 27.38%, 26.19%, 4.76%, and 3.57% of the groundwater samples are classified into non-polluted, slightly polluted, moderately polluted, significantly polluted, and extremely significantly polluted types, respectively. The HHRA model reveals high potential non-carcinogenic risks for NO₃⁻ and low risks for F⁻ in the study area. The health risks associated with high levels of NO3- in the areas surrounding Dongping Lake and Ningyang County are greater than in those other regions and therefore should be a significant concern for public health. Furthermore, this study attempts to combine the EWQI and NPI to categorize groundwater protection and governance statuses into four types: protective, utilizable, preventive, and remedial. This approach addresses the shortcomings in comprehensively identifying water quality types by single evaluation methods and offers valuable insights for distinguishing water quality types under nitrogen pollution conditions.

Wei S ，Zhang Y ，Cai Z ，Bi D ，Wei H ，Zheng X ，Man X ... -  《-》

Deciphering pollution sources and mechanisms controlling groundwater chemistry in a typical dense agricultural plain on Yungui Plateau.

Groundwater is a critical resource for economic growth and livelihoods in the dense agricultural plains of plateaus. However, contaminations from various sources pose significant threats to groundwater quality. Understanding the sources of groundwater contamination and the mechanisms of hydrochemical control is essential for the sustainable development of agriculturally intensive plains. This research utilizes 23 datasets of groundwater chemical measurements to apply hierarchical clustering analysis, positive matrix factorization, and hydrochemical analysis techniques. Through these methods, the study identifies the sources of groundwater contamination and deciphers the hydrochemical control mechanisms within a representative intensive agricultural plain region of Yungui Plateau. The finds indicate that groundwater in the plain primarily derives from the rainfall occurred in the surrounding mountains. During the long underground flow process, groundwater undergoes water-rock interactions and ion exchanges with various lithological strata, resulting in the formation of distinct hydrochemical types. As it traverses regions influenced by human activities, groundwater encounters varying levels and types of contamination. Consequently, there is a notable variation in groundwater quality across different areas of the plain. Groundwater is dominated by the hydrochemical faces of HCO3-Ca type in the southern part of the plain. Groundwater in the piedmont region of this part exhibits the highest quality, acting as the baseline for the overall groundwater quality of the plain. Groundwater in agricultural areas of this part is severely polluted by nitrate-rich agricultural wastewater. In the central urban area, under the control of municipal wastewater discharge and denitrification, groundwater is to some extent polluted by NH4 +. In the northern sector of the plain, groundwater chemistry exhibits greater diversity due to variations in geological strata and exposure to a range of pollution sources. The majority of the regions are contaminated with SO4 2- and Cl- and present a predominance of Cl-Na type for groundwater hydrochemical facies. Groundwater at the northernmost end is polluted by NO2 -, NH4 +, and P. In addition, there is also a small amount of groundwater near the lake that is heavily polluted by fertilizers. This study provides valuable insights for the development of sound groundwater management strategies, applicable not only to the current agricultural plain but also to analogous regions worldwide. PRACTITIONER POINTS: This study probed the impact of agricultural pollution on the groundwater hydrochemistry in a cultivated plain. The research pinpointed the origins and contributions of groundwater chemicals in the cultivated agricultural plain. A conceptual model was established to illustrate groundwater chemistry formation in an intensive agricultural irrigation plain on Yungui Plateau.

Wang J ，Xiao Y ，Wang L ，Zhang Y ，Feng M ，Zhu W ，Yang W ，Shi W ，Yang H ，Han J ，Hu W ，Wang N ... -  《-》

Geochemical and isotopic studies of the Douda-Damerjogue aquifer (Republic of Djibouti): Origin of high nitrate and fluoride, spatial distribution, associated health risk assessment and prediction of water quality using machine learning.

Groundwater from the East African Rift System (EARS), for which there is limited data available, is often characterized by high levels of dissolved fluoride and nitrate, which pose inherent health risks. Within the EARS, the Douda-Damerjogue aquifer system was overexploited and subjected to anthropogenic and/or geogenic pollution with high NO3-concentrations (up to 375.4 mg L-1) and F-(up to 4.5 mg L-1). This study is the first to examine the origin and cumulative health risk assessment of groundwater with high F- and NO3- contents in rifting zones, as well as the spatial patterns and the water quality forecasting. This study use a combination of geochemical and thermodynamic tools, geospatial analysis, MixSIAR model, Machine Learning (ML) model, as well as stable isotope ratios, including δ18O(H2O), δ2H(H2O), δ15N(NO3-), and δ18O(NO3-). A ML framework was developed to forecast NO3-, Electrical Conductivity (EC), and Irrigation Water Quality Index (IWQI) in such data-scarce environments. The key geochemical processes controlling the groundwater composition in the study area were: (i) basalt weathering; (ii) ion exchange; (iii) mixing with fossil groundwater; and (v) seawater intrusion. Fluoride enrichment (> 1.5 mg L-1) in the groundwater was likely driven by the dissolution of fluoride-bearing minerals and desorption from sorbent surfaces. The combined application of the MixSIAR model, stable nitrate isotopes, and the NO3/Cl vs Cl diagram identified soil organic nitrogen, NH4-fertilizers, sewage and manure as the primary anthropogenic sources of NO3- in the groundwater. Groundwater chemistry showed that 76 % of samples exceeded the permissible limits for fluoride and nitrate, posing potential health risks, especially for teenagers and infants. The proposed ML-based framework provides a robust, scalable solution for forecasting water quality in Djibouti and other regions facing similar challenges.

Awaleh MO ，Boschetti T ，Marlin C ，Robleh MA ，Ahmed MM ，Al-Aghbary M ，Vystavna Y ，Waberi MM ，Dabar OA ，Rossi M ，Adaneh AE ，Chirdon MA ，Dirieh ES ，Egueh NM ，Elmi OI ... -  《-》