Evaluation of groundwater quality using an integrated approach of set pair analysis and variable fuzzy improved model with binary semantic analysis: A case study in Jiaokou Irrigation District, east of Guanzhong Basin, China

Hydrochemical characterization and health risk assessment of different types of water bodies in Fenghuang Mountain Area, Northeast China

Groundwater, as an essential resource, holds significant importance for human production and livelihoods. With the deterioration of the water environment, the issue of groundwater quality has become an urgent international concern. This study focused on the Fenghuang Mountain Area (FMA) and collected a total of 41 sets of samples including pore groundwater (PGW), fissure groundwater (FGW), karst groundwater (KGW), and river water (RW). Hydrochemical analysis methods were employed to identify the hydrochemical characteristics and controlling factors. The entropy-weighted water quality index (EWQI) and health risk assessment model were utilized to assess the groundwater quality and nitrate health risk, respectively. The results indicated that the dominant anion and cation in both groundwater and surface water in the FMA were HCO3- and Ca2+, respectively, with the main hydrochemical type being HCO3-Ca. Groundwater and surface water in the FMA were primarily controlled by rock weathering process, with ion concentrations influenced mainly by the dissolution of halite, sylvite, carbonates (calcite and dolomite), silicates, and gypsum, as well as by reverse anion exchange process. PGW was significantly affected by agricultural activities, with NO3- concentration closely related to human activities. The water quality of FGW was relatively good, with Class I and Class II water accounting for the highest proportion, reaching 84.62%. The high-value area of EWQI in PGW was influenced by human activities. The impact of nitrate health risk on children was significantly greater than on adults, with FGW having the lowest health risk and PGW having the highest health risk. The research results can provide important guarantees for the rational development and utilization of water resources in the FMA and the sustainable development of the economy in Northeast China.

Tracing the sources and evaporation fate of surface water and groundwater using stable isotopes of hydrogen and oxygen

Recognizing the origins and movement processes of surface water and groundwater is crucial for understanding hydrochemical genesis, conserving water supplies, and managing water resources. Estimating the source water typically involves identifying the intersection of evaporation line (EL) and meteoric water line. However, there is currently confusion in determining the regional EL and selecting strategies for estimating the source water. This study aimed to explore the source of surface water and groundwater, as well as evaporation effect utilizing stable isotope tracing (δ2H and δ18O). The line-conditioned excess was adopted to differentiate evaporated water and non-evaporated water, then Craig-Gordon model and an analytical framework with Bayesian theory were used to investigate the source of surface water and groundwater and the evaporation influence. The findings revealed that surface water and groundwater in the northern region of the Weihe River suffered more sever evaporation impacts that the south, and the evaporated surface water (7.54 % to 27.34 %) with a wider range of mean evaporation ratio than evaporated groundwater (5.38 % to 8.52 %). Monsoon precipitation is the main contributor to both surface water (contribution ratio: 0.46) and groundwater (0.49) sources. This research provides specific information on evaporation and detailed insights into the source water of surface water and groundwater, aiding in understanding the evaporation effect during the hydrological cycle and facilitating the management of regional water resources.

Multi-model exploration of groundwater quality and potential health risk assessment in Jajpur district, Eastern India

The presence of fluoride and nitrate is a serious groundwater quality issue in India impacting human health. In the present study, 14 different hydrochemical parameters for 76 groundwater samples collected from the Jajpur district of Odisha, India, were evaluated. Entropy-weighted water quality index (EWQI), fixed-weight groundwater quality index (GWQI), principal component analysis (PCA), and rotated factor loading-based water quality index (PCWQI) were employed to assess groundwater quality. About 65.79 ± 4.68%, 33.55 ± 3.95%, and 0.66 ± 0.76% of the samples were rated as "excellent," "good," or "medium" quality, respectively, across the four different water quality indices, with a nominal rating discrepancy of 13.15%. Though 86% of samples consistently received excellent or good ratings across all WQI frameworks, concentrations of F- and NO3- in 36.8% and 11.84% of the samples exceeded the WHO permissible limit. In health risk assessment, about 38.15% of samples surpassed the F- hazard quotient (HQ > 1) posing non-carcinogenic health risks for children. The non-carcinogenic health risks due to NO3- were evident in 55.26% and 11.84% of samples for children and adults, respectively. The higher concentration of NO3- in some of the water samples, together with its positive correlation with HCO3-, may worsen groundwater pollution. The moderate correlation between Ca2+ and HCO3- (r = 0.410) and the insignificant correlation between Mg2+ and HCO3- (r = 0.234) suggests calcite dissolution is far more common than dolomite.

Salinization of shallow groundwater in the Jiaokou Irrigation District and associated secondary environmental challenges

Understanding groundwater salinization of irrigation areas and related secondary environmental challenges is important for ensuring sustainable development. However, the mechanism under which groundwater salinization forms under the influence of long-term anthropogenic activities remains unclear. Therefore, this study analyzed the spatiotemporal variation in groundwater salinization and the underlying mechanism, and discussed the secondary environmental challenges in an irrigation area. The Jiaokou Irrigation District, North China, was adopted as a case study. The results showed a slight downward trend in groundwater salinity over the past two decades at a rate of 0.0229 g/L/y. Higher groundwater salinity was observed in areas with shallow groundwater depth. This correlation was mainly attributed to evaporative concentration, with secondary processes including natural weathering, depth of water-table, and fertilizer leaching. Drainage ditches may reduce groundwater salinity. Groundwater was transformed from freshwater to salt water and then to brackish water during the runoff process. The former transformation is mainly related to evaporation and fertilization. The latter transformation could be related to the inverse relationship between the distance to the Wei River and sediment permeability, with sediment permeability positively related to groundwater flow and leading to the discharge of salt into the Wei River. The secondary environmental challenges related to groundwater salinization in irrigation areas, mainly manifested in deterioration of irrigation water quality, soil salinization, and increased fluorine concentration. This study can act as a theoretical and practical reference for the development and utilization of water resources, ecological protection, and soil salinization in typical irrigation districts.

Groundwater quality assessment by multi-model comparison: a comprehensive study during dry and wet periods in semi-arid regions

With the impact of human engineering activities, groundwater pollution has seriously threatened the health of human life. Accurate water quality assessment is the basis of controlling groundwater pollution and improving groundwater management, especially in specific regions. A typical semi-arid city in Fuxin Province of China is taken as an example. We use remote sensing and GIS to compile four environmental factors, such as rainfall, temperature, LULC, and NDVI, to analyze and screen the correlation of indicators. The differences among the four algorithms were compared by using hyperparameters and model interpretability, including random forest (RF), support vector machine support vector machine (SVM), decision tree (DT), and K-nearest neighbor (KNN). The groundwater quality of the city during the dry and wet periods was comprehensively evaluated. The results show that the RF model has higher integrated precision (MSE = 0.11, 0.035; RMSE = 0.19,0.188; R² = 0.829,0.811; ROC = 0.98, 0.98). The quality of shallow groundwater is poor in general, 29%, 38%, 33% of the groundwater quality in low-water period is III, IV, V water. Thirty-three percent and 67% of the groundwater quality in the high-water period were IV and V water. The proportion of poor water quality in high-water period was higher than that in low-water period, which was consistent with the actual investigation. This study provides a kind of machine learning method for the semi-arid area, which cannot only promote the sustainable development of groundwater in this area, but also provide reference for the management policy of related departments.

Spatiotemporal characteristics of groundwater quality and health risk assessment in Jinghe River Basin, Chinese Loess Plateau

Groundwater is a very important natural resource for humanity, however, the degradation of groundwater quality caused by anthropogenic activities may pose a serious hazard to human health and ecosystem. In this study, 143 groundwater samples were analyzed to investigate the spatiotemporal variations of hydrochemistry, groundwater quality and potential human health risk of groundwater in Jinghe River Basin, Chinese Loess Plateau. Based on the mean concentrations value (MCV) and over-standard rate (OSR), the groundwater in Jinghe River Basin were divided into three groups: Group Ⅰ (high MCV: greater than standard values and high OSR: ≥ 10 %) contains TDS (total dissolved solids), TH (total harness), SO₄^2-, F^- and Fe; Group Ⅱ (low MCV and high OSR) contains pH, Cl^-, NO₃^-, Cr⁶⁺ and As, Group Ⅲ (low MCV and low OSR) contains NO₂^-, NH₄⁺, Zn, Mn, Pb, I^- and Cd. The results of set pair assessment indicated that the unsuitable and doubtful class of comprehensive groundwater quality are mainly distributed in the northern part of study area, accounting for 29 % and 13.6 % of the area in 2004 and 2015, respectively. Human health risk assessment based on the triangular fuzzy number suggested that the variation of risk levels in different age groups is Children > Adult Men > Adult Women. Average carcinogenic risks of As in groundwater for the three groups exceed the acceptable level, and non-carcinogenic risk of NO₃^- for Children is higher than the acceptable threshold. The findings of this study provide valuable insight into the spatiotemporal characteristics of groundwater quality and potential health risks of polluted groundwater by anthropogenic activities.

Assessment of groundwater geochemistry using multivariate water quality index and potential health risk in industrial belt of central Odisha, India

Groundwater in India has been shown to have a variety of water quality issues, including fluoride, nitrate, and uranium pollution, all of which pose a health risk to humans. In the present study, a total of 106 groundwater samples from the Angul district of Odisha, an industrialized region in India, were analyzed for 14 different hydrochemical parameters. In almost 30%, 34.9%, and 4.7% of the groundwater samples, the concentrations of F-, NO^3- and uranium, respectively, exceeded the permissible limit set by WHO. In addition to the fixed-weight groundwater quality index (GWQI), the entropy-weighted water quality index (EWQI), the principal component analysis (PCA) factor (or rotated factor) loading based water quality index (PCWQI) and human health risk assessment were used. Depending on the models, about 19.1 ± 0.9%, 70.5 ± 1.9% and 10.38 ± 1.9% of water samples were classified as "Excellent", "Good" and "Medium" quality, respectively, across four water quality indexes with a nominal rating disagreement of 11.3%. More than 90% of samples are unanimously classified as excellent or good across the WQI rating. For children and adults, approximately 54.7% and 24.5% of samples exceeded the permitted limit for F^-, (hazard quotient HQ > 1), posing non-carcinogenic health hazards, respectively. In contrast, 71.7% and 34.9% of NO₃^- samples respectively, surpassed the allowed limit and caused non-carcinogenic health concerns for children and adults. In terms of carcinogenic HQ values, about 13.2% and 7.5% of samples exhibit an uranium related carcinogenic health risk in children and adults, respectively. The existence of significant amounts of Cl ^-, NO₃^-, and especially HCO₃^- ions in groundwater in some samples, as well as their positive interdependence, may increase uranium pollution in the future through uranium dissolution.

Evaluation on the Risk of Water Inrush Due to Roof Bed Separation Based on Improved Set Pair Analysis-Variable Fuzzy Sets

To study and prevent bed separation water inrush accidents in coal mines, it is necessary to evaluate the risk according to the limited geological data correctly. In this work, based on hydrogeological and mining conditions, we established a risk evaluation model and selected seven important factors, including the aquifer thickness, aquifer water abundance, hydraulic pressure of the aquifer, effective aquifuge thickness, mining failure ratio, mining height of the working face, and advancing distance as evaluation indexes. The intuitionistic fuzzy analytic hierarchy process (IFAHP) and entropy weight method (EWM) were used to analyze the weights of the original data, and the minimum information entropy principle was used to further integrate the abovementioned calculation results. With the weight results, set pair analysis-variable fuzzy set (SPA-VFS) theory was applied to determine the risk grade of each working face, which provided scientific guidance for the safe mining of coal mines. For the working face where water inrush may occur, the risk of bed separation water inrush can be reduced by optimizing the parameters or changing the mining conditions through the model analysis.

Uncertain Analysis of Fuzzy Evaluation Model for Water Resources Carrying Capacity: A Case Study in Zanhuang County, North China Plain

The scientific and accurate evaluation of water resources carrying capacity has good social, environmental and resource benefits. Reasonable selection of evaluation parameters is the key step to realize efficient and sustainable development of water resources. Taking Zanhuang County in the North China Plain as the research area, this study selected fuzzy comprehensive evaluation models with different weights in the established evaluation index framework to explore the sources of uncertainty affecting the evaluation results of water resources carrying capacity. By using the sensitivity analysis method of index weight, the index with the biggest influence factor on the evaluation result is selected to reduce the uncertainty problems such as index redundancy and small correlation degree. The results show that the correlation and reliable of comprehensive evaluation value obtained by different weight methods is different. The evaluation result obtained by using the analytic hierarchy process is more relevant than the entropy weight method, and it is more consistent with the actual load-bearing situation. The study of sensitivity index shows that water area index is the biggest factor affecting the change of evaluation results, and water resources subsystem and socio-economic subsystem play a dominant role in the whole evaluation framework. The results show that strengthening the data quality control of index assignment and weight method is helpful to reduce the error of water resources carrying capacity evaluation. It can also provide scientific basis for the improvement of fuzzy evaluation model.