Hydrogeochemical assessment of groundwater quality and suitability for irrigation in the coastal part of Cuddalore district, Tamil Nadu, India

Precise management and control around the landfill integrating artificial intelligence and groundwater pollution risks

The Landfill plays an important role in urban development and waste disposal. However, landfill leachate may also bring more serious pollution and health risks to the surrounding groundwater environment. Compared with other areas, the area around the landfill needs more precise management. To solve this problem, based on the "pressure-state-response" framework, a method for the identification and evaluation of groundwater pollution around the landfill was constructed. The LPI method was used to assess the contamination potential of the leachate. The comprehensive quality of groundwater was evaluated by the entropy-AHP water quality assessment method, sodium adsorption ratio and sodium percentage. The probabilistic health risks of groundwater were assessed based on a Monte Carlo algorithm. The sources of pollutants were identified by comprehensively using the PCA-APCS-MLR model and the PMF model. Finally, the self-organizing map algorithm and the Kmeans algorithm were integrated to enhance the precision of groundwater management and control measures. The results showed that the leachate of the landfill was in the mature stage, and the concentration of inorganic substances was relatively high. Leachate had the potential to contaminate surrounding groundwater. The groundwater quality of 68.14% of the study area was in the poor or lower level. The groundwater near the landfill was unsuitable not only for drinking but also for irrigation purposes. Cl- was the main non-carcinogenic risk factor. Reducing pollutant concentration and controlling exposure time are effective strategies for mitigating health risks caused by high-concentration pollutants (Cl-, NO3-) and low-concentration pollutants (F-), respectively. The groundwater around the landfill was jointly affected by six pollution sources. The PMF model has better analytical ability in mixed pollution areas. The groundwater in the study area was divided into five clusters, of which cluster Ⅰ was significantly affected by leachate, and cluster Ⅴ had the lowest pollution and health risk.

Groundwater suitability assessment for irrigation and drinking purposes by integrating spatial analysis, machine learning, water quality index, and health risk model

An in-depth understanding of nitrate-contaminated surface water and groundwater quality and associated risks is important for groundwater management. Hydrochemical characteristics and driving forces of groundwater quality and non-carcinogenic risks of nitrate were revealed by the integrated approaches of self-organizing map analysis, spatial visualization by geography information system, entropy and irrigation water quality indices, and human health risk model. Groundwater samples were categorized into two clusters by SOM analysis. Cluster I including three samples were Ca-SO4 type and cluster II of remaining 136 samples were Ca-HCO3 type. Hydrochemical compositions of two cluster samples were dominated by water-rock interaction: (1) calcite and gypsum dissolution for cluster I samples and (2) calcite dissolution, silicate weathering, and positive cation exchange for cluster II samples. Nitrate contamination occurred in both cluster I and II samples, primarily induced by agricultural nitrogen fertilizer. The EWQI results showed that 90.97% in total groundwater samples were suitable for drinking purpose, while the IWQI results demonstrated that 65.03% in total groundwater samples were appropriate for irrigation purpose. The HHR model and Monte Carlo simulation indicated that the non-carcinogenic nitrated risk was highest in children. Exposure frequency was the most sensitive factor (86.33% in total) influencing the total non-carcinogenic risk, indicated by sensitivity analysis. Compared with the two clusters of groundwater, surface water has a shorter circulation cycle and lower ion concentrations resulting in better water quality. This study can provide scientific basis for groundwater quality evaluation in other parts of the world.

Suitability of treated wastewater for irrigation and its impact on groundwater resources in arid coastal regions: Insights for water resources sustainability

Water scarcity threatens agriculture and food security in arid regions like Saudi Arabia. The nation produces significant quantities of municipal wastewater, which, with adequate treatment, could serve as an alternative water source for irrigation, thereby reducing reliance on fossil and non-renewable groundwater. This study assessed the appropriateness of using treated wastewater (TWW) for irrigation in a dry coastal agricultural region in Eastern Saudi Arabia and its impact on groundwater resources. Field investigations were conducted in Qatif to collect water samples and field measurements. A multi-criteria approach was applied to evaluate the TWW's suitability for irrigation, including complying with Saudi Standards, the Irrigation Water Quality Index (IWQI), the National Sanitation Foundation water quality index (NSFWQI), and the individual irrigation indices. In addition, the impact of TWW on groundwater was assessed through hydrogeological and isotope approaches. The results indicate that the use of TWW in the study area complied with the Saudi reuse guidelines except for nitrate, aluminum, and molybdenum. However, irrigation water quality indices classify TWW as having limitations that necessitate the use for salt-tolerant crops on permeable and well-drained soils. Stable isotopic analysis (δ2H, δ18O) revealed that long-term irrigation with TWW affected the shallow aquifer, while deep aquifers were minimally impacted due to the presence of aquitard layer. The application of TWW irrigation has successfully maintained groundwater sustainability in the study area, as evidenced by increased groundwater levels up to 2.3 m. Although TWW contributes to crop productivity, long term agricultural sustainability could be enhanced by improving effluent quality, regulating irrigation practices, implementing buffer zones, and monitoring shallow groundwater. An integrated approach that combines advanced wastewater treatment methods, community involvement, regulatory oversight, and targeted monitoring is recommended to be implemented.

Entropy-weighted water quality index, hydrogeochemistry, and Monte Carlo simulation of source-specific health risks of groundwater in the Morava River plain (Serbia)

Population growth, urbanization, industry, floods, and agriculture globally degrade groundwater in river plains, necessitating action for its quality assessment and management. Hence, a comprehensive methodology, including hydrogeochemical facies (Piper, Gibbs), irrigation indices (SAR, Wilcox), entropy-weighted water quality index (EWQI), positive matrix factorization (PMF), and Monte Carlo simulation of source-specific health risks was used in this study to analyze groundwater in the Morava river plain (Serbia). The results revealed a prevalent Ca-Mg-HCO3 groundwater type, influenced by water-rock interactions. Although groundwater was found suitable for irrigation, only 66.7 % of the samples were considered drinkable. Agricultural activities, natural processes, and municipal wastewater were identified as primary pollution sources. The incremental lifetime cancer risk (ILCR) and hazard index (HI) threshold exceedance for adults and children ranged from 8.5 % to 39 % of the samples, with arsenic identified as the most risk-contributing contaminant. These findings provide valuable insights for researchers studying groundwater vulnerability in river plains.

A hydrochemical and isotopic approach for source identification and health risk assessment of groundwater arsenic pollution in the central Yinchuan basin

Arsenic contamination of groundwater is becoming a major global issue as it can severely affect the safety of drinking water and human health. In this paper, 448 water samples were investigated to study the spatiotemporal distribution, source identification and human health risk of groundwater arsenic pollution in the central Yinchuan basin by applying a hydrochemical and isotopic approach. The results showed that arsenic concentrations in groundwater ranged from 0.7 μg/L to 26 μg/L with a mean of 2.19 μg/L, and 5.9% of samples were above 5 μg/L, indicating the arsenic pollution of groundwater in the study area. High arsenic groundwater was mainly distributed in the northern and eastern areas along the Yellow river. The main hydrochemistry type of high arsenic groundwater was HCO3·SO4-Na·Mg, and the dissolution of arsenic-bearing minerals in sediment, irrigation water infiltration and aquifer recharge from the Yellow river were the main sources of arsenic in groundwater. The arsenic enrichment was dominantly controlled by the TMn redox reaction and the competitive adsorption of HCO3-, and the influence of anthropogenic activities was limited. The health risk assessment suggested that the carcinogenic risk of As for children and adults greatly exceeded the acceptable risk threshold of 1E-6, displaying a high carcer risk, while the non-carcinogenic risks of As, F-, TFe, TMn and NO3- in 2019 were largely higher than the acceptable risk threshold (HQ > 1). The present study provides insight into the occurrence, hydrochemical processes and potential health risk of arsenic pollution in groundwater.

Water quality and health risk assessment of heavy metals in groundwater of Ranbir Singh Pura tehsil of Jammu and Kashmir, India

Groundwater is one of the important sources available for drinking, agricultural, domestic, and various other purposes in the study area. Study area is having agricultural importance and is famous for Basmati rice production in the world. In order to assess water suitability for irrigation and drinking purposes, 25 sampling sites were selected and water samples were collected from handpumps, borewells and motors from May 2022 to June 2022. Fifteen physico-chemical parameters and water quality index (WQI) was calculated to assess the drinking water suitability. The results obtained then compared with the BIS (2012) and WHO drinking water guidelines. For irrigation water suitability, irrigation water quality index (IWQI) and other indices were calculated. Heavy metal health risk assessment was also evaluated using target hazard quotient (THQ), carcinogenic risks (CR), non-carcinogenic risks, heavy metal pollution index (HPI), etc. Study found 60% of water samples under poor category of WQI. All water samples were found suitable for irrigation purposes according to different indices except for permeability index for which only 32% samples were found suitable. IWQI classifies 52%, 32%, and 12% of water samples under moderate, low, and no restriction category respectively. Groundwater of the study area found to be contaminated with copper (Cu), iron (Fe), lead (Pb), and chromium (Cr) while low contamination of zinc (Zn) and arsenic (As) was found according to heavy metal evaluation index (HEI). High contamination of chromium (HPI= 9740.8) and lead (HPI=188) was recorded as per HPI. HQ value for men, women, and children in case of zinc were found safe while HQ values for copper and lead in all population groups were found at risk. Overall, the study area was found highly contaminated with the lead, copper, and chromium concentrations. Thus, study recommends regular monitoring of the groundwater of study area as well as treatment before using this water for drinking purposes.

Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques

Groundwater is the main source to answer the irrigation supply in several arid and semi-arid areas. In the present work, groundwater quality for irrigation purposes in the arid region of Menzel Habib (Tunisia) for thirty-six groundwater samples is assessed considering the application of different conventional water quality indicators, particularly, electrical conductivity (EC), sodium absorption ratio (SAR), soluble sodium percentage (SSP), magnesium adsorption ratio (MAR), Kelly ratio (KR), and permeability index (PI). The results obtained indicate a variability for EC: 3.06 to 14.98 mS.cm^-1; SAR: 4.08 to 19.30; SSP: 35.78 to 71.53%; MAR: 34.19 to 56.01; PI: 38.47 to 72.74; and KR: 0.56 to 2.47. These results suggest that groundwater from Menzel Habib aquifer system is classified between excellent to unsuitable according to the applied water quality indices. Furthermore, the groundwater samples are also plotted in the Richards diagram classification system, based on the relation between SAR and EC, suggesting that almost groundwater samples present a harmful quality. Moreover, fuzzy logic model has been proposed and created to assess groundwater quality for irrigation. The membership functions are constructed for six significant parameters such as EC, SAR, SSP, MAR, KR, and PI and the rules are, then, fired to get a simple Fuzzy Irrigation Water Quality Index (FIWQI). The obtained groundwater quality results suggest that 3% of the samples from Menzel Habib region are considered as "good" for irrigation, 3% are classified as "good to permissible", 33% with a "permissible" quality, 36% "permissible to unsuitable", while 25% of groundwater present an "unsuitable" quality. Thus, the use of fuzzy logic techniques has more reliable and robust results by overcoming the uncertainties in the decision-making attributed to the conventional methods by the creation of new classes (excellent to good, good to permissible, and permissible to unsuitable) in addition to the classes proposed by Richards diagram classification (excellent, good, permissible, and unsuitable) to assess the groundwater quality suitability for irrigation purposes.

Hydro-chemical assessment of coastal groundwater aquifers for human health risk from elevated arsenic and fluoride in West Bengal, India

The vulnerability of groundwater in the coastal regions in terms of As, F^-, and NO₃^- exposure is growing rapidly. Hence, the present study focused on assessing groundwater quality, ecological richness, and HR in the coastal districts of West Bengal by applying field-based CD, GWQI, ERI, and HRI techniques. After assessing the GW vulnerability, it is stated that approximately 40-50 % area of the two selected coastal district's GW is poor to very poor in quality, the ecology of GW is threatened, and human health is faced serious risk for both dry and wet season. The Wilcox and USSL diagram verified that nearly 50 % GW aquifers of coastal district of West Bengal are not fit for irrigation and drinking. The findings of this study will be beneficial to manage and control groundwater vulnerability in the coastal regions for water scientists, policy makers, and researchers as well in sustainable way.