Trends In Groundwater Quality Research Articles

GIS based geostatistical modelling and trends analysis of groundwater quality for suitable uses in Dhaka division

Preserving the quality of groundwater has become Bangladesh’s primary challenge in recent years. This study explores temporal trend variations in groundwater quality on a broader scale across 18 stations within the Dhaka division over 35 years. The data set encompasses an analysis of 15 distinct water quality parameters. Modified Mann-Kendal, Sens Slope and Mann-Kendal tests were performed to determine the trend’s variation and slope. In addition, the spatial–temporal changes in the quality of groundwater are studied through Geographic Information System (GIS) mapping and Piper diagram was applied to identify the unique hydrochemical properties. This is the first study conducted on this area using various trends analysis and no in-depth study is available highlighting the trends analysis of groundwater quality on a larger magnitude. In contrast, the correlation matrix reveals a high association between Mg2+ and SO42−, Na+ and Cl− that affects salinity and overall hardness at the majority of sites. The Piper diagram also demonstrates that the groundwater in Madaripur Sadar has major salinity issues. The analysis reveals a distinctive dominance of bicarbonate (HCO3−) ions across all sampling stations, with (HCO3−) equivalent fractions consistently ranging from 0.70 to 0.99 which can cause a significant impact on groundwater uses. This extensive analysis of long-term groundwater quality trends in the Dhaka Division enables researchers to comprehend the overall transition of groundwater quality for hardness related complications in future. Moreover, it can be a baseline study considering the valuable implications and future steps for sustainable water resource management in this region.

Anthropogenic Drivers of Spatial Trends in Groundwater Quality in the Upper Athi River Basin of Kenya, East Africa

Rapid urbanization and population growth in the upper Athi River basin in Kenya have increased the strain on the sub catchments water supply and sanitation situation. Due to increasing demand, inadequate supply of drinking water and lack of sanitation facilities, people in the sub-catchment are increasingly reliant on groundwater as a primary or supplementary water source. However, the use of on-site wastewater systems and agricultural pollution, mainly from runoff containing fertilizers, pesticides, herbicides, and faeces, pose a threat to groundwater in the sub catchment. Subsequently, the current study was conducted in the Thiririka sub catchment, Kiambu County, Kenya, to determine the safety of groundwater sources and to examine the factors influencing groundwater quality in the catchment area. This study assessed the influence of anthropogenic activities on the physical, chemical, and bacteriological quality of groundwater in the Upper Athi River basin of Kenya between April and June 2022. Twenty variables were analyzed and compared with water quality standards to determine hydro chemical characteristics, evidence of contamination, and suitability of groundwater. Shallow wells (SW) had higher concentrations of major ions and key parameters than boreholes (BH), such as alkalinity (7%), turbidity (96%), nitrates (92%), sulfates (48%), phosphates (93%), chlorides (77%), potassium (84%), sodium (30%) and fecal coliforms (99%) significant at p < 0.01. Concentrations of eleven water quality variables however were comparable in both systems. Farming, animal husbandry, and pit latrines were negatively but significantly correlated with the water quality of SW explaining substantial amounts of variation (≤ 45%) in concentrations of water quality variables. Ionic and coliform levels increased with decreasing distance and vice versa. IDW interpolation maps were generated in ArcGIS software to determine the spatial variability of groundwater quality in the basin. Anthropogenic activities such as pit latrines and animal husbandry impaired the quality of groundwater which in most cases was not potable.

Early Warning of Regional Groundwater Pollution： A Case Study for Plain Area of Barkol-Yiwu Basin

Groundwater pollution early warning is an effective means for regional groundwater pollution prevention. The groundwater pollution early warning model coupled with the current situation of groundwater quality, groundwater quality variation trend, and groundwater pollution risk were applied to the plain area of Barkol-Yiwu Basin, and the regional scale groundwater pollution early warning was realized by combining the early warning of groundwater quality status and trend. The TOPSIS method based on comprehensive weight was used to evaluate the current situation of groundwater quality. The variation trend of groundwater quality was analyzed by calculating the trend interpolation results of 18 in-situ groundwater quality monitoring wells. The groundwater vulnerability map, groundwater pollution load map, and groundwater function value map were superimposed using the superposition index method to evaluate groundwater pollution risk. The results showed that the groundwater quality was good and relatively good, and the poor groundwater quality in some areas was mainly affected by the shallow groundwater depth and the large porosity of the vadose zone. Groundwater quality was stable from 2011 to 2022, mainly due to the leakage of wastewater generated by industries and agriculture into groundwater, resulting in the deterioration of groundwater quality in some areas. Groundwater pollution risk was generally low, and the dual effects of high vulnerability and high pollution load of groundwater led to local areas with high pollution risk. The early warning level of groundwater pollution was generally low, and the heavy and highly heavy warning areas accounted for 16.4% and 17.5% of the study area, respectively, mainly distributed in Xiamaya Township of Yiwu County and northern Santanghu Town, Dahongliuxia Township, and Dahe Town of Barkol County. The quaternary sediments exposed were mainly sandy pebbles, with developed pores and strong water permeability. The interception and adsorption capacity of pollutants were weak. Pollutants produced by industries, agriculture, and life easily leaked into groundwater aquifers, resulting in poor groundwater quality and high risk of groundwater pollution, which ultimately led to a high early warning level of groundwater pollution in some areas. The research on early warning of groundwater pollution provided an important theoretical basis for the development of groundwater pollution remediation.

Exploring Groundwater Quality Trends in Valliyar Sub-Basin, Kanniyakumari District, India through Advanced Machine Learning Techniques

The assessment of water quality assumes a position of utmost significance as it plays a critical role in upholding ecological balance and safeguarding the well-being of human populations. To achieve these goals, an in-depth consideration of water quality trends is essential, as it offers comprehension into the intricate interplay between various elements within aquatic ecosystems. As a consequence, the proposed work investigates the water quality trends specifically within the Valliyar sub-basin, which encompasses the geographical areas of Kattathurai, Colachal, Thuckalay, and Villukuri. The temporal scope of investigation spans from the year 2000 to 2018 using the dependent variable of water quality parameters with dependent variables of climate data. Recognizing the need for advanced methodologies to tackle the multifaceted nature of water quality dynamics, this research harnesses the power of pioneering machine learning techniques. Two notable approaches, the Radial Bias Function Neural Network (RBFNN) and the DenseNet-121-based Convolutional Neural Network (CNN), are brought into performance. The primary objective is to leverage these techniques to forecast water quality trends for the next twenty-two years. The effectiveness of various machine learning models in predicting water quality is evaluated using the following key performance metrics: the Mean-Square Error (MSE), Mean Absolute Percentage Error (MAPE) and Root-Mean-Square Error (RMSE). Notably, the DenseNet CNN model exhibits accurate prediction among the Artificial Neural Network (ANN), Support Vector Machine (SVM), and Deep Learning (DL) models. This research underscores the significance of machine learning techniques, with DenseNet CNN model emerging as a particularly promising tool in this domain.

Prediction of ground water quality in western regions of Tamilnadu using LSTM network

Assessing and safeguarding groundwater quality is critical for sustaining life in water-scarce regions like western Tamil Nadu. The motivation behind this study stems from the pressing need to address water quality challenges in a region grappling with scarcity. Despite existing efforts, a notable research gap exists in predictive tools that comprehensively capture the nuanced temporal variations and trends in groundwater quality. This is where the LSTM network steps in, showcasing exceptional accuracy in short-term predictions and discerning long-term trends. This research uses Long Short-Term Memory (LSTM) networks, a variant of recurrent neural networks, to predict groundwater quality in South Indian Regions, especially in Tamil Nadu. Extensive data, encompassing parameters such as pH, dissolved oxygen, turbidity, and various chemical constituents, were gathered over an extended timeframe. The LSTM model was then trained on this historical dataset, factoring in temporal dependencies and seasonality inherent in groundwater quality data. The validation process rigorously tests the LSTM model against actual groundwater quality measurements. The results were impressive, as the model demonstrated a remarkable ability to unravel the complex variations in groundwater quality.

Utilizing geographic information system and indexing to evaluate irrigation suitability of groundwater in Kalihati Upazila, Bangladesh

The aim of this research was to evaluate groundwater quality for irrigation in Kalihati Upazila, Bangladesh, a region that is significantly reliant on groundwater for crop development, especially during dry periods. By combining hydrochemical analysis and Geographic Information System (GIS), the research examined the physicochemical attributes and their spatial distribution. Fifteen groundwater samples from various locations were analyzed to measure parameters such as sodium adsorption ratio (SAR), soluble sodium percentage (SSP), residual sodium carbonate (RSC), magnesium adsorption ratio (MAR), electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), Kelly's ratio (KR), permeability index (PI), and potential salinity (PS). The pH of the groundwater ranged between 5.51 and 7.53, indicating slightly acidic to moderately alkaline conditions suited for irrigation. The EC ranged between 115.7 and 458 μS/cm, mostly falling into the "excellent" or "good" categories. Groundwater displayed irrigation suitability with TDS below 182 ppm and low SAR values, but variable RSC and MAR values indicated localized water quality issues. Based on the irrigation water quality index, all samples were within the "permissible" range. However, GIS-generated maps showed disparities in groundwater quality across the study area. Correlation matrices revealed significant links between various factors. Both the Piper and Gibbs diagrams displayed a prevalent Ca-HCO3 groundwater type influenced by geological formations. Overall, the study confirmed groundwater's appropriateness for irrigation while recommending periodic evaluations due to a few uncertainties. In conclusion, the study found that hydrochemical analysis, GIS mapping, and correlation matrices reveal groundwater quality and spatial trends, allowing for sustainable water resource management and agricultural advancement.

Hydrogeochemical changes during artificial groundwater well recharge

Artificial groundwater recharge is a relatively economic and efficient method for solving shortages and uneven spatial-temporal distribution of water resources. Changes in groundwater quality during the recharge process are a key issue that must be addressed. Identifying the hydrogeochemical reactions that occur during recharge can be vital in predicting trends in groundwater quality. However, there are few studies on the evolution of groundwater quality during artificial recharge that comprehensively consider environmental, chemical, organic matter, and microbiological indicators. Based on an artificial groundwater recharge experiment in Xiong'an New Area, this study investigated the hydrogeochemical changes during groundwater recharge through a well. The results indicate that (1) as large amounts of recharge water (RW) were injected, the groundwater level initially rose rapidly, then fluctuated slowly, and finally rose again. (2) Water quality indicators, dissolved organic matter (DOM), and microbial communities were influenced by the mixture of RW and the background groundwater before recharge (BGBR), as well as by water-rock interactions, such as mineral dissolution-precipitation and redox reactions. (3) During well recharge, aerobic respiration, nitrification, denitrification, high-valence manganese (Mn) and iron (Fe) minerals reduction dissolution, and Mn2+ and Fe2+ oxidation-precipitation occurred sequentially. (4) DOM analysis showed that protein-like substances in the BGBR were the main carbon sources for aerobic respiration and denitrification, while humic-like substances carried by the RW significantly enhanced Mn and Fe minerals reduction dissolution. Therefore, RW quality significantly affects groundwater quality after artificial groundwater well recharge. Controlling indicators, such as dissolved oxygen (DO) and DOM, in the RW can effectively reduce harm to groundwater quality after recharge. This study is of theoretical and practical significance for in-depth analysis of the evolution of groundwater quality during artificial well recharge, prediction of trends in groundwater quality during and after recharge and ensuring groundwater quality safety.

Impact of mine closure on groundwater resource: Experience from Westrand Basin-South Africa

The mining sector is at the edge of expanding to cater for natural resources that are much needed for technological development and manufacturing. Mushrooming of mines will consequently increase the number of mines closure. Moreover, mines closure have adverse impact on the environment at large and specifically on water resources. This study analyses historical groundwater quality parameters in mine intensive basin of Westrand Basin (WRB) to understand the status of groundwater quality in relation to mining activities and mine closure. Geographic information system (GIS) was used to map the spatio-temporal variation of groundwater quality in the basin and groundwater quality index (GQI) to evaluate its status. The coefficient of variation (CV) was applied to understand the stability of groundwater quality after the mine closure. Results indicated unstable and altered trend with increasing levels of acidity and salts concentration around the mines vicinity following the mine closure. The resultant maps indicated a significant deterioration of groundwater quality around the WRB with concentrations decreasing downstream. Obtained average GQI for the study period of 1996–2015 suggested a moderate groundwater quality at a range of GQI = 64–73. The CV indicated varying water quality at CV > 30% suggesting presence of source of contamination. Observed groundwater quality trends in Westrand basin suggested that mines closure present potential threat on groundwater quality and thus, a need for a robust mine closure plan and implementation.

Groundwater Quality Assessment Using Multi-Criteria GIS Modeling in Drylands: A Case Study at El-Farafra Oasis, Egyptian Western Desert

The most critical issue that was the main research interest is its groundwater quality which is vital for public health concerns. Groundwater is a significant worldwide water supply for diverse communities, especially in dryland regions. Groundwater quality assessment in desert systems is largely hindered by the lack of hydrological data and the remote location of desert Oases. This study provides a preliminary understanding of the influences of climate, land usage, and population growth on the groundwater quality in El-Farafra Oasis in the Western Desert in Egypt from 2000 to now. Therefore, the study’s main objective was to determine the extent of change in temporal water quality and the factors causing it. The present study integrates chemical analyses and geospatial modeling better to assess groundwater quality in the study area. A chemical analysis of thirty-one groundwater samples from wells representing each study area was carried out during three time periods (2000, 2010, and 2022). Several chemical properties of groundwater samples gathered from wells in the research area were analyzed. Furthermore, the groundwater quality trend from 2000 to the present was identified using three approaches: Wilcox and Schoeller Diagram in Aq.QA software, interpolation in the ArcGIS software, and Ground Water Quality Index (GWQI). Moreover, the influence of changing land usage on groundwater quality was studied, and it was found that the increase in agriculture and urbanization areas is linked to groundwater quality degradation. The findings revealed that the barren area in 2000, 2010, and 2022 was 371.7, 362.0, and 343.2 km2, respectively, which indicates a substantial decrease of 6.2% within this research timeframe. In contrast, agriculture and human-made structures have expanded by 1.8%. Also, population growth has led to an increase in water consumption as the population has grown at a rate of 7.52% annually from 2000 to 2020. As the climatic condition increases from 2000 to 2022, these changes could extend to the water quality in shallow aquifers with increasing evaporation. Based on the water quality spatial model, it is found that, despite a declining tendency in the rate of precipitation and an expansion in agricultural areas and population growth, the water quality was still appropriate for human and farming consumption in large areas of the study area. The presented approach is applicable to the assessment of groundwater in desert regions in the Middle East area.

Geogenic controls on the high levels of uranium in alluvial aquifers of the Ganga Basin

The Indo-Gangetic Basin (IGB) alluvial aquifer system provides a reliable drinking water supply to over half a billion people. Understanding the groundwater quality, aquifer processes, groundwater storage, and depletion trends in the IGB alluvial aquifer system— one of the world's most important freshwater resources has been the focus of many previous studies. However, understanding what governs uranium variability in the IGB alluvial aquifer system— for example, whether uranium is released from natural deposits or anthropogenic sources such as mill tailing, emissions from the nuclear industry, combustion of fossil fuels, and phosphate fertilizers— are under-explored but critically important for constraining the environmental fate of uranium. Here, we present surface and groundwater uranium concentration data in the central parts of the IGB alluvial aquifer system. We find a high concentration of groundwater uranium above the World Health Organization provisional guideline value of 30 μg/L in 17% (n = 29) of collected groundwater samples, whereas other heavy metals, namely Cr, Ni, Pb, and Cd were within the recommended range. Trace element systematic demonstrates that anomalous uranium enrichment is primarily derived from geogenic sources, while uranium mobility is predominantly controlled by the alkalinity (a proxy for bicarbonate), hence by soluble uranyl carbonate complexes. As in the year 2020, the Bureau of Indian Standard incorporated uranium as a possible drinking water contaminant, our dataset calls for additional assessments of groundwater uranium concentrations in Indian groundwater resources because uranium concentration data are scarce compared to other geogenic contaminants such as arsenic and fluoride. We conclude that uranium, like arsenic and fluoride, is also critical geogenic contaminant in the alluvial aquifers that needs to be better monitored as higher levels of uranium in drinking water have adverse health effects.

Assessment of Groundwater Variability in Mbagathi River Catchment

Groundwater is increasingly an important source of water. Assessment of its variability spatially and temporally besides quality and quantity is not easy. Groundwater contains multiple range of chemical parameters. This contribution proposes a water quality index (WQI) to synthesize various groundwater quality parameters (Na + , F - , Cl ‑ , SO 4 2- , Ca 2+ , Mg 2+ , K + and NO 3 - ) in Geographic Information Systems (GIS) based environment. The parameters are analyzed relative to the Kenya Standard (KS) East Africa Standard (EAS) 12:2018 standard in the Mbagathi river catchment, a metropolitan area, Southwest of Nairobi, Kenya. Prediction maps for three seasons (wet, moderate and dry) and a combination all three seasons were produced. Based on WQI classification, results showed 36% - 28% good, 58% - 61% fair, and 6%-11% poor. A noticeable declining groundwater quality trend from wet to dry seasons was observed. Groundwater quality deterioration was observed to be greater in areas with higher yield and water rest level. Groundwater is safe for drinking, barring the elevated fluoride content in some areas. Application of GIS was a valuable tool in exploration of groundwater characteristics. Maps generated can serve as first-hand information for groundwater development. Keywords : groundwater, quality, kriging, semivariogram, variability DOI: 10.7176/JEES/12-4-03 Publication date: April 30 th 2022

Impact of land use/land cover changes on water quality and human health in district Peshawar Pakistan

The quality and quantity of groundwater resources are affected by landuse/landcover (LULC) dynamics, particularly the increasing urbanization coupled with high household wastewater discharge and decreasing open lands. This study evaluates temporal changes of groundwater quality for 2012 and 2019, its relation to Landuse/landcover, and its impact on Peshawar's residents (study area), Pakistan. A total of 105 and 112 groundwater samples were collected from tube wells in 2012 and 2019. Samples were then analyzed for seven standard water quality parameters (i.e., pH, electric conductivity (EC), turbidity, chloride, calcium, magnesium, and nitrate). Patient data for waterborne diseases were also collected for the years 2012 and 2019 to relate the impact of groundwater quality on human health. Landsat satellite images were classified for the years 2012 and 2019 to observe landuse/landcover dynamics concerning groundwater quality. Results manifested a decrease in groundwater quality for the year 2019 compared to 2012 and were more highlighted in highly populated areas. The nitrate concentration level was found high in the vicinity of agricultural areas due to the excessive use of nitrogenous fertilizers and pesticides, and thus the methemoglobinemia patients ratio increased by 14% (48–62% for the year 2012 and 2019, respectively). Besides, Urinary Tract Infections, Peptic Ulcer, and Dental Caries diseases increased due to the high calcium and magnesium concentration. The overall results indicate that anthropogenic activities were the main driver of Spatio-temporal variability in groundwater quality of the study area. The study could help district health administration understand groundwater quality trends, make appropriate site-specific policies, and formulate future health regulations.

Association of Radionuclide Isotopes with Aquifer Solids in the Midwestern Cambrian–Ordovician Aquifer System

Groundwater, an important source of drinking water globally, is susceptible to contamination by naturally occurring metals and radionuclides. Regional trends in groundwater quality are useful in pr...

Groundwater quality trend and trend reversal assessment in the European Water Framework Directive context: an example with nitrates in Italy

Groundwater resources are of utmost importance in sustaining water related ecosystems, including humans. The long-lasting impacts from anthropogenic activities require early actions, owing to the natural time lag in groundwater formation and renewal. The European Union (EU) policy, within the implementation of the Water Framework Directive (WFD), requires Member States to identify and reverse any significant and sustained upward trend in the concentration of pollutants, defining specific protection measures to be included in the River Basin Management Plans (RBMP). In Italy, official guidelines for trend and trend reversal assessment have been published recently. Statistical methods, such as the Mann-Kendall test for trend analysis and the Sen’s method for estimating concentration scenarios, should be applied at the fixed terms stated by the WFD implementation cycles to identify upward trends, while the Pettitt test is proposed for the identification of trend reversal. In this paper, we present an application of a slightly modified version of the Italian Guidelines to a groundwater body in Northern Italy featuring nitrate pollution and discuss its advantages and limitations. In addition to Pettitt test, for the trend reversal analysis, we apply the Mann-Kendall test in two sections and compare the results. We conclude that this method seems more reliable than Pettitt test to identify a reversal point in quality time series. The overall procedure can be easily applied to any groundwater body defined at risk across Europe, for the assessment of the upward trends of pollutants and their reversal, even with little chemical monitoring data. Although focused on the EU legislative framework, this procedure may be relevant for a wider context, allowing to individuate upward trend as early warning for contamination processes in an integrated water resources management context.

Groundwater Quality Characterization in an Overallocated Semi-Arid Coastal Area Using an Integrated Approach: Case of the Essaouira Basin, Morocco

In this study, hydrogeochemical analyses were combined with geographic information system (GIS) tools to investigate salinization sources of groundwater in the downstream part of the Essaouira basin, and to analyze the spatiotemporal trends in groundwater quality. To assess groundwater suitability for drinking purposes, the quality of sampled water was compared with the World Health Organization (WHO) and the Moroccan guidelines. Wilcox and US salinity laboratory (USSL) diagrams were used to evaluate groundwater suitability for irrigation. Hydrogeochemical analyses revealed that groundwater is of Na-Cl and Ca-Mg-Cl types. The analyses of the correlation between the chemical elements showed that the water–rock interaction and the reverse ion exchange are the major processes impacting groundwater degradation in the study area. The study of groundwater suitability for drinking and irrigation purposes shows that groundwater quality in the study area is permissible, but not desirable for human consumption. Additionally, groundwater is permissible for agricultural use but with high-salinity hazards. The spatial distribution of the physicochemical elements shows a general upward gradient from the north to the south and from the east to the west. The trend in groundwater quality during the last five years shows a shifting in the quality from the mixed Ca-Mg-Cl to the Na-Cl type.

Countrywide Groundwater Quality Trend and Suitability for Use in Key Sectors of Korea

Under changing climate, increasing groundwater use has risen the concern for groundwater quality variations over recent years, to maintain a healthy ecosystem. The objectives were to identify trend of temporal variations in groundwater quality and its suitability for different uses in Republic of Korea. Water quality data were collected from 198 monitoring stations of Groundwater Quality Monitoring Network (GQMN), annually for the period of ten years (2008–2017). Non-parametric trend analysis of a Mann–Kendall test and Theil–Sen’s slope was done on groundwater physico-chemical data of ten years. Groundwater suitability evaluation was done for use in main sectors including domestic (drinking) and agriculture (irrigation). For drinking suitability analysis, results were compared with World Health Organization (WHO) and Korean Ministry of Environment (KME) established guidelines. For irrigation suitability evaluation, electrical conductivity (EC), Sodium Adsorption Ratio (SAR), percent of Na+, Residual Sodium Carbonate (RSC), US Salinity Laboratory (USSL), and Wilcox diagram were used. Most significantly, water type belongs to Ca-HCO3 and Ca-SO4 types, but a small proportion belongs to Na-CO3 and Na-Cl types. Approximately, 96% and 93% of groundwater samples are suitable for drinking, based on WHO and KME guidelines, respectively. Around 98% and 83% of groundwater samples are in suitable range for irrigation use, based on USSL and Wilcox diagrams, respectively.

Identifying areas of degrading and improving groundwater-quality conditions in the State of California, USA, 1974\u20132014

Areas of improving and degrading groundwater-quality conditions in the State of California were assessed using spatial weighting of a new metric for scoring wells based on constituent concentrations and the direction and magnitude of a trend slope (Sen). Individual well scores were aggregated across 2135 equal-area grid cells covering the entire groundwater resource used for public supply in the state. Spatial weighting allows results to be aggregated locally (well or grid cell), regionally (groundwater basin), provincially, or statewide. Results differentiate degrading (increasing concentration trends) areas with low to moderate concentrations (unimpaired) from degrading areas with moderate to high concentrations (impaired). Results also differentiate improving areas (decreasing concentration trends) in the same manner. Multi-year to decadal groundwater-quality trends were computed from periodic, inorganic water-quality data for 38 constituents collected between 1974 and 2014 for compliance monitoring of nearly 13,000 public-supply wells (PSWs) in the State of California. Mann-Kendall (MK) rank correlations and Sen’s slope estimator were used to detect statistically significant trends for the entire period of recorded data (long-term trend), for the period since 2000 (recent trend), for different pumping seasons (seasonal trend), and for reversals of trends. Statewide, the most frequently detected trends since 2000 were for nitrate (36%), gross alpha/uranium (10%), arsenic (14%), total dissolved solids (TDS) (23%), and the major ions that contribute to TDS (19–28%). The Transverse and Selected Peninsular Ranges (TSPR) and the San Joaquin Valley (SJV) hydrogeologic provinces had the largest percentage of areas with moderate to high nitrate concentrations and groundwater quality trends. Improving nitrate concentrations in parts of the TSPR is associated with long-term managed aquifer recharge that has replaced historical, agriculturally affected groundwater with low-nitrate recharge in parts of the TSPR. This example suggests that application of dilute, excess surface water to agricultural fields during the winter could improve groundwater-quality in the SJV over the long term.

Groundwater pollution early warning based on QTR model for regional risk management: A case study in Luoyang city, China

Groundwater pollution early warning has been regarded as an effective tool for regional groundwater pollution prevention, especially in China. In this study, the systemic model was established to assess the groundwater pollution early warning by integrating the present situation of groundwater quality (Q), groundwater quality trend (T) and groundwater pollution risk (R). The model integrated spatial and temporal variation of groundwater quality, and combined the state and process of the groundwater pollution. Q, T and R were assessed by the methods of fuzzy comprehensive assessment, Spearman or nonparametric Mann-Kendall trend test, and overlay index, respectively. Taking the Luoyang City as an example, the groundwater pollution early warning mapping was generated, and verified by corresponding the groundwater quality classes and the early warning degrees. The results showed that the groundwater was dominated by the levels of no warning and light warning, which accounted for 77% of the study area. The serious and tremendous warning areas were affected by the worse trend and relatively bad/bad present situations of groundwater quality with the typical contaminants of total hardness, nitrate, Hg and COD. In summary, the present situation of groundwater quality was the most important factor of groundwater pollution early warning mapping in the study area. The worse trend of groundwater quality played equally a key role in the local regions, as well as the high pollution risk, which was mainly affected by the pollution source loading. Targeted measures for groundwater pollution prevention were proposed in the corresponding degrees of groundwater pollution early warning. The QTR model was proved to be effective for assessing the regional groundwater pollution early warning. The accuracy of the model could be improved if there is further data acquisition of groundwater quality in longer time series and in larger number, and further investigation of pollution sources.The QTR model is proposed and proved to be effective for assessing regional groundwater pollution early warning.

Climate Change Impacts on Groundwater Resources in the Coastal Karstic Adriatic Area: A Case Study from the Dinaric Karst

The Bokanjac–Policnik system, as a complex set of mutually interrelated Dinaric karst catchments and sub-catchments, is a highly vulnerable and limited groundwater source for the wider Zadar area in northern Dalmatia, Croatia. Based on hydrogeological, hydrochemical, and hydrological research, including the prediction of groundwater discharge by the end of the twenty-first century, a complex study was performed with the following main aims: (1) groundwater protection in the present state, (2) assessment of future groundwater protection, and (3) prediction of drinking water availability and quality under the predicted climate change conditions. Long-term prediction of changes in groundwater quantity, as well as investigations of trends in groundwater quality, will allow us to protect this essential natural resource with respect to possible negative trends. The results showed that a significant decrease in the quantity of available groundwater is possible and that extraction will have to be well planned because any decrease in the groundwater pressure in this area will cause a further decrease in quality, especially regarding the possibility of seawater intrusions into the aquifer. The results of this study were incorporated in sanitary protection zones.

Assessing seasonal and long-term changes in groundwater quality due to over-abstraction using geostatistical techniques

Future climate change and the temporal variability of water availability may cause the deterioration of groundwater quality and increase depths to water tables. In this study, groundwater quality data of 347 monitoring sites from 2003 to 2016 from a region in Pakistan were used to analyze the spatiotemporal variability in different water quality parameters using the Mann–Kendall and Sen’s slope estimator tests. The results indicated a significant increasing trend (SIT) at 23% sites in pre-SAR (sodium adsorption ratio during the pre-monsoon season) and at 22% sites in pre-EC (electrical conductivity during the pre-monsoon season) over the entire study period. The spatial distribution modeling of groundwater quality trends indicated that a significant increasing trend was observed in EC at most of the monitoring sites during the pre-monsoon season (α = 0.05). The area with significant increasing trend of groundwater EC and SAR values increased during the pre-monsoon season and decreased during the post-monsoon season. A continuous significant increasing trend in EC and SAR was observed in the northern part of the study area during the period 2003–2016. This trend indicates that excessive groundwater abstraction in the area is causing adverse impacts on groundwater quality, and that management measures need to be urgently implemented to limit further degradation of groundwater quality.