Assessment and uncertainty analysis of groundwater risk

A DFN-based framework for probabilistic assessment of groundwater contamination in fractured aquifers

It is challenging to conduct groundwater contamination risk assessment in fractured aquifers containing a large number of complex fractures, especially in a situation where the uncertainty of massive fractures and fluid-rock interactions is inevitable. In this study, a novel probabilistic assessment framework based on discrete fracture network (DFN) modeling is proposed to assess the uncertainty of groundwater contamination in fractured aquifers. The Monte Carlo simulation technique is employed to quantify the uncertainty of fracture geometry, and the environmental and health risks of the contaminated site are probabilistically analyzed in conjunction with the water quality index (WQI) and hazard index (HI). The results show that the contaminant transport behavior in fractured aquifers can be strongly affected by the distribution of the fracture network. The proposed framework of groundwater contamination risk assessment is capable of practically accounting for the uncertainties involved in the mass transport process and effectively assessing the contamination risk of fractured aquifers.

Microbial community structural response to variations in physicochemical features of different aquifers

Introduction

The community structure of groundwater microorganisms has a significant impact on groundwater quality. However, the relationships between the microbial communities and environmental variables in groundwater of different recharge and disturbance types are not fully understood.

Methods

In this study, measurements of groundwater physicochemical parameters and 16S rDNA high-throughput sequencing technology were used to assess the interactions between hydrogeochemical conditions and microbial diversity in Longkou coastal aquifer (LK), Cele arid zone aquifer (CL), and Wuhan riverside hyporheic zone aquifer (WH). Redundancy analysis indicated that the primary chemical parameters affecting the microbial community composition were NO3 -, Cl-, and HCO3 -.

Results

The species and quantity of microorganisms in the river-groundwater interaction area were considerably higher than those in areas with high salinity [Shannon: WH (6.28) > LK (4.11) > CL (3.96); Chao1: WH (4,868) > CL (1510) > LK (1,222)]. Molecular ecological network analysis demonstrated that the change in microbial interactions caused by evaporation was less than that caused by seawater invasion under high-salinity conditions [(nodes, links): LK (71,192) > CL (51,198)], whereas the scale and nodes of the microbial network were greatly expanded under low-salinity conditions [(nodes, links): WH (279,694)]. Microbial community analysis revealed that distinct differences existed in the classification levels of the different dominant microorganism species in the three aquifers.

Discussion

Environmental physical and chemical conditions selected the dominant species according to microbial functions. Gallionellaceae, which is associated with iron oxidation, dominated in the arid zones, while Rhodocyclaceae, which is related to denitrification, led in the coastal zones, and Desulfurivibrio, which is related to sulfur conversion, prevailed in the hyporheic zones. Therefore, dominant local bacterial communities can be used as indicators of local environmental conditions.

Distribution, sources, and pollution levels of toxic metal(loid)s in an urban river (Ichamati), Bangladesh using SOM and PMF modeling with GIS tool

Indexical assessment coupled with a self-organizing map (SOM) and positive matrix factorization (PMF) modeling of toxic metal(loid)s in sediment and water of the aquatic environment provides valuable information from the environmental management perspective. However, in northwest Bangladesh, indexical and modeling assessments of toxic metal(loid)s in surface water and sediment are still rare. Toxic metal(loid)s were measured in sediment and surface water from an urban polluted river (Ichamati) in northwest Bangladesh using an atomic absorption spectrophotometer to assess distribution, pollution levels, sources, and potential environmental risks to the aquatic environment. The mean concentrations (mg/kg) of metal(loid)s in water are as follows: Fe (871) > Mn (382) > Cr (72.4) > Zn (34.2) > Co (20.8) > Pb (17.6) > Ni (16.7) > Ag (14.9) > As (9.0) > Cu (5.63) > Cd (2.65), while in sediment, the concentration follows the order, Fe (18,725) > Mn (551) > Zn (213) > Cu (47.6) > Cr (30.2) > Ni (24.2) > Pb (23.8) > Co (9.61) > As (8.23) > Cd (0.80) > Ag (0.60). All metal concentrations were within standard guideline values except for Cr and Pb for water and Cd, Zn, Cu, Pb, and As for sediment. The outcomes of eco-environmental indices, including contamination and enrichment factors and geo-accumulation index, differed spatially, indicating that most of the sediment sites were moderately to highly polluted by Cd, Zn, and As. Cd and Zn content can trigger ecological risks. The positive matrix factorization (PMF) model recognized three probable sources of sediment, i.e., natural source (49.39%), industrial pollution (19.72%), and agricultural source (30.92%), and three possible sources of water, i.e., geogenic source (45.41%), industrial pollution (22.88%), and industrial point source (31.72%), respectively. SOM analysis identified four spatial patterns, e.g., Fe-Mn-Ag, Cd-Cu, Cr-Pb-As-Ni, and Zn-Co in water and three patterns, e.g., Mn-Co-Ni-Cr, Cd-Cu-Pb-Zn, and As-Fe-Ag in sediment. The spatial distribution of entropy water quality index values shows that the southwestern area possesses "poor" quality water. Overall, the levels of metal(loid) pollution in the investigated river surpassed a critical threshold, which might have serious consequences for the river's aquatic biota and human health in the long run.

Health risk assessment of groundwater nitrogen pollution in Yinchuan plain

High nitrogen concentration of groundwater poses a threat to human health. This study evaluated the potential health risk of nitrogen pollution in Yinchuan plain by geostatistical analysis and triangular stochastic model considering different land use types, and identified the uncertainties of the parameters. 163 samples were collected from groundwater wells in different land use types. The results show that the concentration of NO₃^--N ranges from 0.059 to 450 mg/L, with an average of 22.439 mg/L. Approximately 32% of the samples exceed Grade III threshold (20 mg/L of N). The concentration of NH₄⁺-N ranges from 0.011 to 11 mg/L, with an average of 0.456 mg/L. The concentration of NO₂^--N ranges from 0.003 to 9.09 mg/L The NO₃^--N and NH₄⁺-N concentration in the groundwater of the unutilized land use is significantly lowest among all the land types. The concentration of nitrogen is highest in farmland use. The ranking of non-carcinogenic risk under different land types for infants, children, adult males and females is: farmland use > residential land use> unutilized land use. The non-carcinogenic risk value of farmland use is three times as much as that of the residential land use. Drinking groundwater can be potentially harmful to human health, and nitrogen pollutants pose an even greater threat to infant. At the same time, considering the impact of different land use types on groundwater would avoid overestimating or underestimating regional risk value. Triangular stochastic model is more sensitive to data changes and can reduce uncertainty. The contribution rate of nitrate concentration to risk is more than 83%, indicating that random sampling is needed to improve the reliability of evaluation results. The research results of this study will provide a new way to solve the uncertainty in groundwater security management.

Evaluation of sustainable groundwater utilization using index methods (WQI and IWQI), multivariate analysis, and GIS: the case of Akşehir District (Konya/Turkey)

Akşehir district is one of the regions where significant agricultural production and industrial activities are carried out. Groundwater is the most important water resource in this region used for different purposes, especially for drinking and irrigation water. In order to ensure sustainable water management in the study area, it is necessary to reveal the drinking and irrigation water quality of groundwater and to take precautions and determine the management plans. In the present study, groundwater quality was evaluated using water quality index methods (WQI and IWQI) and statistical analyses to determine the sustainable and most appropriate usage of groundwater. In addition, spatial distribution maps were prepared using GIS for drinking and irrigation WQI assessments of the groundwater. A total of 31 groundwater samples were collected from wells in October 2018 and physicochemical analysis results were evaluated. According to the results obtained with the WQI method, all groundwater samples in the study area are definitely not suitable for use as drinking water. According to the results obtained by the IWQI method, samples S23, S24, S25, S27, S28, S29, and S31 especially are not suitable for use as irrigation water. Statistical evaluations support the results obtained from WQI and IWQI methods. Also, factor analysis indicates that anthropogenic pollution, especially agricultural applications, is effective on the chemical and quality characteristics of groundwater samples in addition to the geological properties. As seen in the spatial distribution maps for WQI and IWQI results, while the quality of groundwaters around Doğruözü and Erdoğdu is not suitable for drinking water, the groundwater quality in the north-east of the study area is also unusable for irrigation water. Consequently, the use of groundwater in the region as drinking water can be dangerous for human health and alternative drinking water resources should be investigated. In addition, in order to ensure the sustainable use of groundwater, it is necessary to control agricultural activities in the region, to monitor the use of pesticides and fertilizers, and to encourage organic farming practices in the region.

Assessment of groundwater quality and usability of Salda Lake Basin (Burdur/Turkey) and health risk related to arsenic pollution

PURPOSE

In this study the aim was to analyze the seasonal concentration, groundwater quality, usage areas and arsenic-related health risk of major ions and heavy metals in groundwater samples collected from the Salda Lake basin.

METHODS

In this study, 42 groundwater samples were collected from springs and wells in dry and wet seasons in 2015. Hydrogeochemical evaluations were made using different diagrams such as Piper and Gibbs diagrams. Groundwater quality was determined by the water quality index method (WQI) and different diagrams. Finally, health risk assessments related to arsenic were performed.

RESULTS

The dominant water types are Mg-Ca-HCO3 and Mg-HCO3 in the wet season and Mg-HCO3 and Mg-HCO3-CO3 in the dry season. According to calculated WQI values ranged from 24.14 to 56.93 in the wet season ranged from 25.27 to 145.87 in dry season. This situation indicates that the quality of water samples is mostly good both seasons. AsT concentrations were between 2.1-6.3 μg/L in the dry season and 2.9-10.5 μg/L in the wet season. The risk of developing cancer due to arsenic exposure in healthy adults or children is very low. But arsenic has high non-carcinogenic and carcinogenic potentially harmful effect in the study area. In addition, water samples are not appropriate for use as drinking water in terms of fertilizers and trace element concentrations. Also, MH will be an important problem in waters that will be used as irrigation water. The use of some samples is not recommended as it may cause crusting on metal surfaces in industrial areas.

CONCLUSIONS

According to the results obtained, the quality of groundwater in the study area should be monitored and the usage areas should be determined accordingly.

Identification and uncertainty analysis of high-risk areas of heavy metals in sediments of the Yangtze River estuary, China

In this study, ordinary kriging (OK) and indicator kriging (IK) were used to analyze the uncertainty associated with high-risk areas of seven heavy metals (As, Cd, Cr, Cu, Hg, Pb, and Zn) in sediments of the Yangtze River estuary during four seasons. The OK results showed that the high-risk areas of Cd, Cr, Cu, Hg, and Pb had a high proportion, with the highest corresponding to Cr pollution (up to 60%). Predictions based on IK revealed that the proportion of high-risk areas of Cr, Cd, and Hg pollution were high, especially that of Cr was higher than 90%. However, there were uncertainties between the OK and IK results. The uncertainty results revealed that the uncertainty areas of Cr pollution were relatively large, accounting for about 30%, while those of Cd, Cu, and Hg pollution were lower than 10%.

Groundwater pollution source identification and apportionment using PMF and PCA-APCA-MLR receptor models in a typical mixed land-use area in Southwestern China

The quality of groundwater in a region is regarded as a function of natural and anthropogenic factors. Receptor models have advantages in source identification and source apportionment by testing the physicochemical properties of receptor samples and emission sources. In our study, receptor models PMF and PCA-APCS-MLR were developed to qualitatively identify the latent sources of groundwater pollution in the study area and quantitatively evaluate the contribution of each source to groundwater quality. The performances of PMF and APCS-MLR models were compared to test their applicability on the assessment of groundwater pollution sources. Results showed that both of the models identified five sources of groundwater contamination with similar main load species of each potential source. The comparable source apportionment of species NO₂^- and NO₃^- with two models indicated the reliable source estimation for these species, whereas the contributions of sources to species Fe, Mn, Cl^-, SO₄^2- and NH₄⁺ were significantly different due to the large variability of data, difference of uncertainty analysis and algorithm of unexplained variability in the two models. R-squared value between observation and model prediction was 0.603-0.931 in PMF and 0.497-0.859 in PCA-APCS-MLR. The significant disagreement of average source contribution was detected in agricultural source and unexplained variability using PMF and PCA-APCS-MLR models. Average contributions of other sources to groundwater quality parameters had similar estimates between the two models. Higher R² and smaller proportion of unexplained variability in the PMF model suggested that PMF approach could provide more physically plausible source apportionment in the study area and a more realistic representation of groundwater pollution than solutions from PCA-APCS-MLR model. The study showed the advantages of application of multiple receptor models on achieving reliable source identification and apportionment, particularly, providing a better understanding of applicability of PMF and PCA-APCS-MLR models on the assessment of groundwater pollution sources.

Assessing Vegetation Dynamics and Landscape Ecological Risk on the Mainstream of Tarim River, China

The Tarim River (TR), the longest inland river at an arid area in China, plays a critical role in the sustainable development of the regional ecological environment. This study presents the spatial-temporal variations in the vegetation coverage at regional and pixel scales and its driving factors on the TR mainstream. The latest dataset of normalized difference vegetation index (NDVI) and a vegetation coverage index (fc) over the period from 2000–2015 were analyzed with the unary linear regression and the partial correlation. On the basis of land use data, we further built the landscape ecological risk index and assessed the ecological risk level of the mainstream. Our results suggest that the vegetation coverage index demonstrated fluctuations but denoted a generally upward trend in the TR mainstream, the vegetation improvement areas are far greater than the degraded areas during the study period. Apparently, the overflow days in the TR mainstream and the cumulative amount of water transport are the two main factors that dominate the vegetation coverage. The ecological risk level varies throughout the TR with a high-to-low spatial distribution from upstream to downstream, and the overall landscape ecological risk of the whole basin exhibits an upward tendency. Above all, our study provides a framework with the remote sensing data to assess vegetation coverage and landscape ecological risk which can help design and implement reliable strategies for the ecological management and vegetation restoration in the Tarim River Basin.

Risk assessment framework for nitrate contamination in groundwater for regional management

Nitrate pollution in groundwater is now one of the most important environmental problems all over the world. For this purpose, a new framework for risk screening and assessment of groundwater nitrate was proposed according to source-pathway-receptor-response model to provide basic for defining environmental management strategies. The framework is composed of groundwater relative risk model (RRM), groundwater contamination risk assessment (CRA), and human health risk assessment (HHRA). The framework is applied in the lower Liaohe river basin plain, northeast of China. The results showed that the priority area with high groundwater relative risk in study area was successfully screened by RRM. Furthermore, the sites with high human health risk for public by groundwater nitrate were selected as hazardous areas. This framework promotes systematic integration of risk assessment of groundwater nitrate and expands traditional research on groundwater management from a scale-based approach to crucial insights into pollution.

Groundwater pollution and risk assessment based on source apportionment in a typical cold agricultural region in Northeastern China

Increasing anthropogenic contamination poses a significant threat to groundwater security. Identifying potential contamination sources and apportioning their corresponding contributions are of vital importance for the prevention of contamination and management of groundwater resources. In this study, principal component analysis (PCA), modified grey relational analysis (MGRA), absolute principal component score-multiple linear regression (APCS-MLR), and positive matrix factorization (PMF) receptor modeling technologies were employed to evaluate the groundwater quality and apportion the potential contamination sources in the Lalin river basin, a main grain production district in the northeast of China. The contamination assessment with PCA and MGRA suggested that the groundwater in Lalin river basin was polluted due to human activities. The PCA method identified five and four potential contamination sources in wet and dry seasons, respectively, and the main sources were basically same. The APCS-MLR and PMF methods apportioned the source contributions to each groundwater quality variable. The final results showed that agricultural sources including waste water, agrochemicals and fertilizers were identified as the main sources of groundwater contamination both in wet and dry seasons. In addition, groundwater management strategies learned from the advanced experiences were discussed to protect the groundwater system in that region.