Search

This study retains the basic structure of DRASTIC model and obtains more specific evaluation results by adding land-use type and groundwater resource yield parameters, modifying the rating scale and weight of nine parameters. Comparison of the modified DRASTIC-LY vulnerability map with the map of the original DRASTIC-LY method revealed differences in 40.49% of the study area. The risk map shows that the very high vulnerability area decreased from 2.79 to 1.67%, while the high vulnerability area increased from 18.70 to 28.86%. Areas with low vulnerability increased by 10.15%, while areas with medium vulnerability decreased by 15.01%. The areas with very high groundwater vulnerability are mainly distributed in the Hanbin area on the north bank of the Han River, the areas with high are mainly concentrated on both sides of the Fujia River, while the areas with low are distributed in most areas in the west of the basin. The Pearson's correlation factor was 0.0583 in the original DRASTIC model, 0.1113 in the DRASTIC-LY method and 0.8291 in the modified DRASTIC-LY model, which indicated that the revised DRASTIC-LY model was more appropriate than the original model. The results can help the government with the protection of water resources. HIGHLIGHTS Improve the DRASTIC model.; Determine the weight, grade and category of each parameter.; Based on the sensitivity analysis and model validation results, construct the best model suitable for groundwater vulnerability assessment.; The results of this study will help government managers improve the composition of water use and strengthen the protection of vulnerable aquifers.;

In this study, a hydrochemical investigation was conducted in Shuangliao city to identify the hydrochemical characteristics and the quality of groundwater using descriptive statistics and correlation matrices. And on that basis, combined with Analytic hierarchy process (AHP), an improved two-level fuzzy comprehensive evaluation method is used to evaluate the groundwater quality. The results indicate that the major cations and anions in groundwater are Ca2+ and HCO3-, respectively. The chemical types are mainly HCO3—Ca type water, some areas are complicated due to the influence of human activities. The evaluation results show that the water quality in the area is mostly III type water, and the groundwater quality in some areas is IV or V water due to the influence of primary geological conditions or human activities. The groundwater quality in the East Liaohe River Valley and Shuangliao urban area is relatively poor, and in the northwest part which is the saline alkali soil area is also relatively poor.

The source of metasilicate in mineral water of Jingyu County. located in Changbai Mountains of northeastern China, was analysed through two groups of water-rock interaction experiments. One is a hydrolysis immersion experiment using basalt and the other is an immersion experiment utilizing a mixture of soil, scoria, and clastic basalt under the same conditions. Results indicate that the metasilicate in mineral water is mainly derived from the hydrolysis of silicates and silica in the basalt, scoria, and soil. In the first immersion experiment, the release of metasilicate is linear, with dissolved metasilicate increasing continuously through time at a stable release rate of about 0.01 mg/(kg·day). The second experiment indicates that the contribution of soil and scoria to metasilicate in mineral water is higher than that of clastic basalt under the same conditions.

The conductivity of the streamflow is controlled by the content of the dissolved components, which mainly come from the water-rock interaction of the baseflow. This paper showed that the conductivity sequence controlled by water-rock interaction in the runoff process can be screened out by the two-parameter recursive filter method. The analysis of the streamflow and conductivity series of USGS gauge numbered 02298202 from October 2005 to October 2009 showed that the water-rock interaction controls the conductivity characteristics of the stage of streamflow recession. And with the increase of water-rock interaction time (T), the conductivity of the streamflow increases in a power function, which satisfies the equation C = 252.92T0.262.

This study investigated the hydrogeochemical characteristics of fluoride in the groundwater of Shuangliao City. This paper analyzes the effects of different forms of hydrochemistry and the chemical speciation of fluorine in water. The results showed that an area of high fluorine was located in the northern section of Shuangliao City, and the soil salinization degree was also high in this area. The chemical composition of groundwater was mainly formed by the evaporation-concentration process; both pH (weak alkaline environment) and total dissolved solids (TDS) had a positive effect on fluorine enrichment within a certain range; Na+ and F- had significant positive correlation, HCO3- and F- had a weak positive correlation, and Ca2+ was the only ion with a negative correlation with F-.

At present, the study of groundwater pollution risk assessment is generally based on the study of groundwater vulnerability. The impact of the pollutants themselves has not been paid more attention. The assessment of the risk of groundwater pollution should include two aspects: one is the contaminated nature of the aquifer itself and the other is spatial distribution of the pollutant. The vulnerability of the aquifer is only the natural susceptibility of the aquifer to the contaminant. Therefore, the risk assessment of groundwater pollution should also reflect the distribution and transport of pollutants in an aquifer. This study takes a tailings area as an example, and puts forward the risk assessment method of groundwater pollution based on physical processes. Before aquifer contamination occurs, the experts determine spatial distribution of each risk level according to the surrounding economic and social sensitivity conditions and hydrogeological conditions; and then use the numerical model to invert the intensity of the pollution source corresponding to each risk level. The results show that this method can express the distribution in space and time of risk level. For a single point source of contamination, this method is better than the previous based on aquifer vulnerability risk assessment method.

This study was aimed at understanding the factors affecting groundwater for the benefit of water resources management. Groundwater collected from 18 sites over an area of 770 Km2 was analysed. Temperature (Temp.), pH, Total Dissolved Solids (TDS) and Electrical Conductivity (EC) were measured in the field and 15 chemical parameters analysed in the laboratory. Factor Analysis (FA) of physiochemical results indicated mineralization, weathering of silicates and K-feldspar, and anthropogenic sources were mainly responsible for groundwater chemistry. Hierarchical Cluster Analysis (HCA) revealed sample clusters were mainly controlled by structure rather than by lithology, water source or altitude because 86% of cluster I samples occurred along a NNE-SSW trending fault zone. It was thus concluded that water-rock interaction, tectonics and anthropogenic factors are responsible for water physiochemistry.