Evolution origin analysis and health risk assessment of groundwater environment in a typical mining area: Insights from water-rock interaction and anthropogenic activities.

Coal mining changes groundwater environment, results in deterioration of water quality and endangering human health in the mining area. However, the comprehensive study of groundwater evolution and its potential impact in mining area is still insufficient. In this study, 95 groundwater samples were collected from 2019 to 2020 in a typical mining area of China. Ion ratio coefficients, isotopic tracing technology, Entropy-weighted water quality index (EWQI) and human health risk assessment model (HHRA) were applicated to investigate the hydrochemical variation reasons, groundwater quality and its potential health risk in the study area. Results showed that the groundwater hydrochemical types changed from HCO3∙SO4-Ca∙Mg type to SO4-Ca∙Mg and SO4∙Cl-Ca∙Mg type. Water-rock interaction, agricultural activities, manure and sewage input, precipitation and evaporation controlled the groundwater hydrochemical composition. Groundwater quality showed a trend of fluctuation with an average EWQI of 59.23, 68.92, 63.75, 58.02 and 64.92, respectively. 91.6% of the water samples was fair and acceptable for drinking. The groundwater health risk of nitrate in the study area ranged from 0.03 to 17.80. Infants had the highest health risk and nitrate concentration was the most sensitive parameter. The results will present a comprehensive research of groundwater evolution and potential impacts through a typical mining area example. Thereby offering valuable insights into the influencing factors identification, hydrochemical processes evolution, protection and utilization of groundwater in global mining areas.

Dual stable isotopes to rethink the watershed-scale spatiotemporal interaction between surface water and groundwater.

The interaction between groundwater and surface water, including their recharge relationship and ratio, is crucial for water cycling, management, and pollution control. However, accurately estimating their spatiotemporal interaction at the watershed scale remains challenging. In this study, we used dual stable isotopes (δ18O, δ2H, d-excess, and lc-excess) and hydrochemistry methods to rethink spatiotemporal interaction at the Yiluo River watershed in central China. We collected 20 groundwater and 40 surface water samples over four periods in two seasons (dry and wet). Our results showed that in the downstream region, groundwater recharged surface water in the dry season while surface water recharged groundwater in the wet season, with average recharge ratios of 89.82% and 90.02%, respectively. In the midstream region, surface water recharged groundwater in both seasons with average ratios of 93.79% and 91.35%. In contrast, in the upstream region, groundwater recharged surface water in both seasons with ratios of 67.35% and 76.89%. Seasonal changes in the recharge relationship between surface water and groundwater in the downstream region also been found. Our findings provide valuable insights for watershed-scale water resource and pollution management.

Comparison of multi-DLM approaches for predicting daily runoff: evidence from the data-driven model in one of China's largest wheat production-bases.

Runoff forecasting is extremely important for various activities of water pollution research and agricultural. Data-driven models have been proved an effective approach in predicting daily runoff when combining deep learning methods (DLM). However, predicting accuracy of daily runoff still need improved. Here, we firstly proposed a combined model of Gate Recurrent Unit (GRU) and Residual Network (ResNet) and compared with one shallow learning method (Back Propagation Neural Network, BPNN) and one deep learning method (GRU) with data from 2010 to 2020 in three stations in daily runoff forecasting in the Yiluo River watershed. The results showed that the combined model with precipitation data and runoff data as input has the highest prediction accuracy (NSE = 0.9325, 0.8735, 0.9186, respectively). Input data with precipitation have higher prediction accuracy than that without. The performance of the model was better in the dry season than the wet season. The topographic and geomorphic factors may also the main factors affecting runoff forecast. Those results of this study can provide useful strategies to predict short runoff and manage watershed scale water resources especially in the important agriculture region.

Multi-methods to investigate spatiotemporal variations of nitrogen-nitrate and its risks to human health in China's largest fresh water lake (Poyang Lake).

Nitrogen-nitrate contamination has been recognized as the main threaten to the large lake surrounding with the intensive agriculture activities. However, there are still insufficient studies on the interannual evolution of nitrogen-nitrate, source and its impact on the environment and human health in the large fresh water lake. In this study, 248 samplings were collected in Poyang Lake from 2013 to 2018, multi-methods (mathematical statistics method, grey correlation analysis, person correlation analysis and human health risk assessment) to investigate the spatiotemporal variations, impact factors and potential health risks of NO2--N, NO3--N and NH4+-N. The results showed that the middle region had the highest NO2- concentration (mean 0.04µg/l), the northern region had the highest NO3- concentration (mean 1.12 mg/l), and the southern region had the highest NH4+ concentration (mean 0.48 mg/l). For NO3- and NH4+, the concentration was higher than in the wet season. While the concentration of NO2- had the reverse trend. Grey correlation analysis and person correlation analysis results indicate that nitrogen fertilizer, waste water, pH, CODMn and temperature were main factors affecting the nitrogen concentration in Poyang Lake. Health risk assessment results revealed that potential hazards in the study area were acceptable (HR < 1). NO3- provided the highest health risks, and oral ingestion is the major source of local nitrogen health risk. Those results can provide the reference for developing the treatment methods of the international large freshwater lake.