[Chemical Characteristics and Genetic Analysis of Karst Groundwater in the Beijing Xishan Area].

As an important water supply source in Beijing， karst groundwater has played an irreplaceable role in the security of urban water supply and ecological environment protection in the past 70 years. The Xishan karst groundwater system， located in the upper reaches of western Beijing， belongs to ecological conservation areas. There are several centralized water supply fields in this area. In this study， the Xishan karst groundwater system was taken as the research object. A total of 120 karst groundwater samples in this area were investigated by using statistical analysis， ion ratio， and principal component analysis （PCA） methods to explore the spatial distribution characteristics and formation mechanism of groundwater hydrochemistry. The research results showed that： ① the groundwater quality of the Xishan system was generally good， with the characteristics of neutral pH and low salinity. A total of 84.17% of the water samples were classified as hard water. The chemical type of groundwater was mainly HCO3-Ca·Mg. ② The chemical composition of groundwater was mainly affected by the water-rock interaction， and the weathering source of rock was mainly the dissolution of carbonate. ③ The results of principal component analysis showed that 34.41% of the chemistry formation of groundwater could be explained by carbonate dissolution， 27.33% by rock salt and evaporate dissolution， 11.76% by aquifer sediment dissolution， and 10.30% by domestic sewage discharge. From the recharge area to the runoff area and then to the discharge area， the TH and TDS gradually increased. Coal mining drainage and human activities were the main factors that caused groundwater degradation and variable hydrochemical types in the piedmont. In the future， it is necessary to further strengthen environmental governance， control point and non-point source pollution， and continuously monitor key areas to provide scientific support for ecological and environmental protection.

Spatiotemporal modeling of land subsidence using a geographically weighted deep learning method based on PS-InSAR.

The demand for water resources during urbanization forces the continuous exploitation of groundwater, resulting in dramatic piezometric drawdown and inducing regional land subsidence (LS). This has greatly threatened sustainable development in the long run. LS modeling helps understanding the factors responsible for the ongoing loss of land elevation and hence enhances the development of prevention strategies. Data-driven LS models perform well with fewer variables and faster convergence than physically-based hydrogeological models. However, the former models often cannot simultaneously reflect the temporal nonlinearity and spatial correlation (SC) characteristics of LS under complex variables. We proposed a LS spatiotemporal model which considers both nonlinear and spatial correlations between LS and groundwater level change of exploited aquifers. It is based on deep learning method and LS time series detected by permanent scatterer-interferometric synthetic aperture radar (PS-InSAR). The LS time series and hydrogeological properties are constructed as a spatiotemporal dataset for model training. The spatiotemporal LS model, geographically weighted long short-term memory (GW-LSTM), is constructed by integrating SC with LSTM. This latter is a deep recurrent neural network approach incorporating sequential data. The model is validated by a case study in the Beijing plain. The results show that the accuracy of the proposed model can be greatly improved considering the spatial correlation between LS and influencing factors. Furthermore, the comparison between the LSTM and GW-LSTM models reveals that groundwater level variation is not a unique causation of LS in the study area. The developed model deals with the spatiotemporal characteristics of LS under multiple variables and can be used to predict LS under different scenarios of groundwater level variations for the purpose of monitoring and providing evidence to support the prevention of future LS.

[Assessment of groundwater quality of different aquifers in Tongzhou area in Beijing Plain and its chemical characteristics analysis].

In order to evaluate the groundwater quality of Tongzhou area in Beijing Plain and to discuss the characteristics of its distribution by the view of hydrochemistry, a total of 151 groundwater samples, collected within study area in the dry period of 2008 according to the geological and hydrogeololgical condition of Tongzhou area, were classified as shallow, middle and deep groundwater, respectively. Based on the data, the groundwater quality was evaluated by the method of F value. The mean and variance of main chemical constituents of groundwater samples were presented. Almost all the quaternary groundwater of Chaobai river pluvial fan belonged to the alkaline water type. The evaluation results based on the analysis results showed that from shallow to deep, the quality of groundwater in Beijing became better. The total areas of groundwater belonging to class IV and V area were 884 km2, 599 km2 and 94 km2 respectively for shallow, middle and deep groundwater. The evaluation results showed that the main exceeding chemical constituents were TDS, hardness, NH4(+), F(-) and total Fe. Most exceeding samples belonged to middle and deep aquifers. The main types of shallow groundwater were HCO2-Ca x Mg- and HCO3 x Cl-Ca x Na x Mg, while the chemical types of mid-deep groundwater were mostly HCO3-Na x Ca- and HCO3 x SO4(2-) -Na x Ca type due to the increased Na(+), SO4(2-) and Cl(-) concentration. Study results showed that the quality of shallow groundwater became worse mainly due to human activities. The deterioration of groundwater quality in mid-deep aquifers was due to both human activities and natural occurrence of poor-quality water.

[Risk assessment of quaternary groundwater contamination in Beijing Plain].

Firstly, advances in investigation and evaluation of groundwater pollution in China in the last decade were presented, and several issues in the field which hinder the development of groundwater environment were pointed out. Then, four key concepts in risk assessment of groundwater pollution were briefly described with more emphasis on the difference between groundwater pollution assessment and groundwater quality assessment in this paper. After that, a method on risk assessment of groundwater pollution which included four indicators, the pollution assessment, the quality assessment, the vulnerability and the pollution load of groundwater, was presented based on the regional characteristics of Beijing Plain. Also, AHP and expert scoring method were applied to determine the weight of the four evaluation factors. Finally, the application of this method in Beijing Plain showed the area with high, relative high, medium, relative low and low risk of groundwater contamination was 1 232.1 km2, 699.3 km2, 1 951.4 km, 2 644 km2, and 133.2 km2, respectively. The study results showed that the higher risk in the western region was likely caused by the higher pollution load and its higher vulnerability, while the relatively high risk in the southeast of Beijing plain area, the Tongzhou District, is mainly caused by historical pollution sources.