Xuequn Chen

Coastal aquifers are critical freshwater resources that face increasing threats from contamination and saltwater intrusion. Traditional approaches for characterizing these aquifers are challenged by complex dynamics, high-dimensional parameter spaces, and significant computational demands. This study presents an innovative method that combines an Auto-Regressive Convolutional Neural Network (AR-CNN) surrogate model with the Iterative Local Updating Ensemble Smoother (ILUES) for the joint inversion of contamination source parameters and hydraulic conductivity fields. The AR-CNN surrogate model, trained on synthetic data generated by the SEAWAT model, effectively approximates the complex input–output relationships of coastal aquifer systems, substantially reducing computational burden. The ILUES framework utilizes observational data to iteratively update model parameters. A case study involving a heterogeneous coastal aquifer with multipoint pollution sources demonstrates the efficacy of the proposed method. The results indicate that AR-CNN-ILUES successfully estimates pollution source strengths and characterizes the hydraulic conductivity field, although some limitations are observed in areas with sparse monitoring points and complex geological structures. Compared to the traditional SEAWAT-ILUES framework, the AR-CNN-ILUES approach reduces the total inversion time from approximately 70.4 h to 16.2 h, improving computational efficiency by about 77%. These findings highlight the potential of the AR-CNN-ILUES framework as a promising tool for efficient and accurate characterization of coastal aquifers. By enhancing computational efficiency without significantly compromising accuracy, this method offers a viable solution for the sustainable management and protection of coastal groundwater resources.

To keep groundwater levels stable, Jinan’s government has implemented several water management measures. However, considerable volumes of dissolved organic carbon (DOC) can enter groundwater via water exchange, impacting groundwater stability. In this study, a SWAT-MODFLOW-RT3D model designed specifically for the Yufu River Basin is developed, and part of the code of the RT3D module is modified to simulate changes in DOC concentrations in groundwater under different artificial recharge scenarios. The ultimate objective is to offer valuable insights into the effective management of water resources in the designated study region. The modified SWAT-MODFLOW-RT3D model simulates the variations of DOC concentration in groundwater under three artificial recharge scenarios, which are (a) recharged by Yellow River water; (b) recharged by Yangtze River water; and (c) recharged by Yangtze River and Yellow River water. The study shows that the main source of groundwater DOC in the basin is exogenous water. The distribution of DOC concentration in groundwater in the basin shows obvious spatial variations due to the influence of infiltration of surface water. The area near the upstream riverbank is the earliest to be affected. With the prolongation of the artificial recharge period, the DOC concentration in groundwater gradually rises from upstream to downstream, and from both sides of the riverbank to the surrounding area. By 2030, the maximum level of DOC in the basin will exceed 6.20 mg/l. The Yellow River water recharge scenario provides more groundwater recharge and less DOC input than the other two scenarios. The findings of this study indicate that particularly when recharge water supplies are enhanced with organic carbon, DOC concentrations in groundwater may alter dramatically during artificial recharge. This coupled modeling analysis is critical for assessing the impact of recharge water on groundwater quality to guide subsequent recharge programs.

Jinan, renowned as the “Spring City” in China, relies significantly on karst groundwater as an indispensable resource for socio-economic development, playing a crucial role in ecological regulation, tourism, and historical and cultural aspects. The Yufu River basin, situated within Jinan’s karst region, represents a vital riverine leakage zone. Therefore, investigating the evolutionary characteristics and causative mechanisms of surface water and groundwater at different aquifer levels in the Yufu River basin can provide a scientific foundation for the protection of Jinan’s springs. This study, based on hydrogeochemical and isotopic data from the river water, shallow groundwater, deep groundwater, and springs in the Yufu River basin, explored the hydrogeochemical evolution in this region. The findings revealed significant spatial variations in the hydrochemical parameters of the Yufu River basin. Groundwater received contributions from surface water, while springs represented a mixture from both surface water and various recharge aquifers. Dominant ions include Ca²⁺ and HCO₃⁻, with prevailing hydrochemical types being HCO₃·SO₄-Ca and HCO₃-Ca. Atmospheric precipitation served as the primary source of recharge for surface water and groundwater in the Yufu River basin, albeit influenced by pronounced evaporation processes. The hydrochemical composition in the Yufu River basin was primarily attributed to water–rock interactions, mainly driven by the combined effects of carbonate rock, silicate rock, and gypsum weathering and dissolution. Among these, the weathering and dissolution of carbonate rocks played a dominant role, with human activities exerting a relatively minor influence on the hydrochemistry of the Yufu River basin.

Subsurface dams are widely used to prevent saltwater intrusion, with good results. This blockage often leads to an accumulation of pollutants and salt on the inland and seaside of the dam, respectively. While the latter is intended, the former effect is not desired and poses a huge problem in groundwater management. In order to quantitatively address this issue and clarify the impact of subsurface dam height, location, and the head difference for the saltwater and freshwater boundary on saltwater wedges and fresh groundwater discharge, a flow tank and numerical model were constructed. The results indicate that there was an optimal effective dam height and location (also the minimum effective dam location) for controlling saltwater intrusion, which corresponded to the maximum groundwater and freshwater discharge. When the various conditions of the numerical model were set according to the flow tank and the dam was 15 cm away from the saltwater boundary, the minimum effective dam height was equal to the aquifer thickness multiplied by 0.36. The dam height reached a height that was slightly higher than the minimum effective height, namely, the ratio of dam height to aquifer thickness was 0.38, which revealed that the freshwater discharge reached its maximum at 22.71 cm³/min, the saline water wedge area was the smallest at 378 cm², and the prevention effect of saltwater intrusion was the best. Building a dam too high, that was, the ratio of dam height to aquifer thickness exceeded 0.38, resulted in an increased saltwater wedge area and exacerbated aquifer pollution. When the dam was located at the minimum effective distance for preventing saltwater intrusion under a certain dam height and head difference between saltwater and freshwater boundary, that was, the ratio of the distance of the dam to the saltwater boundary to the total length of the aquifer was 0.063, the distance of the dam to the saltwater boundary was the minimum effective distance. Compared to other effective distances, when the dam was at the minimum effective distance, the freshwater discharge reached its maximum at 22.71 cm³/min, and the saltwater wedge area was the smallest at 378 cm². These conclusions provide a theoretical reference for the impact of subsurface dam construction on the saltwater wedge. This study examines the impact of tides and waves on the water head of the saltwater boundary, and it is also necessary to verify these conclusions through actual field experiments. We will investigate this in future work.