Zhuo Zhang

Coastal groundwater systems are highly susceptible to seawater intrusion and salinization. However, complex depositional settings and multiple geochemical processes have made it difficult to understand the mechanism of groundwater salinization. To characterize coastal groundwater salinization and elucidate its controlling mechanisms in Tianjin, China, a total of 228 groundwater samples were collected. The degree of groundwater salinization and associated hydrochemical evolution was systematically investigated using the groundwater quality index for seawater intrusion (GQI _SWI ) and some hydrochemical indicators and evolutionary diagrams. Hydrochemical analyses revealed an overall evolution from HCO₃‐Ca type to Cl‐Na type groundwater, with distinct salinization geochemical evolution pathways among different aquifers. The GQI _SWI assessment indicated that both shallow and deep groundwater in Tianjin are dominated by fresh and brackish waters, with only minor differences in the overall degree of salinization along the vertical profile. Salinization of shallow groundwater is mainly concentrated in coastal areas and generally decreases progressively from the coastline toward inland areas. In contrast, the spatial distribution of salinity in deep groundwater is characterized primarily by localized high‐salinity anomalies, without the development of a continuous salinization zone. Groundwater salinization in Tianjin therefore cannot be attributed solely to modern seawater intrusion; rather, it is jointly controlled by modern coastal salt inputs, freshwater recharge, long‐term water–rock interactions, and ion exchange. These findings provide new insights into the identification of seawater intrusion and the interpretation of salinization mechanisms in complex coastal groundwater systems and offer a scientific basis for groundwater resource protection and management.

This editorial introduces and synthesizes the contributions included in this Special Issue on innovative methods and technologies in groundwater resource development

High-arsenic (As) groundwater is widely reported in coastal river deltas worldwide. However, the levels of arsenic risk and its controlling factors across different deltaic regions remain poorly understood. This study integrates 3,373 shallow groundwater samples and 31 environmental variables across the Pearl River Delta, Yangtze River Delta, and Bohai coastal alluvial plains of China. We developed a stacking ensemble-learning model to predict shallow groundwater As exceedance probability and applied SHAP and centered PDP analyses to identify key environmental controls and nonlinear responses. The stacking model showed good predictive performance across the three regions and the combined dataset, with AUC values ranging from 0.80 to 0.89. It effectively identified major high-risk zones, including the coastal low-lying areas of the Pearl River Delta, the southern plain of the Yangtze River Delta, and the northern low-elevation alluvial areas and estuarine tidal flats of the Bohai Rim. SHAP analysis indicated that hydrochemical conditions were the dominant common control category for shallow groundwater As enrichment, contributing 36.2% of the total importance, with Eh, EC, and pH being the key variables. Human activities, hydrogeology, soil and climate factors contributed 23.5%, 22.2%, 10.7%, and 7.4%, respectively. Regional differences were evident among the three coastal alluvial plains. High-As risk was mainly controlled by EC, pH, and hydraulic gradient in the Pearl River Delta. In contrast, redox conditions dominated in the Yangtze River Delta and Bohai Rim, with stronger modulation by climate in the former and hydrogeology in the latter. This study provides a scientific basis for As-risk identification, monitoring design, and zoned prevention in coastal deltaic groundwater systems.

High-fluoride (F⁻) groundwater is a widespread environmental problem that poses significant risks to human health in many regions worldwide. Understanding the origin, circulation, and evolution of fluoride-rich groundwater is therefore essential for effective groundwater management and mitigation strategies. In recent years, stable isotope techniques have helped to address key gaps in understanding the hydrogeochemical processes governing F⁻ enrichment, particularly regarding the source identification and water-rock interaction mechanisms that remain poorly constrained. This study reviews the applications of hydrogen–oxygen, strontium–calcium, and lithium–boron isotopes in research on high-F⁻ groundwater systems. Hydrogen and oxygen isotopes (δ²H and δ¹⁸O) are widely used to identify groundwater recharge sources, mixing processes, and evaporative effects, thereby providing key constraints on the origin of fluoride-rich groundwater. Strontium and calcium isotopes (⁸⁷Sr/⁸⁶Sr and δ^44/40Ca) serve as effective tracers of water-rock interactions and associated hydrogeochemical processes, including mineral weathering and dissolution, cation exchange, and secondary mineral precipitation, which play critical roles in fluoride mobilization and enrichment. In addition, lithium, and boron isotopes (δ⁷Li and δ¹¹B) provide valuable insights into the influence of geothermal fluids and deep hydrothermal processes on fluoride accumulation in groundwater systems. Overall, the integrated application of these stable isotope systems offers a robust framework for elucidating the formation mechanisms and evolutionary pathways of high-F⁻ groundwater. Moving beyond qualitative source identification, future research should prioritize the development of Bayesian isotope mixing models that explicitly quantify uncertainty in fluoride source apportionment and utilize sensitivity analysis to test competing hydrogeochemical mechanisms.

As an important drinking water source for Beijing, the capital of China, the water inflow of Miyun Reservoir has been decreasing year by year, which has affected the urban water supply security. To understand the variation trend of the inflow and analyze the main factors influencing the runoff change, this research focused on the watershed of Miyun Reservoir as the target. Based on the runoff data from 1984 to 2020 at the outlet of the basin, as well as the precipitation, potential evaporation intensity, NDVI (normalized difference vegetation index), population, and GDP (Gross Domestic Product) data, combined with correlation analysis methods, empirical statistical methods, the SCRCQ (Slope Change Ratio of Cumulative Quantity) method, and the GIS, the interannual variation characteristics of various elements in the basin were analyzed, the correlation between runoff and other factors was studied, and the influencing degrees of precipitation, water surface evaporation intensity, human activities, and other factors on the runoff change in the basin were quantitatively separated. The research results showed that the runoff exhibited a distinct decreasing trend, and there were two mutation points in the basin runoff from 1984 to 2020, which were 1995 and 2014, respectively. The runoff change was divided into three stages: 1984–1995 (upward trend in T1), 1995–2014 (downward trend in T2), and 2014–2020 (stable trend in T3). Runoff was significantly correlated with four indicators: the summer leaf area index of the Chaohe River and Baihe River, the regional GDP and population, among which the correlation of the summer leaf area index was the largest. Compared with the period T1, the contribution rates of climate change to the runoff reduction in T2 and T3 were 6.38% and 5.73%, and the contribution rates of human activities to the runoff reduction were 93.62% and 94.27%, respectively. Therefore, the change in annual runoff in the Miyun Reservoir watershed is mainly affected by human activities, and the contribution of climate change to the runoff attenuation is weak. This study is significant in the maintenance and enhancement of runoff in typical watershed.