Groundwater is an essential source of drinking and irrigation water. However, elevated Fe and Mn concentrations in groundwater have been found in recent decades, which can adversely affect human health and decrease crop quality and yields. The roles of hydrogeochemical changes and groundwater pollution (exogenous reductive material inputs) in this have not been studied adequately. We determined the distribution of Fe and Mn concentrations in groundwater in the Songnen Plain, northeast China, which is known for elevated Fe and Mn concentrations, and investigated the factors and mechanisms involved in causing the elevated concentrations. Chemical and statistical analyses indicated that the Fe and Mn concentrations in groundwater significantly correlated with climate parameters (precipitation and temperature), surface features (altitude, distance from a river, soil type, soil texture, and land use type) and hydrogeochemical characteristics (chemical oxygen demand and NH₄⁺, NO₃⁻, and P concentrations). In particular, the Fe and Mn concentrations in groundwater are higher in areas containing paddy fields and water bodies than other land use type areas. Areas with groundwater containing ultra-high Fe and Mn concentrations have almost all of the favorable factors. The main reasons for the elevated Fe and Mn concentrations in groundwater in the study area are the Fe/Mn mineral-rich strata and soil with abundant organic matter acting as sources of Fe and Mn to the groundwater and the reductive environment in the lower terrain and areas containing water bodies favoring Fe and Mn dissolution in the groundwater. Inputs of pollutants from agricultural activities have caused the Fe and Mn concentrations in groundwater to increase. Future studies should be performed to study interactions between pollutants from agricultural activities and Fe and Mn in groundwater and develop environmental management strategies for preventing future increases in Fe and Mn concentrations and promoting sustainable development of agriculture.

The DPSIR model is a conceptual model established by the European Environment Agency to solve environmental problems. It provides an overall framework for analysis of environmental problems from five aspects: driving force (D), pressure (P), state (S), impact (I), and response (R). Through use of the DPSIR model framework, this paper presents the SEEC model approach for evaluating watershed ecological security. The SEEC model considers four aspects: socioeconomic impact (S), ecological health (E), ecosystem services function (E), and control management (C). Through screening, 38 evaluation indicators of the SEEC model were determined. The evaluation results showed that the ecological security index of the study area was >80, indicating a generally safe level. The lowest score was mainly attributable to the low rate of treatment of rural domestic sewage. The water quality status was used to evaluate the applicability of the SEEC model, and the calculation results indicated that the higher the score of the ecological security evaluation results, the better the water quality status. The findings show that the SEEC model demonstrates satisfactory applicability to evaluation of watershed ecological security.

There is a severe issue with groundwater overuse and water scarcity in the North China Plain. The capacity of groundwater resources to promote economic development is also diminished due to the overexploitation of resources to suit the industrial needs of diverse sectors. Therefore, it is crucial to research the regional groundwater resource carrying capacity from both a temporal and spatial perspective. The relationship between water usage efficiency and groundwater availability, which was built using regional data on water supply and consumption as well as gross domestic product, is used in this study to assess the carrying capacity of Hebei’s groundwater resources through time and space. The results show that from the perspective of time, in the years when the groundwater resource exploitation degree is greater than one from 2010 to 2017, the contribution rate of the groundwater resource exploitation to economic development reaches 62.5%, indicating that the economic development of the study area is highly dependent on the groundwater resources. The exploitation degree of groundwater resources is less than one, but the degree of economic development value keeps increasing to nearly 80% and the overexploitation rate is 75% in the total time scale. In terms of spatial scale, only Hengshui City has no overexploitation index, and the overexploitation rate is 9.1%. The overload and severe overload areas account for 45.45%, respectively. Among them, the exploitation degree of groundwater has been in a state of over-saturation, and as economic development depends on groundwater resources, water efficiency needs to be improved through water saving. Optimizing and promoting industrial structures and water-saving technology to further improve water efficiency are key factors to improve the carrying capacity of groundwater resources.

Identifying the source and impact pathways of soil heavy-metal pollution is critical for its assessment and remediation. Numerical simulation has been widely used to simulate soil heavy-metal pollution processes and predict risks. However, traditional numerical simulation software requires a large number of parameters, which are difficult to obtain in site-scale studies. This study proposes a rapid method for identifying soil heavy-metal pollution processes using the TOUGH2/EOS7 software. It has automatic calibration and uncertainty analysis capabilities, which can effectively reduce the demand for parameters. This study established a method, including model selection, simulation, validation, and error analysis, to verify the effectiveness of the proposed method. This study identified the most realistic scenario for chromium pollution and simulated its release over 20 years, and the results met accuracy requirements with a best-case fit of 0.9998. The results showed that the method can quickly identify the source and impact pathways of soil heavy-metal pollution, providing strong evidence for environmental damage assessment.