Spatiotemporal dynamics in soil iron affected by wetland conversion on the Sanjiang Plain

Agricultural fertilization near marshes impacts the potential for greenhouse gas emissions from wetland ecosystems by modifying microbial communities

Ensuring agricultural security and preserving the health of wetland ecosystems are crucial concerns facing northeast China. However, the adverse effects of environmental pollution, especially nitrogen (N), caused by prolonged agricultural development on the health of marsh wetlands cannot be systematically recognized. To address this issue, an 18-year trial with four different levels of N application was carried out in a typical area of the Northeast region: 0, 6, 12, and 24 gN·m-2·a-1 (referred to as CK, N6, N12, and N24, respectively) to investigate changes in wetland ecological functioning. The results showed that long-term N input significantly enhanced soil N availability. High-level of N addition (N24) significantly reduced soil bacterial richness in October, while fungal diversity was significantly higher in June than in October for both control and N6 treatments. The main environmental factors affecting microorganisms in June were TN, NH4+, and EC, while bacterial and fungal communities were influenced by TN and Leaf Area Index (LAI), respectively, in October. It was found that the AN16S gene was significantly higher in June than in October, indicating that summer is the critical time for N removal in the wetland. N addition significantly reduced the abundance of the NIFH gene and decreased the N fixation potential of the wetland. In June, low and medium levels of N inputs promoted denitrification processes in the wetland and elevated the wetland N2O emission potential. The abundance of NARG, NIRK, and NOSZ genes decreased significantly in October compared to June, indicating a decrease in the wetland N2O emission potential. Additionally, it was observed that soil methanotrophs were positively affected by NH4+ and TN in October, thereby reducing the wetland CH4 emission potential. Our research provides a systematic understanding of the impact of agricultural N pollution on marsh wetlands, which can inform strategies to protect wetland health.

Analysis of Groundwater Overexploitation Based on Groundwater Regime Information

Although groundwater overexploitation is a global problem, there are no unified standards for its identification and determination. To date, groundwater overexploitation has mainly been evaluated using the groundwater quantity balance and effect of groundwater exploitation on the environment. However, it is difficult to determine groundwater exploitation for an agricultural irrigation area owing to the lack of detailed environmental monitoring data. We used the experience of previous studies to introduce a novel identification model for groundwater overexploitation by relying on groundwater regime information and multi-factor analysis. The model was applied to the Songhua River-Naoli River area, Sanjiang Plain (China). In the demonstrated model, the study area was divided in the context of the risk of overexploitation into natural and non-natural regime areas according to groundwater regime characteristics. The areas were identified by analyzing groundwater flow fields, cones of groundwater depression, and storage variation. The analysis demonstrated that the study area could be divided into high-risk, medium-risk, low-risk, and non-overexploitation areas with corresponding area ratios of 10.12%, 1.38%, 54.8%, and 33.7%. Moreover, the total amount of overexploited groundwater was estimated to be 30.41 × 108  m3 (average annual decrease = 1.69 × 108  m3 ). Overall, the proposed identification model was shown to be applicable to agricultural irrigation areas, thereby offering promising implications.

Hydrochemical Evolution and Quality Assessment of Groundwater in the Sanjiang Plain, China

Groundwater is subjected to contamination threats from human activities, such as agriculture, especially long-term farming in the Sanjiang Plain, China. Identifying the sources and distribution of pollution is essential for its reasonable prevention and control. In this study, we analysed the chemical characteristics of 389 samples at 60 shallow groundwater monitoring points from 2011 to 2015 in the Sanjiang Plain using traditional hydrochemical methods, water quality assessment, Pearson’s correlation, and principal component analysis (PCA). Although groundwater type in this area was predominantly HCO3-Ca·Mg, three forms of nitrogen pollution (ammonia, nitrate, and nitrite) were all detected in this area. The interaction of natural geochemical and anthropogenic factors during hydrochemical formation is confirmed by the high coefficients of variation and Gibbs plots of the main ions in the water. The overall shallow groundwater situation was described as good, with more than 40% and 90% of groundwater samples suitable for drinking and irrigation according to the quality assessment, respectively. The proportion of poor water quality in the wet season was higher than that in the dry season. NO3-N and NH3-N were identified as the major anthropogenic pollutants in the study area. Results from Pearson’s correlation and principal component analysis shows two main pollutants fall into two chemical controlling factors together with natural chemical parameters, which implies that the migration and transformation of pollutants may have affected the overall hydrochemical characteristics of the regional groundwater. Therefore, findings from this paper can provide insight into the chemical evolution of groundwater in response to long-term agricultural activities and can help contribute to better management of groundwater resources and agricultural sustainable development.