Abstract
The North China Plain (NCP) has been facing declining groundwater levels and increasing nitrate contamination over the past few decades. Understanding the transport and accumulation of nitrogen in the subsurface is crucial to sustainable groundwater management. This work aims to evaluate the impact of historical nitrogen loading and fluctuating water tables on groundwater quality, estimate the distribution of the nitrate concentration in the aquifer, and assess the potential pollution risk associated with rising groundwater levels. The simulation involves determining the nitrate input to the aquifer and calculating the groundwater nitrate concentration using a mixing model. It is found that historical nitrogen loading has not significantly impacted shallow aquifer water quality yet, and deep groundwater nitrate concentrations remain stable. However, if groundwater levels are restored due to management strategies in the next 15 years, noticeable deterioration of shallow water quality would occur. The areas that are most vulnerable to nitrate contamination are expected to be the piedmont plain and southern and eastern parts of the central plain, with the pollution extending toward the central and northern regions. Moreover, it is estimated that the exceedance rate of nitrate concentration in the NCP could potentially double due to rising water levels by 2035.
| Original language | English |
|---|---|
| Pages (from-to) | 2369-2381 |
| Number of pages | 13 |
| Journal | ACS ES and T Water |
| Volume | 4 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 14 2024 |
| Externally published | Yes |
Funding
This research was supported by the National Key R&D Program of China (2021YFC3200502), the National Natural Science Foundation of China (42377045), Guangdong Provincial Basic and Applied Basic Research Fund (2021A1515110781), Shenzhen Science and Technology Innovation Committee (JCYJ20210324105009024), Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control (2023B1212060002), and the Center for Computational Science and Engineering of Southern University of Science and Technology.
Keywords
- groundwater level recovery
- groundwater quality
- nitrate contamination
- spatiotemporal distribution
- travel time