Abstract:

Monitoring agricultural non-point source pollution is crucial for ensuring environmental water safety and promoting sustainable agricultural development. This study systematically analyzed the spatiotemporal variation characteristics and potential influencing factors of water quality at the inlet and outlet of a typical monitoring area in the Zengcheng District ofGuangzhou City during the 2023 rainfall period. The results showed that the water quality indicators in the monitoring area were primarily classified as class III to V, with class V being the most prevalent (37.9%) and followed by class IV (31.0%). The water quality indicators exhibited significant fluctuations on a monthly basis. The concentrations of total phosphorus, phosphate, and soluble phosphate decreased over the months, which may be related to agricultural activities, rainfall, temperature, and rural sewage discharge. The concentrations of total nitrogen, ammonia nitrogen, and nitrate nitrogen generally showed a fluctuating downward trend, followed by a gradual increase, possibly due to the dilution effect of rainfall and the high mobility of nitrogen. The monthly average instantaneous flux difference of total phosphorus and phosphate was highly positively correlated with rainfall (r=0.89-0.93, p=0.021-0.043), highlighting the significant impact of runoff on phosphorus pollution. In the early and middle stages of runoff generation, total phosphorus, phosphate, and soluble phosphate were significantly correlated with flow (r=0.46-0.57, p=0.001-0.008), whereas more indicators were correlated with flow in the later stages (r=0.43-0.68, p=0.001-0.012). These results indicate that the scouring effect of runoff was weak, having a minor impact on water quality, whereas a large amount of pollutants entered the water with rainfall runoff in the mid-stage, leading to stronger correlations in the later stages. This study provides scientific evidence for the control of agricultural non-point source pollution and the management of regional water pollution in China.

Key words: agricultural non-point source pollution, rainfall, pollutant flux, runoff production, water quality

摘要：

农业面源污染监测对于保障水环境安全和推动农业可持续发展至关重要。以广州市增城区典型监测区为对象，系统分析了2023年降雨期间出入口水质的时空变化特征及潜在影响因素。结果表明，监测区水质主要为III类至V类，其中V类水质占比最大（37.9%），其次为IV类（31.0%）。监测区内水质指标呈现明显的逐月波动趋势。总磷、磷酸盐和可溶性磷酸盐浓度随月份逐渐降低，这可能与农业活动、降雨、气温和农村污水排放相关。总氮、氨氮和硝酸盐氮大致呈现波动下降而后逐渐上升趋势，这可能与降雨稀释以及较强的氮素迁移能力相关。相关性分析显示，总磷和磷酸盐的出入口月度降雨期间污染物平均瞬时通量差值与降雨量呈高度正相关（r=0.89-0.93，p=0.021-0.043），说明降雨径流对监测区水体磷素污染有显著影响。在降雨产流初期和中期，总磷、磷酸盐、可溶性磷酸盐与流量呈显著正相关（r=0.46-0.57，p=0.001-0.008），而在降雨产流后期，更多指标与流量产生相关性（r=0.43-0.68，p=0.001-0.012）。以上结果表明，初期降雨径流冲刷作用微弱，对水质影响较小，而中期大量污染物随降雨径流汇入，导致后期相关性增强。该研究为农业面源污染防控与区域水污染攻坚提供了科学依据。

关键词: 农业面源污染, 降雨, 污染物通量, 产流, 水质