长江三角洲河网平原地区集约化种植面源污染监测指标筛选研究

    Researches on Monitoring Indicators Screening of Intensive Plant Source Pollution in the Plain Area of the Yangtze River Delta

    • 摘要: 以长江三角洲河网平原地区典型区域不同种植模式(水稻、小麦和设施蔬菜)面源污染发生过程为研究对象,通过连续3 a田间试验,确定不同种植模式面源污染发生量。结果显示,水稻种植中氨挥发损失、地表径流损失和淋溶损失分别占施氮量的15.4%、5.3%和1.8%,总损失量约占22.5%。小麦种植中氨挥发损失、地表径流损失和淋溶损失分别占施氮量的3.3%、5.1%和3.0%,总损失量约占11.4%。设施蔬菜种植中氨挥发损失、地表径流损失和淋溶损失分别占施氮量的0.1%、3.0%和18.9%,总损失量约占22.0%。基于田间试验结果,针对长江三角洲河网平原地区水稻、小麦和设施蔬菜种植模式,分别提出4个(田面水铵态氮浓度、日最高气温、土壤120 cm深度处总氮浓度和降水量)、5个(0~30 cm土壤中铵态氮浓度、日最高气温、土壤pH、氮肥投入量和降水量)和2个(氮肥投入量和降水量)简易监测指标,结合田间试验数据的验证,确认新建立的简易监测指标及构建的数学关系能够提高面源污染发生量预测精度,从而可为我国环境管理部门提供一种便捷有效的监测和管理方法。

       

      Abstract: The amount of non-point source pollution from intensive cropping with different patterns (rice, wheat and greenhouse vegetable) were measured by three successive years' field experiments in typical area of Yangtze River Delta. The field experiments results illustrated the losses of ammonia volatilization, surface runoff and leaching were accounted for 15.4%, 5.3% and 1.8% of the applied nitrogen in the rice season and the total loss percentage was about 22.5%. In the wheat season, the losses of ammonia volatilization, surface runoff and leaching were responsible for 3.3%, 5.1% and 3.0% of the applied nitrogen, respectively and the total loss percentage was about 11.4%. By the greenhouse vegetable farming, the losses of ammonia volatilization, surface runoff and leaching were accounted for 0.1%, 3.0% and 18.9% of the applied nitrogen and the total loss percentage was about 22.0%. Based on the field experiments' results, several monitoring indicators were screened to forecast the non-point source pollutions. Specifically, 4 monitoring indicators (ammonium concentration in the flooded water, the daily highest temperature, the TN concentration at the soil depth of 120 cm and rainfall) for rice planting system, 5 monitoring parameters (soil ammonium concentration in the 0-30 cm layer, the daily highest temperature, soil pH, the nitrogen application rate and rainfall) for wheat planting system, and 2 monitoring indexes (the nitrogen application rate and rainfall) for greenhouse vegetable planting system have been proposed in the study. Statistical validation confirmed that these newly developed monitoring indicators can improve the prediction accuracy of non-point source pollution emission. Therefore, this study provides a convenient and effective method of environment monitoring and management for the environmental protection authorities of government.

       

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