| 陈诚,怀红燕,吴阿娜,刘熠阳,陈小华,沈根祥.平原河网地区农田面源污染月尺度入河系数精准测算方法[J].农业环境科学学报,2024,43(12):2838-2847. |
| 平原河网地区农田面源污染月尺度入河系数精准测算方法 |
| Method of monitoring and calculating monthly export coefficient of farmland non-point source pollution at outlets into rivers in the plain river network areas |
| 投稿时间：2024-10-12 |
| DOI：10.11654/jaes.2024-0862 |
| 中文关键词: 平原河网地区 水文水质协同监测 农田面源污染入河系数 自动采样 负荷分类评估 微积分算法 |
| 英文关键词: plain river network area collaborative monitoring of hydrology and water quality export coefficient of farmland non-point source pollution at outlets into rivers automatic sampling classified load estimation calculus algorithm |
| 基金项目:上海市农业科技创新项目（产业提升项目）[沪农科（I2023008，I2023004）]；上海市科技创新行动计划项目（21DZ1202400）；上海市生态环境局工作课题（H2023090168） |
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| 中文摘要: |
| 为充分考虑平原河网地区特有的地理环境和水系特点，精细化排摸其农田面源污染排放底数与排放特征，基于上海市“4+9”（4个市级试点+9个区级试点）农田面源污染试点监测评估成果构建了面源污染月尺度入河系数测算的成套技术方法体系。平原河网地区农田面源污染入河系数测算包括监测区域选取、基础资料搜集、监测单元划定、监测点位布设、采样监测周期和方式选择、自动采样触发条件和监测频次设置、监测指标选定、（净）入河系数计算、负荷分类评估、质量控制等10个重要环节。在农田入河排放口开展流量高频在线监测，并合理设置程序触发水质自动采样，以完整捕捉农田产流事件全过程。针对农田面源污染的脉冲式输出特征设置“先密后疏”的采样频次，结合水文监测数据对降水、灌溉和倒灌产流事件进行识别，根据施肥时间节点等选取典型产流事件开展面源污染监测，分别计算入河负荷和净入河负荷，并采用微积分算法和平均浓度法分别估算监测期和非监测期的入河负荷，从而实现全周期负荷精准评估，并定量分析人为（可控）因素与自然（不可控）因素对面源污染排放造成的影响。针对2024年9月双台风首次同时登陆上海的汛期农田面源污染排放典型事件的监测评估结果表明，试验稻田当月总磷、磷酸盐、总氮、氨氮、硝酸盐氮、高锰酸盐指数的入河系数分别为0.225、0.093、1.719、0.597、0.775、4.916 kg·hm-2·月-1。 |
| 英文摘要: |
| In order to sufficiently consider the unique characteristics of geographical environment and river systems in the plain river network areas, and accurately investigate the export amount and characteristics of farmland non-point source pollution, a complete series of technical method system was established for monitoring and calculating the monthly export coefficient of non-point source pollution at outlets into rivers based on Shanghai “4+9” （four municipal pilots + nine district-level pilots）farmland non-point source pollution pilot monitoring and evaluation. Farmland non-point source pollution monitoring and calculation in the plain river network areas require ten important steps, including determination of monitoring areas, collection of basic documents, delimitation of monitoring units, selection of monitoring points, choosing of sampling and monitoring period and mode, setting of triggering criteria and monitoring frequency, selection of monitoring index, calculation of（net）export coefficients at outlets into rivers, classified evaluation of load and quality control. Highfrequency online monitoring of discharge was conducted at farmland outlets into rivers. Procedure was reasonably set up to trigger automatic sampling for water quality analysis so as to capture the entire process of field-scale runoff events. The sampling frequency was set up to frequent at first and then gradually to sparse according to the pulse-type export characteristics of farmland non-point source pollution. The precipitation, irrigation and backflow events were recognized with hydrology monitoring data. Non-point source pollution monitoring was conducted during typical runoff events according to the fertilization time. Loads and net loads discharged into the river were respectively calculated. The loads discharged into the river during monitoring and non-monitoring periods were estimated with the application of calculus algorithm and mean concentration methods, respectively. Consequently, the accurate estimation of loads during the whole period was accomplished and the influence of human（controllable）and natural（uncontrollable）factors on non-point source pollution export was quantificationally analyzed. A typical farmland non-point source pollution export event was monitored during the first landing of two successional typhoons in Shanghai in September, 2024 since records began. The monitoring and estimation results indicated that the export coefficient at the outlet into the river of total phosphorus, phosphate, total nitrogen, ammonia nitrogen, nitrate nitrogen and permanganate index were 0.225, 0.093, 1.719, 0.597, 0.775 kg·hm-2·month-1 and 4.916 kg·hm-2·month-1, respectively. |
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