A breakthrough program for intelligent regulation of non-point source pollution: From accurate observation to fine management
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摘要:
农业面源污染不仅造成了地表水环境恶化, 而且严重制约了农业绿色可持续发展, 近年来愈发得到各部门高度重视, 相关监测方案和管理体系逐步建立, 但是仍存在面源污染治理成效较低的问题。本文总结了面源污染监测在不同尺度下的监测对象、时空精度、污染源识别方案和管理措施现状, 指出了监测精度不足、污染源识别动态性不足、污染源和管理措施匹配性不足的瓶颈, 这也直接或间接导致面源污染监测体系不健全、智能化不足、精细化程度较低和污染治理效率较低等问题。随着信息化和数字化发展, 物联网平台通过集成天空地一体化监测设备与算法, 成为智能化监管的关键抓手, 为面源污染精细化监测提供了技术支撑, 构建农业面源污染物联网智能观测体系, 解决模型关键参数观测精度问题, 利用“面源污染模型+指纹示踪”的面源多污染源识别与追踪技术体系, 解决污染源精准定位问题, 考虑多污染源和多治理模式的成效评估及方案优选, 解决精准化和差别化治理问题。最终实现面源管控的系统性、集成性和智能性水平提升, 打通从“监测”到“治理”的关键突破路径。物联网智能监测平台应用与示范在太湖流域逐步开展, 为农业面源污染智慧监管破局提供了重要参考。
Abstract:Agricultural non-point source pollution not only causes deterioration of the surface water environment but also seriously restricts the green and sustainable development of agriculture. In recent years, relevant monitoring plans and management systems with increasing emphasis on non-point source pollution control have gradually been established in China. However, there are still some problems with the low effectiveness of non-point source pollution control. We summarized the status of monitoring targets, spatiotemporal resolution, source identification methods, and management measures for non-point pollution monitoring at different scales. This pointed out the problems of discontinuous monitoring of non-point source pollution, insufficient spatiotemporal refinement and estimation accuracy of non-point source pollution load, lack of dynamic identification of pollution sources, and insufficient matching between pollution sources and management measures, which directly or indirectly lead to an imperfect monitoring system, insufficient intelligence, low level of refinement, and low efficiency of pollution control for non-point source pollution. With the development of informatization and digitization, the Internet of Things platform has become a key lever for intelligent supervision by integrating sky and ground monitoring equipment and algorithms and providing technical support for finely monitoring non-point source pollution. The construction of an intelligent observation system for Internet of Things for agricultural non-point source pollutant to improve the observation accuracy of key parameters, using the “non-point source model + fingerprint tracing” technology system for identifying and tracking multiple sources of non-point source pollutants sources area, and considering the effectiveness evaluation and scheme optimization of multi-source and multi governance models to solve the problem of precise and differentiated governance was proposed. Finally, the systematic, integrated, and intelligent level of non-point source control will be improved, and connect the key breakthrough path from “monitoring” to “governance”. The application and demonstration of the Internet of Things intelligent monitoring platform were carried out in the Taihu Basin, which has both plain and hilly complex terrain, a dense population, and active agricultural activities. This typical case has integrated monitoring instruments, a non-point source pollution simulation model, pollution source identification, and other parts, providing an important reference for the intelligent supervision of agricultural non-point source pollution.
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图 1 面源污染“精准观测—精细管理”的破局路径
Figure 1. Breakthrough path of “precise observation–fine management” for non-point source pollution
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图 2 “卫星遥感+物联网”观测体系
Figure 2. “Satellite remote sensing + Internet of Things” observation system
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图 3 基于“面源污染模型+指纹示踪”的多污染源精准定位、识别与追踪
Figure 3. Accurate localization, identification and tracking of multi-source areas based on “non-point source pollutant model + fingerprint tracing”
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图 5 面源污染物联网装备体系管理平台
Figure 5. Internet of Things Equipment System Management Platform for non-point source pollution
表 1 不同尺度下面源污染负荷监测时空分辨率及其主要监测对象[5,7,20-35]
Table 1 Spatiotemporal resolution and main monitoring objects of non-point source pollution monitoring at different scales[5,7,20-35]
监测尺度
Scale of monitoring时间分辨率
Temporal resolution监测单元/空间分辨率
Monitoring unit /
spatial resolution主要监测对象
Main monitoring object地块/圩区
Land plot / polder area逐分钟至逐月
Minute by minute to month by month田块/最高可达米级
Field plot / up to meter level农田径流、农田淋溶、农艺措施、畜禽养殖排污、农村生活污水排污、土壤理化特征和植被特征
Farmland runoff, farmland leaching, agronomic measures, discharge of livestock and poultry production wastewater, discharge of rural domestic wastewater, soil physical and chemical characteristics, and plant characteristics小流域/县区
Small basin / county or district逐小时至逐年
Hour by hour to year by year子流域/最高可达十米级
Sub-basin / up to ten-meter level农艺措施、畜禽养殖排污、农村生活污水排污、大气沉降、流域水文水质、气象要素、土壤理化特征和植被特征
Agronomic measures, discharge of livestock and poultry production wastewater, discharge of rural domestic wastewater, atmospheric deposition, hydrology and water quality of basin, meteorological element, soil physical and chemical characteristics, and plant characteristics大流域/省级及以上
Large watershed / provincial or higher scale逐月至逐年
Month by month to year by year行政边界或者子流域/千米级及以上
Administrative boundary or sub-basin / kilometer or higher level
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表 2 农业面源污染监测对象、技术和时空分辨率[36-47]
Table 2 Monitoring objects, technologies, and spatiotemporal resolution of agricultural non-point source pollution monitoring[36-47]
监测对象
Monitoring object监测技术
Monitoring technology监测指标
Monitoring indicator时间分辨率
Temporal resolution空间分辨率/数量
Spatial resolution / number农田径流
Farmland runoff流量计法、堰测法、人工模拟降雨和导流管-径流桶法
Flow meter method, weir measurement method, artificial simulated rainfall, and diversion pipe-runoff bucket method全氮、氨态氮、硝态氮、总磷、可溶性磷等
Total nitrogen, ammoniacal
nitrogen, nitrate, total phosphorus,
dissolved phosphorus, etc.逐分钟至逐月
Minute by minute to month by month根据地块布设监测点位
Set up monitoring points according to the plot农田淋溶
Farmland leaching淋溶盘法、淋溶集水槽法、
渗漏池法、抽滤管法和土柱实验法
Leaching tray method, leaching collection tank method, leakage pool method, filtration tube method, and lysimeter method全氮、氨态氮、硝态氮、
总磷和可溶性磷等
Total nitrogen, ammoniacal nitrogen, nitrate, total phosphorus, dissolved phosphorus, etc.逐分钟至逐月
Minute by minute to month by month根据地块布设监测点位
Set up monitoring points according to the plot农艺措施
Agronomic measure入户调研法和统计年鉴法
Household survey method and statistical yearbook method化肥施用量、水肥比例
和用水量等
Chemical fertilizer application, ratio of water to fertilizer, water consumption, etc.逐季度至逐年
Season by season to year by year根据地块或片区调研
Investigation based
on the plot or area畜禽养殖排污
Discharge of livestock and poultry production wastewater系数法和代谢笼采样法
Coefficient method and
metabolic cage sampling method全氮、全磷和化学需氧量等
Total nitrogen, total phosphorus, chemical oxygen demand, etc.根据饲养阶段
设置监测时间
Set monitoring time according to
feeding stage根据养殖场分布格局
布设监测点位
Set up monitoring points according to the distribution of farm农村生活污水排污
Discharge of rural domestic wastewater污水收集设施测定
Measurement of sewage
collection facility全氮、全磷和化学需氧量等
Total nitrogen, total phosphorus, chemical oxygen demand, etc.逐月至逐年
Month by month to year by year根据居民点分布格局
布设监测点位
Set up monitoring points according to the distribution of residential area大气沉降
Atmospheric deposition大气沉降桶测定法
Atmospheric deposition bucket measurement method全氮和全磷等
Total nitrogen, total phosphorus, etc.逐月至逐年
Month by month to year by year根据研究区布设监测点位
Set up monitoring points according to the the research area流域水文水质
Hydrology and water quality of basin流量计法、水文站监测、水质仪法等
Flow meter method, hydrological station monitoring and water quality meter method, etc流量、流速、全氮、全磷和化学需氧量等
Flow rate, flow velocity, total nitrogen, total phosphorus, chemical oxygen demand, etc.逐分钟至逐月
Minute by minute to month by month根据流域水系结构和水文特征
布设监测点位
Set up monitoring points based on the water system structure and hydrological characteristics of the watershed气象要素
Meteorological element气象监测仪器法
Meteorological monitoring
instrument method降水量、降水强度和温度等
Precipitation, precipitation intensity, temperature, etc.逐分钟至逐月
Minute by minute to month by month根据研究区地形地貌等特征
布设监测点位
Set up monitoring points based on the terrain and landforms of the research area土壤理化特征
Soil physical and chemical characteristics实地样品采集和地统计方法
Field sample collection and geostatistical methods土壤有机质、全氮和全磷等
Soil organic matter, total nitrogen, total phosphorus, etc.逐季节至逐年
Season by season to year by year根据土地利用等地表特征
布设监测点位
Set up monitoring points based on surface features such as land use植被特征
Plant characteristics点取法、样方法、遥感估算法
Point sampling method, quadrat sampling method, remote sensing estimation method植被覆盖度
Vegetation cover逐日至逐年
Day by day to
year by year根据土地利用和植被类型等地表特征布设监测点位, 或者根据遥感影像分辨率确定监测点位
Set up monitoring points based on surface features such as land use and vegetation types, or determine monitoring points based on remote sensing image resolution
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名称
Name操作方法
Operation method时空分辨率
Spatiotemporal resolution优势
Advantage限制
Limitation面源污染模型模拟
Simulation of non-point source pollution model基于地面观测、径流小区试验以及卫星遥感技术构建模型, 模拟区域营养盐负荷和划分流失等级
Develop models based on ground observations, runoff plot experiments and remote sensing to simulate regional nutrient loads and classify loss levels取决于面源污染模型机
理和输入参数, 主要分
辨率为月际和子流域
Depending on the mechanism and input parameters of the non-point source pollution model, and the main resolutions are month and
sub-basin应用广泛, 适用于模拟大范
围长时间尺度的面源污染模拟
Widely applicable and suitable for simulating large-scale and long-term non-point source pollution simulation需要大量观测数据, 各类模
型适用边界不同, 不确定性高
Require a large amount of observational data, and different models have different applicable boundaries. High uncertainty同位素示踪
Isotope tracing通过富集、分离和纯化各形态氮, 测定氮氧同位素组成, 对比理论平衡值和判断氮来源
Determinating nitrogen and oxygen isotope compositions, comparing with theoretical equilibrium values, and determining nitrogen sources via enrichment, isolation and purification of nitrogen forms取决于降水事件和试验条
件, 最高可达日级和田块
Depending on precipitation events and experimental conditions, the resolution can reach up to daily and field能准确有效识别不同污染源,
能建立受纳水体和污染源的
直接联系
Accurately and effectively identify different pollution sources, and establish direct connections between receiving water bodies and source areas主要溯源氮流失, 输移过程
中各形态氮间会相互转化,
操作复杂, 来源判别数量
有限, 成本高昂
Mainly focusing on the traceability of nitrogen
losses, and inter-conversion
between different forms of nitrogen during transport.
Complexity of operation,
limited number of source
identification, and high cost指纹示踪
Fingerprint tracing通过测定泥沙和污染源土壤样本的地化性质, 构建泥沙指纹示踪模型, 结合污染物输出系数, 开发颗粒态污染物示踪模型
By measuring the geochemical properties of sediment and source samples, develop sediment fingerprint tracing model, and particulate pollutants tracing model combined with pollutant output coefficients取决于降水事件和试验条件, 最高可达日级和田块类型
Depending on precipitation events and experimental conditions, the resolution can reach up to day level and field能建立受纳水体和污染源
的直接联系, 并定量获取
污染源位置/类型的贡献率
Establish direct connection between the receiving water
body and the source area, and quantitatively obtain the contribution rate of different pollution source location / type主要溯源颗粒态污染物, 操
作复杂, 来源判别数量有限,
不确定性高, 成本高昂
Mainly focusing on traceability of particulate pollutants. Complex operation, limited number of source identifications, high uncertainty, and high cost
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