Agricultural non-point source (NPS) pollution is a major cause of water quality degradation, with pollutants such as nitrogen and phosphorus carried by farmland surface runoff being important sources. Statistics show that in 2017, the total nitrogen discharge from agricultural sources in China reached 1.4149 Mt, and total phosphorus was 212 kt. Among these, the nitrogen and phosphorus emissions from cropping alone accounted for 51% and 36% of agricultural source pollutants, respectively. However, current farmland runoff monitoring methods have obvious limitations: traditional runoff pool monitoring has a small range and is prone to interruption by heavy rains; manual sampling is time-consuming and labor-intensive with insufficient data representativeness; and there are large uncertainties when extrapolating monitoring results from experimental plots to field scales. How to establish a technical system that can not only truly reflect the actual situation of farmland but also realize automated and large-scale continuous monitoring has become the key to solving the problem of agricultural NPS pollution prevention and control.
Wenchao Li from Hebei Agricultural University and Lingling Hua from Beijing University of Agriculture et al. have developed an online monitoring system for NPS pollution in continuous cropping farmland based on a serial pipeline. The system, with diversion trenches, online flowmeters, and dynamic acquisition devices as the core, realizes real-time monitoring and automated sampling of farmland runoff through innovative design. Compared with traditional runoff pools, the design of diversion trenches and transmission pipelines in the new system significantly reduces the project scale, lowers construction costs and land occupation, and avoids interference with agricultural production activities. The related paper had been published in Frontiers of Agricultural Science and Engineering ( DOI: 10.15302/J-FASE-2024596 ).
The core advantage of this system lies in breaking through multiple limitations of existing technologies. In terms of monitoring range, by laying diversion trenches and transmission pipelines, it can realize centralized runoff monitoring of continuous cropping farmland covering hundreds of hectares, overcoming the limitation that traditional runoff pools are only suitable for small plots of tens of square meters. In terms of data reliability, online flowmeters and water quality monitoring devices can collect real-time parameters such as flow rate, total nitrogen, total phosphorus, and chemical oxygen demand (COD). The dynamic acquisition device triggers sampling through a rainfall sensor, automatically collecting a representative water sample for each rainfall event, which solves the problems of poor timeliness of manual sampling and the inability of automatic samplers to reflect the entire runoff process. In addition, the system supports remote data transmission and control, allowing managers to view monitoring data in real-time through the client, and automatic alarms are triggered in case of abnormal water quality, greatly improving the efficiency of emergency response.
In the field application in the Baiyangdian Basin of Xiong'an New Area, Hebei Province, the system demonstrated good stability and accuracy. Monitoring data from July to August 2023 showed that the developed system could accurately capture the runoff lag effect—for example, after the rainfall on August 11, runoff began to form at 11:00 the next day and gradually increased, a process that was highly consistent with meteorological data. Under extreme heavy rain conditions, increasing the monitoring frequency could track flow changes in real-time, verifying the system's ability to respond to complex hydrological processes.
The method applied in experimental plots in this system has been listed as a key technology for comprehensive control of agricultural NPS pollution by the Agricultural Ecology and Resource Protection Station of the Ministry of Agriculture and Rural Affairs of China. Compared with traditional methods relying on experimental plots, its monitoring data are more in line with actual farmland production scenarios, which can provide more reliable parameters for estimating agricultural NPS pollution loads. With the promotion of the technology, the system is expected to play an important role in the next national pollution source census, providing scientific support for formulating targeted prevention and control strategies and improving the water ecological environment.
