麦田生态系统CO2通量自动监测系统设计与试验

Design and Test of Automated CO2 Flux Monitoring System for Wheat Field Ecosystem

摘要:

为克服传统箱法监测农田CO2通量自动化程度低、通量测量类型单一、设备部署困难以及运行成本高等问题，本研究设计了一套麦田生态系统CO2通量自动监测系统，集成主控箱、自动气体箱、太阳能供电和云平台管理系统，可低成本地实现麦田生态系统土壤呼吸通量和冠层CO2交换通量的长期无人值守自动监测。采用高精度、低成本CO2传感器，实时监测自动气体箱内CO2浓度变化速率，同时采集箱内空气温湿度、气压，土壤理化参数等多源环境信息，并进行本地存储;通过GPS和4G模块实现时空数据同步采集与远程传输;利用云平台管理系统实现数据云存储、通量计算和指令下发。为评估系统的精度和稳定性，以陕西省杨凌示范区冬小麦为研究对象，分别进行施氮量为0、100、150、200 kg/hm2处理，在冬小麦拔节期、抽穗期与灌浆期分别持续监测5~7 d冠层CO2通量，并以商用LI-850型气体分析仪同步测量结果为标准。试验结果表明，当通量为-23.01~11.67 μmol/(m2·s)时，该系统与标准设备监测结果线性拟合决定系数R2为0.964，RMSE为1.57 μmol/(m2·s)，具有较高的精度和稳定性。在不同温度、湿度和光合有效辐射条件下，能准确捕捉环境因子变化对冠层CO2通量的响应;同时，可准确识别不同氮施用量引起的小麦冠层CO2通量差异。研究结果可为麦田生态系统碳通量监测提供有效的技术支持。

Abstract:

Aiming to address the limitations of traditional chamber methods in monitoring CO2 fluxes in cropland ecosystems, such as low automation, single measurement types, difficult equipment deployment, and high operational costs, an automated monitoring system for CO2 flux in wheat agroecosystems was developed. By integrating a main control unit, automated gas chambers, a solar-powered supply, and a cloud-based management platform, the system enabled low-cost, long-term, and unattended monitoring of both soil respiration flux and canopy CO2 exchange flux. Utilizing high-precision, low-cost CO2 sensor, the system monitored the rate of change in CO2 concentration within the chambers in real time. Simultaneously, it collected and locally stored multi-source environmental data, including air temperature, humidity, atmospheric pressure, and soil physicochemical parameters. Spatio-temporal data synchronization and remote transmission were achieved via GPS and 4G modules, while the cloud platform facilitated cloud storage, flux calculation, and command dispatch. To evaluate the system's accuracy and stability, experiments were conducted on winter wheat in Yangling, Shaanxi Province, at four nitrogen application rates (0 kg/hm2, 100 kg/hm2, 150 kg/hm2, and 200 kg/hm2). Canopy CO2 flux was monitored for 5~7 days during the jointing, heading, and filling stages, respectively, using the commercial LI-850 gas analyzer as the reference. The results showed that within a flux range of -23.01~11.67 μmol/(m2·s), the system demonstrated high precision and stability, with a coefficient of determination (R2) of 0.964 and a root mean square error (RMSE) of 1.57 μmol/(m2·s) compared with the standard equipment. Under varying conditions of temperature, humidity, and photosynthetically active radiation, the system accurately captured the response of canopy CO2 flux to environmental factors and effectively identified differences in wheat canopy CO2 flux induced by different nitrogen levels. The research result can provide robust technical support for carbon flux monitoring in wheat field ecosystems.