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应用生态学报 ›› 2025, Vol. 36 ›› Issue (10): 3225-3230.doi: 10.13287/j.1001-9332.202510.034

• 技术方法 • 上一篇    

生态系统土壤水热远程监测网络的低成本构建方法

王浩飞1,2, 刘斌3, 王丽3, 朱美玲3, 冯亮亮3, 倪兴成3, 李轾3, 樊军1,4*   

  1. 1西北农林科技大学水土保持与荒漠化整治全国重点实验室, 陕西杨凌 712100;
    2西北农林科技大学资源环境学院, 陕西杨凌 712100;
    3神木市林业局, 陕西神木 719300;
    4中国科学院水利部水土保持研究所, 陕西杨凌 712100
  • 收稿日期:2025-02-10 修回日期:2025-08-25 发布日期:2026-05-04
  • 通讯作者: *E-mail: fanjun@ms.iswc.ac.cn
  • 作者简介:王浩飞, 男, 1998年生, 博士研究生。主要从事人工林生态系统服务功能研究。E-mail: wanghaofei@nwafu.edu.cn
  • 基金资助:
    国家重点研发计划项目(2021FY100705)和陕西省神木市林业局与水利局科技项目(SMSL2023QQZX2301)

A low-cost construction method for remote monitoring network for soil moisture and temperature in ecosystems

WANG Haofei1,2, LIU Bin3, WANG Li3, ZHU Meiling3, FENG Liangliang3, NI Xingcheng3, LI Zhi3, FAN Jun1,4*   

  1. 1State Key Laboratory of Soil and Water Conservation and Desertification Control, Northwest A&F University, Yangling 712100, Shaanxi, China;
    2College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, Shannxi, China;
    3Shenmu Forestry Bureau, Shenmu 719300, Shaanxi, China;
    4Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, Shaanxi, China
  • Received:2025-02-10 Revised:2025-08-25 Published:2026-05-04

摘要: 随着自动化技术发展,远程监测网络将在生态系统数据获取与高效处理上发挥优势,为生态监测和资源管理提供数据支持。本文采用国产低成本智能数字传感器与采集器,集成构建了一种生态系统土壤水热远程监测网络,实现了对多参数(土壤水分、温度、空气温湿度和降水量)的长期连续监测和数据远程传输。具体安装流程包括:1)样点选择:综合考虑地形地貌与植被类型等选择有代表性的监测样点;2)设备安装:通过田间钻孔法在选定样点2 m深土壤剖面上安装不同深度土壤水热传感器,并通过总线方式连接到由10 W太阳能板供电的数据采集器;3)数据记录:每小时测量存储一组数据汇聚到基于互联网的服务器。与进口设备相比,该方法设备成本为进口设备的20%左右。基于该方法,在陕西省神木市构建了包含60个样点的监测网络,包括沙黄土和沙土两种主要土壤质地,进行实际运维与验证。结果表明,在不同土壤质地条件下该网络均可精准捕捉不同深度土壤水分和温度变化,并表现出良好的测量精度(R2≥0.90),监测网络还可以实现对空气湿度和降水的同步观测。本研究建立的远程监测网络为多样点生态系统土壤水热远程监测提供了技术范式,对推动生态系统原位动态观测具有积极意义。

关键词: 土壤水分, 土壤温度, 远程监测网络, 样点选择

Abstract: With the development of automation technology, the advantages of remote monitoring network in the acquisition and efficient processing of ecosystem data will be more prominent and provide data support for ecological monitoring and resource management. We employed domestic low-cost sensors and intelligent data collectors to construct a remote monitoring network for soil moisture and temperature, achieving long-term continuous monitoring of multi-parameters (soil moisture, temperature, air temperature, air humidity and rainfall) and automatic data transmission. The specific installation process including: 1) Sample point selection: select representative monitoring sampling points based on the comprehensive consideration of topography, landform and vegetation type; 2) Equipment installation: install five soil hydrothermal sensors in the 2 m soil profile by field drilling method, and connect the sensors to the intelligent collector powered by 10 W solar panels through the intelligent data collector, measure and store a set of data per hour; 3) Data recording: measure and store data per hour and aggregate to a server based on the internet. The cost of this equipment is approximately 20% of that of the imported equipments. Based on this method, a network of 60 sampling points with two main soil textures, sand loess and sand, was established in Shenmu, Shaanxi Province. Actual operation and maintenance as well as verification were conducted. The results showed that the network can accurately capture the changes of soil moisture and temperature at different depths, and the sensors exhibited great measurement accuracy (R2≥0.90). The monitoring network enabled synchronous observation of air humidity and precipitation. The remote monitoring network established in this study provides a technical paradigm for the remote monitoring of soil moisture and temperature in diverse ecosystems.

Key words: soil moisture, soil temperature, remote monitoring network, sample selection