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