Chinese Soil Moisture Observation Network and Time Series Data Set for High Resolution Satellite Applications

High-quality ground observation networks are an important basis for scientific research. Here, an automatic soil observation network for high-resolution satellite applications in China (SONTE-China) was established to measure both pixel- and multilayer-based soil moisture and temperature. SONTEChina is distributed across 17 field observation stations with a variety of ecosystems, covering both dry and wet zones. In this paper, the average root mean squared error (RMSE) of station-based soil moisture for well-characterized SONTE-China sites is 0.027 m(3)/m(3) (0.014 similar to 0.057 m(3)/m(3)) following calibration for specific soil properties. The temporal and spatial characteristics of the observed soil moisture and temperature in SONTE-China conform to the geographical location, seasonality and rainfall of each station. The time series Sentinel-1 C-band radar signal and soil moisture show strong correlations, and the RMSE of the estimated soil moisture from radar data was lower than 0.05 m(3)/m(3) for the Guyuan and Minqin stations. SONTE-China is a soil moisture retrieval algorithm that can validate soil moisture products and provide basic data for weather forecasting, flood forecasting, agricultural drought monitoring and water resource management.

Automated summary

The SONTE-China network in China measures pixel- and multilayer-based soil moisture and temperature, covering dry and wet zones. It validates soil moisture products and provides basic data for weather forecasting, flood forecasting, agricultural drought monitoring, and water resource management.