Welcome to Smart Agriculture

Smart Agriculture ›› 2022, Vol. 4 ›› Issue (1): 84-96.doi: 10.12133/j.smartag.SA202202010

• Topic--Crop Growth and Its Environmental Monitoring • Previous Articles     Next Articles

Monitoring Specified Depth Soil Moisture in Field Scale with Ground Penetrating Radar

ZHANG Wenhan1(), DU Keming2(), SUN Yankun1(), LIU Buchun2, SUN Zhongfu2, MA Juncheng2, ZHENG Feixiang2   

  1. 1.College of Resources and Environment, Northeast Agricultural University, Harbin 150030
    2.Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081
  • Received:2021-12-25 Online:2022-03-30
  • Supported by:
    National Key Research and Development Program of China(2016YFD0300606);National Natural Science Foundation of China(31628015)


Ground-penetrating radar (GPR) is one of the emerging technologies for soil moisture measurement. However, the measurement accuracy is difficult to determine due to some influence factors including radar wave frequency, soil texture type, etc. The GPR equipment with 1000 MHz center frequency and the measurement method of common midpoint (CMP) were adopted in the research to collect radar wave raw data in the selected field area under arid soil and moist soil conditions. The transmitter and receiver antennas of the GPR equipment were moved 0.01 m respectively in opposite directions on each radar wave raw data collection. Therefore, a CMP radar image consisted of 100 pieces of radar wave raw data by increasing the antenna distance from 0 m to 2 m. Each radar wave raw data indicated that the radar waves were reflected in the reflective layer with different dielectric constant under the same antenna distance. And the reflected and refracted radar waves were acquired by the receiving antenna at different two-way travel time respectively, and recorded in the computer. The collection of CMP soundings aimed to determine the inversion accuracy, optimum inversion depth, effective inversion depth and optimal inversion model of soil moisture content at different depth ranges and adjacent reflective layers by GPR at field scale. The reflected and refracted radar wave data were extracted from the raw data. The velocities of the surface waves and reflected waves were obtained respectively from the line slope of the surface wave data and the hyperbolic curves fitting of the reflected wave data. In addition, the relative dielectric constant of the soil at specified depth were deduced according to the soil dielectric constant and its reflected wave velocity. Moreover, 4 different models including Topp, Roth, Herkelrath and Ferre were used to figure out the soil volumetric water content inversion. Meanwhile, the measured data of soil volumetric moisture content obtained by oven drying method were used to verify the accuracy of the inversion results. The results showed that the effective inversion depth of 1000 MHz GPR ranged from 0 to 50 cm. The best inversion depth was 50 cm in arid soil and 40 cm in moist soil. The Roth model had the best correlation and stability with the highest R2 was 0.750, the Root Mean Square Error (RMSE) was 0.0114 m3/m3 and the lowest Relative Error (RE) was 3.0%. The GPR could possess the capacity of quick, precise and non-destructive measurement of specified depth soil moisture in field scale. The inversion model of soil moisture content needs to be calibrated according to different soil conditions.

Key words: ground penetrating radar, soil water content monitoring, common midpoint, optimum inversion depth, optimum inversion model, Roth model

CLC Number: