Abstract

Ground-penetrating radar (GPR) is a convenient geophysical technique for active-layer soil moisture detection in permafrost regions, which is theoretically based on the petrophysical relationship between soil moisture (θ) and the soil dielectric constant (ε). The θ–ε relationship varies with soil type and thus must be calibrated for a specific region or soil type. At present, there is lack of such a relationship for active-layer soil moisture estimation for the Qinghai–Tibet plateau permafrost regions. In this paper, we utilize the Complex Refractive Index Model to establish such a calibration equation that is suitable for active-layer soil moisture estimation with GPR velocity. Based on the relationship between liquid water, temperature, and salinity, the soil water dielectric constant was determined, which varied from 84 to 88, with an average value of 86 within the active layer for our research regions. Based on the calculated soil-water dielectric constant variation range, and the exponent value range within the Complex Refractive Index Model, the exponent value was determined as 0.26 with our field-investigated active-layer soil moisture and dielectric data set. By neglecting the influence of the soil matrix dielectric constant and soil porosity variations on soil moisture estimation at the regional scale, a simple active-layer soil moisture calibration curve, named CRIM, which is suitable for the Qinghai–Tibet plateau permafrost regions, was established. The main shortage of the CRIM calibration equation is that its calculated soil-moisture error will gradually increase with a decreasing GPR velocity and an increasing GPR velocity interpretation error. To avoid this shortage, a direct linear fitting calibration equation, named as υ-fitting, was acquired based on the statistical relationship between the active-layer soil moisture and GPR velocity with our field-investigated data set. When the GPR velocity interpretation error is within ±0.004 m/ns, the maximum moisture error calculated by CRIM is within 0.08 m3/m3. While when the GPR velocity interpretation error is larger than ±0.004 m/ns, a piecewise formula calculation method, combined with the υ-fitting equation when the GPR velocity is lower than 0.07 m/ns and the CRIM equation when the GPR velocity is larger than 0.07 m/ns, was recommended for the active-layer moisture estimation with GPR detection in the Qinghai–Tibet plateau permafrost regions.

Highlights

  • Soil moisture information is essential for understanding permafrost regions’ environmental evolution, such as active-layer freezing and thawing processes and its special distribution modelling

  • The laboratory experiment by Yuanshi [26] revealed that each 0.1 g/cm3 increase in soil bulk density will result in a −0.004 cm3/cm3 measurement error in soil water content with a time domain reflectometry (TDR) sensor, which means that a 1 g/cm3 soil density difference only has a 0.04 cm3/cm3 soil water calculation error, which is smaller than or equivalent to many soil moisture calibration curves’ calculated errors

  • We used 18 active layer Ground-penetrating radar (GPR) detecting pits that were distributed in different areas in the Qinghai–Tibet plateau permafrost region to construct active-layer soil moisture measure methods with GPR signal travel speed

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Summary

Introduction

Soil moisture information is essential for understanding permafrost regions’ environmental evolution, such as active-layer freezing and thawing processes and its special distribution modelling. The active layer is defined as the layer of ground that is subject to seasonal thawing and freezing in areas underlain by permafrost It plays a vital role in hydrological processes, heat flux exchanges between ground and air, as well as land surface modeling. Active-layer soil moisture was often monitored with the buried time domain reflectometry (TDR) [1] sensor or acquired through traditional gravimetric methods with active-layer profile soil samples These in situ measurements may be prone to uncertainties due to, for example, loss of intimate contact between sensors and the surrounding soil because of shrinkage or biological activity, or a lack of calibration, especially for soils with high specific surface areas. Because of the high spatial variability of soil moisture due to spatiotemporal variations of associated meteorological and biogeophysical parameters, measurement and monitoring of large-scale active-layer soil moisture is challenging

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