Preprints
https://doi.org/10.5194/tc-2020-236
https://doi.org/10.5194/tc-2020-236

  26 Aug 2020

26 Aug 2020

Review status: this preprint is currently under review for the journal TC.

Three-in-one: GPS-IR measurements of ground surface elevation changes, soil moisture, and snow depth at a permafrost site in the northeastern Qinghai-Tibet Plateau

Jiahua Zhang1, Lin Liu1, Lei Su2,3, and Tao Che2,4 Jiahua Zhang et al.
  • 1Earth System Science Programme, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, 999077, China
  • 2Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
  • 3University of Chinese Academy of Sciences, Beijing, 100049, China
  • 4Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, 100101, China

Abstract. Ground surface elevation changes, soil moisture, and snow depth are all essential variables for studying the dynamics of the active layer and permafrost. GPS interferometric reflectometry (GPS-IR) has been used to measure surface elevation changes and snow depth in permafrost areas. However, its applicability to estimating soil moisture in permafrost regions has not been assessed. Moreover, these variables were usually measured separately at different sites. Integrating their estimates at one site facilitates the comprehensive utilization of GPS-IR in permafrost studies. In this study, we run simulations to elucidate that the commonly-used GPS-IR method for estimating soil moisture content cannot be directly used in permafrost areas, because it does not consider the bias introduced by the seasonal surface elevation changes due to thawing of the active layer. We propose a solution to improve this default method by introducing modeled surface elevation changes. We validate this modified method using the GPS data and in situ observations at a permafrost site in the northeastern Qinghai-Tibet Plateau (QTP). The root-mean-square error and correlation coefficient between the GPS-IR estimates of soil moisture content and the in situ ones improve from 1.85 % to 1.51 % and 0.71 to 0.82, respectively. We also implement a framework to integrate the GPS-IR estimates of these three variables at one site and illustrate it using the same site in the QTP as an example. This study highlights the improvement to the default method, which makes the GPS-IR valid in estimating soil moisture content in permafrost areas. The three-in-one framework is able to fully utilize the GPS-IR in permafrost areas and can be extended to other sites such as those in the Arctic. This study is also the first to use GPS-IR to estimate environmental variables in the QTP, which fills a spatial gap and provides complementary measurements to those of ground temperature and active layer thickness.

Jiahua Zhang et al.

Jiahua Zhang et al.

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Short summary
We improve the commonly-used GPS-IR method for estimating soil moisture in permafrost areas, which does not consider the bias introduced by seasonal surface elevation changes. We implement a framework to integrate the GPS-IR measurements of ground surface elevation changes, soil moisture, and snow depth at one GPS site, and illustrate an example by using a GPS site in Qinghai-Tibet Plateau. This study is also the first to use GPS-IR to measure environmental variables in Qinghai-Tibet Plateau.