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Stochastic representation of spatial variability in thaw depth in permafrost boreal forests

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  • Taro Nakai
  • Tetsuya Hiyama
  • Ayumi Kotani
  • Yoshihiro Iijima
  • Takeshi Ohta
  • Trofim C. Maximov

Abstract

A simple stochastic representation of the spatial variability in thaw depth is proposed. Thaw depth distribution measured in the two larch‐type forests in eastern Siberia, Spasskaya Pad and Elgeeii, showed different spatial, seasonal, and interannual variability, respectively. Year‐to‐year variation in active‐layer thickness was minor in Spasskaya Pad compared to Elgeeii. A gamma distribution adequately represented both sites' thaw depth spatial variability as the cumulative probability. Thus, we developed a simple model using the gamma distribution that illustrates the spatial variability in thaw depth at any thawing stage as a function of a given mean thaw depth. A hierarchy of models was introduced that sequentially considered the constant state, linearity, and nonlinearity in the dependence of the rate parameter of the gamma distribution on the mean thaw depth. Although the requirements of the model levels differed between Spasskaya Pad and Elgeeii, the proposed model successfully represented the spatial variability in thaw depth at both sites during different thaw seasons.

Suggested Citation

  • Taro Nakai & Tetsuya Hiyama & Ayumi Kotani & Yoshihiro Iijima & Takeshi Ohta & Trofim C. Maximov, 2023. "Stochastic representation of spatial variability in thaw depth in permafrost boreal forests," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 34(4), pages 481-493, October.
  • Handle: RePEc:wly:perpro:v:34:y:2023:i:4:p:481-493
    DOI: 10.1002/ppp.2204
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