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

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...

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Bibliographic Details
Published in:Permafrost and Periglacial Processes
Main Authors: Nakai, Taro, Hiyama, Tetsuya, Kotani, Ayumi, Iijima, Yoshihiro, Ohta, Takeshi, Maximov, Trofim C.
Other Authors: Japan Society for the Promotion of Science, Ministry of Education and Science of the Russian Federation, Ministry of Education, Culture, Sports, Science and Technology
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2023
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Online Access:http://dx.doi.org/10.1002/ppp.2204
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ppp.2204
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Summary: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.