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

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...

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Bibliographic Details
Published in:Permafrost and periglacial processes 2023-10, Vol.34 (4), p.481-493
Main Authors: Nakai, Taro, Hiyama, Tetsuya, Kotani, Ayumi, Iijima, Yoshihiro, Ohta, Takeshi, Maximov, Trofim C.
Format: Article
Language:English
Subjects:
Boreal forests
Depth
Distribution
Interannual variability
Modelling
Nonlinear systems
Nonlinearity
Permafrost
Probability distribution functions
Probability theory
Representations
Seasonal variability
Spatial variability
Spatial variations
Statistical analysis
Stochasticity
Thawing
Thickness
Variability
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Summary: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.
ISSN:1045-6740
1099-1530
DOI:10.1002/ppp.2204