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

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

Permafrost and Periglacial Processes, 2023, vol. 34, issue 4, 481-493

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.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/ppp.2204

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:perpro:v:34:y:2023:i:4:p:481-493

Access Statistics for this article

More articles in Permafrost and Periglacial Processes from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().