Permafrost Favorability Index: Spatial Modeling in the French Alps Using a Rock Glacier Inventory

Frontiers in Digital Humanities

Brenning, Alexander¹  Charvet, Raphale²  Gottardi, Frdric³  Marcer, Marco⁵  Schoeneich, Philippe⁶  Bodin, Xavier⁸ 

[1] Grenoble Alpes, France;Savoie Mont Blanc, France;Department of Geography, Friedrich Schiller University Jena, Germany;EDF-DTG, France;Institut de GéLaboratoire EDYTEM, Centre National de la Recherche Scientifique, UniversitéService RTM, Office National de Forets, France;ographie Alpine, Université

关键词: Permafrost modelling;    French Alps;    Mountain permafrost;    Rock glaciers;    Statistical Modelling;   

DOI  :  10.3389/feart.2017.00105

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

In the present study we used the first rock glacier inventory for the entire French Alps to model spatial permafrost distribution in the region. The inventory, which does not originally belong to this study, was revised by the authors in order to obtain a database suitable for statistical modelling. Climatic and topographic data evaluated at the rock glacier locations were used as predictor variables in a Generalized Linear Model. Model performances are strong, suggesting that, in agreement with several previous studies, this methodology is able to model accurately rock glacier distribution. A methodology to estimate model uncertainties is proposed, revealing that the subjectivity in the interpretation of rock glacier activity and contours may substantially bias the model. The model highlights a North-South trend in the regional pattern of permafrost distribution which is attributed to the climatic influences of the Atlantic and Mediterranean climates. Further analysis suggest that lower amounts of precipitation in the early winter and a thinner snow cover, as typically found in the Mediterranean area, could contribute to the existence of permafrost at higher temperatures compared to the Northern Alps. A comparison with the Alpine Permafrost Index Map (APIM) shows no major differences with our model, highlighting the very good predictive power of the APIM despite its tendency to slightly overestimate permafrost extension with respect to our database. The use of rock glaciers as indicators of permafrost existence despite their time response to climate change is discussed and an interpretation key is proposed in order to ensure the proper use of the model for research as well as for operational purposes.

【 授权许可】

CC BY