Permafrost model in coarse-blocky deposits for the Dry Andes, Argentina (28°-33° S)

C Tapia-Baldis,D Trombotto-Liaudat

doi:10.18172/cig.3802

Abstract

In this work, a statistical permafrost distribution model for coarse-blocky deposits in the Dry Andes of Argentina (28-33°S) is presented. The empiric mathematical formulation was based on a logistic regression. The final model is a combination of two independent occurrence probability models: a) a mean annual air temperature-terrain ruggedness model and, b) a mean annual air temperature-potential incoming solar radiation model. For all cases, calibration was made according the complete geomorphological characterization of a periglacial basin with 250 km2. Lately, the results of probabilistic model were extrapolated to the whole study area in the Dry Andes and compared with the Argentine rock glacier inventory data base. High permafrost likelihood, in coarse debris, is expected above 4200 and 5700 m a.s.l., from south to north in the study area and covers a surface of approximately 1200 km2. Medium permafrost likelihood is expected above 3400 and 4200 m a.s.l. with a surface of 6178 km2 while low permafrost likelihood, occurs between 3000 and 3400 m a.s.l. with an area of 11.060 km2. These findings indicate that permafrost may occur in several types of coarse-blocky deposits in the Dry Andes, not only restricted to rock glaciers. Thermal properties of the ground in coarse-blocky deposits allow permafrost permanence, even under unfavourable climatic conditions.The performance of the permafrost model was also tested, considering the transition from cold paleoclimate Tardiglacial to present climatic conditions. During the warming, likely permafrost surface reduced from 56 to 13%. In the same way, rock glaciers with high and medium permafrost likelihood decrease from 62 to 30%, respectively while, rock glaciers with low likelihood and no permafrost category, increased 75% and 474%, respectively. Moreover, we identified some sites in which permafrost degradation is arguably expected. About that, 0.9% of the rock glaciers in the study area display possible permafrost degradation and 33% of them, likely permafrost degradation.

Highlights

The Dry Andes of Argentina contain extensive areas currently with permafrost condition
Medium permafrost likelihood is expected above 3400 and 4200 m a.s.l. with a surface of 6178 km2 while low permafrost likelihood, occurs between 3000 and 3400 m a.s.l. with an area of 11.060 km2. These findings indicate that permafrost may occur in several types of coarseblocky deposits in the Dry Andes, restricted to rock glaciers
Ésper Angillieri (2017) calculated the permafrost extension for the study area, using an empiric statistical model with rock glaciers as predictive variable. This model displays a surface for high permafrost likelihood of 10.700 km2, much higher than the 1200 km2 calculated in this work

Summary

Introduction

The Dry Andes of Argentina contain extensive areas currently with permafrost condition. Rock glaciers are widely used as mountain and Andean permafrost indicators (Haeberli, 1985; Barsch, 1996; Humlum, 1996; Trombotto, 2000; Harris et al, 2009; Haeberli et al, 2010; Saito et al, 2016). Rock glaciers are mesoscale landforms built-up by masses of rock fragments and finer material that, if active, move down slope by influence of gravity through a creeping mechanism, involving ground ice deformation (Barsch, 1996; Trombotto et al, 2014). According to the recently published Argentine rock glacier inventory (IANIGLA, 2017), more than 600 km of national territory is occupied by active and inactive rock glaciers (6846 landforms >1 km2), both indicating old or current creeping permafrost conditions. Rock glacier surface alone underestimates the real extension of permafrost in cold high-mountain environments. Mountain permafrost can be found below several surface-types: under perennial snow covers, in steep bedrock, fine or coarse talus slopes or deposits, or in valley bottoms (Boeckli et al, 2012; Scherler, 2014)

Methods

Results

Conclusion