Abstract
Based on the results of remote sensing data interpretation, this paper aims to simulate and predict the mountain permafrost distribution changes affected by the mean decadal air temperature (MDAT), from the 1990s to the 2040s, in the Qilian Mountains. A bench-mark map is visually interpreted to acquire a mountain permafrost distribution from the 1990s, based on remote sensing images. Through comparison and estimation, a logistical regression model (LRM) is constructed using the bench-mark map, topographic and land coverage factors and MDAT data from the 1990s. MDAT data from the 2010s to the 2040s are predicted according to survey data from meteorological stations. Using the LRM, MDAT data and the factors, the probabilities (p) of decadal mountain permafrost distribution from the 1990s to the 2040s are simulated and predicted. According to the p value, the permafrost distribution statuses are classified as ‘permafrost probable’ (p > 0.7), ‘permafrost possible’ (0.7 ≥ p ≥ 0.3) and ‘permafrost improbable’ (p < 0.3). From the 1990s to the 2040s, the ‘permafrost probable’ type mainly degrades to that of ‘permafrost possible’, with the total area degenerating from 73.5 × 103 km2 to 66.5 × 103 km2. The ‘permafrost possible’ type mainly degrades to that of ‘permafrost impossible’, with a degradation area of 6.5 × 103 km2, which accounts for 21.3% of the total area. Meanwhile, the accuracy of the simulation results can reach about 90%, which was determined by the validation of the simulation results for the 1990s, 2000s and 2010s based on remote sensing data interpretation results. This research provides a way of understanding the mountain permafrost distribution changes affected by the rising air temperature rising over a long time, and can be used in studies of other mountains with similar topographic and climatic conditions.
Highlights
Permafrost is defined as the ground which remains at or below 0 ◦C for at least two consecutive years [1,2]
Three referencing results are obtained to validate the model simulation results, which are acquired during the 1990s, the 2000s and the 2010s respectively, to correspond to the model simulation results from the 1990s, the 2000s and the 2010s respectively
The referencing results are acquired at a fixed time, whereas the simulation results represent mountain permafrost distribution in a decade
Summary
Permafrost is defined as the ground (including soil, rock, etc.) which remains at or below 0 ◦C for at least two consecutive years [1,2]. The Qilian Mountains is one of the most important regions for distributing mountain permafrost in the Qinghai-Tibet Plateau, even in China. The distribution area of mountain permafrost in the Qilian Mountains has a good potential for gas hydrate prospecting [6]. Mountain permafrost degradation has an important link to natural disasters, such as freezing-dissolving disasters [3]. Given these facts, it is essential to understand and simulate the mountain permafrost degradation status affected by the air temperature in the Qilian Mountains, which has both scientific and economic significance [10]
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