Forewarning Model for Glacial Lake Outburst in Southeast Tibet

Abstract

The southeast region of Tibet experiences frequent glacial lake outburst disasters, and disaster warning systems are thus crucial for disaster prevention and mitigation in the area. In this study, based on remote sensing images and historical data, 20 glacial lakes in southeast Tibet were selected as samples for risk analysis. A probability model of glacial lake outburst floods (GLOFs) in southeast Tibet was established using logistic regression for seven selected prediction indexes. By calculating the sensitivity and specificity of the model, the probability of identifying GLOFs was found to be 60%, with an identification degree of 86%. The under the ROC (receiver operating characteristic) curve index was prominently larger than 0.5, indicating the applicability of logistic regression for predicting GLOFs in southeast Tibet. The probability equation of the model shows that the area of the glacial lake, the distance of the glacial lake from the glacier, the slope of the glacier, the slope of the glacier tongue, and the dam backwater slope have a great influence on the probability of GLOFs. The results can provide a reference for the local governments to prevent disasters and reduce the damage of GLOFs.