Climatic change-induced glacier recession has been accompanied by formation and growth of proglacial lakes in the Himalayan region, which pose an emerging significant threat to the downstream communities/settlements in the form of outburst floods. To understand spatiotemporal evolution patterns, sources and driving mechanism of formation and expansion of glacial lakes, a temporal inventory of glacial lakes (area > 2000 m²) in Chandra basin has been developed from 2000 to 2014 using IRS LISS-III images. From 2000 to 2014, the total number of glacial lakes in Chandra basin increased from 28 to 46 and area expanded from 1.91 ± 0.24 km² to 3.26 ± 0.24 km². Glacier recession and increased glacier melt runoff due to climate warming led to the formation and expansion of glacial lakes in space vacated by glacier recession. The increase in number and area of ice-dammed lakes at higher elevations confirms the continued glacier retreat in the basin. Lakes in contact or in the proximity of the mother glacier exhibit higher growth and formation rate. The accelerated growth of glacial lakes has resulted in increased hazard and damage potential of glacial lake outburst floods in Chandra basin. Seven potentially dangerous lakes are identified and analysed qualitatively for outburst probability.

Landslide susceptibility mapping is a crucial step in comprehensive landslide risk management. The purpose of the present study is to analyze the landslide susceptibility of Mandi district, Himachal Pradesh, India, based on optimum feature selection and hybrid integration of the Shannon entropy (SE) model with random forest (RF) and support vector machine (SVM) models. An inventory of 1723 rainfall-induced landslides was generated and randomly selected for training (1199; 70%) and validation (524; 30%) purposes. A set of 14 relevant factors was selected and checked for multicollinearity. These factors were first ranked using Information Gain and Chi-square feature ranking algorithms. Furthermore, Wilcoxon Signed Rank Test and One-Sample T-Test were applied to check their statistical significance. An optimum subset of 11 landslide causative factors was then used for generating landslide susceptibility maps (LSM) using hybrid SE-RF and SE-SVM models. These LSM’s were validated and compared using receiver operating characteristic (ROC) curves and performance matrices. The SE-RF performed better with training and validation accuracies of 96.93% and 88.94%, respectively, compared with the SE-SVM model with training and validation accuracies of 94.05% and 82.4%, respectively. The prediction matrices also confirmed that the SE-RF model is better and is recommended for the landslide susceptibility analysis of similar mountainous regions worldwide.

Glacial lakes are forming and evolving in the high-mountain regions as a result of glacier recession induced by global climate change. To provide comprehensive information about the spatial distribution and temporal changes of glacial lakes an updated detailed inventory has been developed in a study area of 7300 km² for four subbasins of the northwestern Himalaya for 1971, 2003, and 2011 using Corona, ASTER, and IRS-R2 data. In total, 77, 133, and 154 glacial lakes larger than 1000 m² covered areas of 1.9, 3.4, and 4.3 km² in 1971, 2003, and 2011, respectively. The majority of the lakes (75%) are glacier-fed and exhibit a significant expansion trend as compared to stable nonglacier-fed lakes. Around 75% of the lakes have surface drainage and excess water from precipitation is drained off, hence we conclude that glacier meltwater and vacated space due to glacier recession dominates the expansion and formation of lakes in the region. In addition, the formation of new lakes at higher altitude and the growth of glacier-fed lakes correspond well with the glacier recession. The study presents a comprehensive database of glacial lakes for long-term monitoring, outburst flood hazard assessment, and water resource management in the northwestern Himalaya.