Assessment of rock glaciers and permafrost distribution in Uttarakhand, India

• Published in: Permafrost and Periglacial Processes
• Main Authors: Baral, Prashant, Haq, Mohd Anul, Yaragal, Shivaprakash
• Other Authors: NIIT University
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2019
• Subjects: permafrost; Permafrost and Periglacial Processes
• Online Access: http://dx.doi.org/10.1002/ppp.2008; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fppp.2008; https://onlinelibrary.wiley.com/doi/pdf/10.1002/ppp.2008; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ppp.2008

Abstract We have compiled an inventory of 1004 rock glaciers for Uttarakhand State, India, using high‐resolution satellite data freely available on Google Earth. The inventory is used to analyze the origin, spatial distribution, geometry and dynamics of rock glaciers using a combination of optical remote sensing techniques with a geographic information system (GIS). Results show that development of rock glaciers in this region depends strongly on high elevation (> 4000 m a.s.l.) and slope aspect. Rock glaciers are more dominant towards the southern quadrant (S, SE, SW) than the northern quadrant (N, NE, NW). A large number ( n = 608) of small (<0.5 km 2 ) rock glaciers originating from glacial moraine indicates glacial retreat in this region as one of the major causes for the formation of such a large number of rock glaciers. Median elevation of intact rock glaciers indicates that climatic conditions above 4600 m a.s.l. are suitable for the existence of permafrost in this region and that the lower limit of discontinuous permafrost gradually increases from west to east. Despite mean annual air temperatures below 0°C, increasing mean temperatures during warmest quarter of the year could be a strong controlling factor for permafrost thawing in the region. Logistic regression modeling using WorldClim version 2 climate data sets and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data show that these models can produce fairly reliable estimates of permafrost probability in the studied area. MODIS LST climate data sets can be crucial for mapping and monitoring permafrost in the region.