Mass wasting and tectonic uplift are the major factors, responsible for reshaping the northern Pakistan that contains the world's most steeply inclined mountainous regions including: Karakoram, Himalayas, and Hindukush Ranges. The role of GIS and remote sensing is inevitable to study the river geomorphology for the identification and evaluation of different mass wasting processes. digital elevation models (DEMs) are frequently used to extract the longitudinal profile of the rivers to identify the knickpoints and their related geomorphic attributes. For this study, ASTER DEM of 30 m spatial resolution satellite data was utilized to perform the geomorphological analysis of the longitudinal profile of the Hunza River in ArcGIS and Matlab environment. The Hunza River channel with having the watershed area of 13571 km 2 , has witnessed a number of historic landslide dams (i.e. Attabad, Ganesh and Boultar glacier, etc.) that blocked the main river channel at multiple sections in different episodes of time. These past landslides presumably preserved in the river channel as knickpoints at their respective locations. In this study, a total of 77 knickpoints were identified along the main stem of the river channel. The spatial locations of the extracted knickpoints and their normalized steepness index (ks) values were compared with the Hunza River landslide inventory map, lithologic contact, tectonic faults and historic landslides data. Furthermore, the likely role of these geomorphic factors was evaluated to ascertain their association with knickpoints formation. The results of this GIS-based geomorphic analysis of the river profile and subsequent field visit of the area revealed that the formation of landslide dams and their subsequent breaching is one of the major trigger factor of knickpoints along the channel. Such studies highlight the benefits of inexpensive remote sensing data and GIS tools to assess the likely role of various geomorphic features in the formation of significant knickpoints along the river profiles on a regional scale.
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