Analysing the morphological features of the drainage basin helps to understand its hydrological characteristics and the association of water, with soil, topography, and vegetation of the catchment. Morphometric analysis reveals the linear, areal, and relief aspects of a drainage basin. In this study, morphometric analysis has been performed using geospatial techniques to evaluate the hydrological characteristics of the Suswa River basin. The SRTM (Shutter Radar Topography Mission) DEM at 30 m resolution has been used to delineate the basin and drainage network in the Arc GIS Software with the help of Spatial Analysis Tools. From this research, we have derived that the basin is having sub-dendritic to dendritic drainage pattern, and the average drainage density of the basin is 2.84 km/km². The elongation ratio of the Suswa River basin is 0.46 which implies that the basin is elongated in shape with moderate relief. This study concludes that morphometric analysis based on GIS & remote sensing techniques is a competent tool for hydrological studies. The present study would be beneficial to various managers and decision-makers for the organization working on watershed management and sustainable natural resources management.

The present study aims to assess slope stability and landslide susceptibility mapping of road-cut slopes along Mussoorie road in the Lesser Himalayan region. A total of 18 suspected unstable slope sites were selected for the investigation, and performed geo-mechanical classification techniques, including Rock Mass Rating (RMR), Slope Mass Rating (SMR), Geological Strength Index (GSI), and kinematic analysis. For the Landslide susceptibility mapping, the Frequency Ratio (FR) method was employed using the weightage of various causative factors which includes slope, aspect, curvature, elevation, distance from streams, distance from lineaments, lithology, and rainfall. The finding indicates that out of 18 selected slopes, 4 slopes are bad slope or unstable, which includes slope 3,4 and 6 in the lower part of the Mussoorie area near Jharipani, while slope 10 near Hathi Paon-Mussoorie Road is also unstable. The slopes around Junu waterfall are stable. Partially unstable slopes may vulnerable to slope failure in the future due to heavy rainfall and unstructured construction. Additionally, the Area Under Curve (AUC) and predictive rate curve values are 61% and 78% respectively, indicating acceptable overall accuracy. This study highlights the landslide issues in Mussoorie region due to rapid urbanization & climate change and demonstrates the effectiveness of the employed methods for future risk analysis.

The occurrence of landslides is a costly and cataclysmic natural hazard that mainly occurs in hilly areas due to factors like earthquakes, cloud burst, extreme rainfall, human pressure, etc. leading to loss of biodiversity, property, and life. Effective and comprehensive landslide risk management is crucial to address landslide susceptibility. Utilizing remote sensing and Geographic Information System (GIS) techniques, this work focuses on the landslide hazard zonation (LHZ) mapping. The study is specifically conducted in the Doon Valley. These advanced technologies help in identifying and categorizing the areas prone to landslides. The Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data at 30 m resolution and Sentinel-2B data at 10 m resolution were used to perform the remote sensing and GIS operations in ArcGIS Software. Thematic layers such as Land Use/Land Cover (LULC), Slope, Geology, Soil Type, Elevation, Drainage Density, Vegetation, and Aspect were produced utilizing remote sensing and GIS data. The weighted overlay, a multi-criteria analysis method, was applied to assign attribute values to each thematic layer based on their importance, which was then combined to calculate the landslide hazard zone. The findings of this study demonstrate that landslides are more likely to occur near and above the Main Boundary Thrust/Fault (MBT). The high to very high hazard zone covers 16.64% of the total area, making landslides occurring more frequently. Additionally, the study found that the Doon Valley rivers’ upper segments are more susceptible to landslides than their lower segments. By integrating Remote Sensing and GIS techniques, it is possible to obtain extensive knowledge of regions prone to landslides. This information will be helpful for decision-makers and planners to reduce the impact of landslides in the near future.

The morphometric analysis of the watersheds is essential for the conservation of natural resources, including soil, water, and vegetation. The Morphometric analysis defines the linear, areal and relief aspects of the watershed. It involves the comprehensive analysis of various factors such as drainage network, surface water flow, and other topographical features. The aim of this study is to develop a sustainable watershed management strategy for the Nayar watershed based on morphometry and Land Use Land Cover (LULC) change dynamics. The Nayar watershed has a total area of 1956.33 km². The multispectral satellite imagery, Digital Elevation Model (DEM) data, and Survey of India (SOI) Toposheets were used for understanding the topographical and morphological characteristics along with the LULC change dynamics. The findings of this research conclude that the Nayar watershed has parallel and dendritic drainage patterns with high relief. According to the LULC change dynamics, the Nayar watershed's area change comprising 57.60 km² and 57.15 km², are from Agricultural Land to Wasteland and from Forest Cover to Wasteland, respectively. This shift in the hilly region will increase the risks of landslides and erosion. Furthermore, the change of 110.03 km² area of Forest Cover to Agricultural Land raises further challenges due to loss of natural vegetation in long run. In summary the change in LULC of Nayar watershed is vulnerable to risk of natural calamities like landslide, erosion. This work would be helpful to many experts and decision-makers for sustainable watershed management and natural resource management.

This study focused on the urban river management using geospatial techniques of the Dehradun Municipal Corporation (DMC) and its associated watersheds of the Bindal River and Rispana River. Shutter Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data with a spatial resolution of 30 m was used for the delineation of watershed boundaries and drainage networks and for identifying topographic features. Additionally, Sentinel-2 data with a spatial resolution of 10 m were utilized to analyze change in land use in 2017 and 2022. The drainage patterns in the Bindal and Rispana watersheds were dendritic in shape with moderate relief. The study found a significant decline in agricultural land from 17.94% in 2017 to 14.66% in 2022. This decline was accompanied by an increase in built-up area from 32.53% to 35.44%. The increased biotic pressure poses a critical threat to river health and biodiversity. This study highlights the urgent need for comprehensive river management strategies to efficiently monitor biotic pressure due to transformations in land use. This research will be beneficial to diverse stakeholders, including decision-makers and urban planners engaged in the sustainable management of water resources and urban development.