Developing Landslide Hazard Scenario of Kashmir Himalaya from the Historical Events

Kashmir Himalaya being a rugged and tectonically active zone has complex, unstable geology along with steep slopes, creating a favorable environment for landslide hazards, especially along the National Highway (NH-44) that connects the Vale of Kashmir with the rest of India. The historical landslide database for the whole country has not yet been developed and the data provided by various government organizations are often very limited because most of the time local and small-scale landslide events do not get recorded, thus, leading to misinterpretations. The present study focuses on retrieving the information on landslide events and their impacts to develop a comprehensive database for the period from 1990 to 2020 in Jammu and Kashmir, emphasizing Jammu-Srinagar National Highway (NH-44). A hotspot analysis tool (Getis-ord-Gi* algorithm) was used to understand the spatial distribution and concentration of the events throughout the region. The annual and seasonal analysis of the 739 landslide events reported in the valley for the selected period suggests an increasing trend causing 1000 fatalities and 267 injuries. The findings show that out of 20 districts, 16 are relatively more exposed to landslides and the socio-impact induced by landslides was found more along the NH-44 with 303 landslide occurrences reported in 260 days in the past three decades having a high intensity of damage and loss. The results of this study are expected to be of potential use for developing a Landslide Early Warning System (LEWS) and for mitigating the impacts of landslides in the Kashmir Himalaya.

Evaluation of Various DEMs for Quantifying Soil Erosion Under Changing Land Use and Land Cover in the Himalaya

Soil erosion is one of the serious environmental threats in the Himalayas, primarily exacerbated by the steep slopes, active tectonics, deforestation, and land system changes. The Revised Universal Soil Loss Equation was employed to quantify soil erosion from the Vishav watershed in the Kashmir Himalaya, India. Topography and land use/land cover (LULC) are important driving factors for soil erosion. Most often, a Digital Elevation Model (DEM) is used in erosion models without any evaluation and testing which sometimes leads to erroneous estimates of soil erosion. For the best topographic characterization of the watershed, four publicly available DEMs with almost identical resolution (∼30 m), were evaluated. The DEMs were compared with GPS measurements to determine the most reliable among the tested DEMs for soil erosion estimation. Statistical evaluation of the DEMs with GPS data indicated that the CARTO DEM is better with root mean square error (RMSE) of 18.2 m than the other three tested DEMs viz., Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mission (SRTM), and Advanced Land Observing Satellite (ALOS). Slope length and slope steepness factors were computed from the DEMs. Crop cover and management factors were generated from the satellite-derived LULC. Moreover, rainfall data of the nearest stations were used to compute rainfall erosivity and soil erodibility factor was derived from the soil texture data generated from 375 soil samples. The simulated erosion estimates from SRTM, ALOS, and CARTO DEMs showed similar spatial patterns contrary to the ASTER estimates which showed somewhat different patterns and magnitude. The mean erosion in the study area has almost doubled from 2.3 × 106 tons in 1981 to 4.6 × 106 tons in 2019 mainly driven by the anthropogenic LULC changes. The increased soil erosion is due to the degradation of forest cover, urbanization, steep slopes, and land system changes observed during the period. In absence of the observations, the simulated soil erosion was validated with the land degradation map of the watershed which showed a good correspondence. It is hoped that the results from this work would inform policymaking on soil and water conservation measures in the data-scarce mountainous Kashmir Himalaya.