Land degradation reduces the ability of the land to perform many biophysical and chemical functions. The main aim of this study was to determine the status of land degradation in the Budgam area of Kashmir Himalaya using remote sensing and geographic information system. The satellite data together with other geospatial datasets were used to quantify different categories of land degradation. The results were validated in the field and an accuracy of 85% was observed. Land use/land cover of the study area was determined in order to know the effect of land use on the rate of land degradation. Normalized differential vegetation index (NDVI) and slope of the area were determined using LANDSAT-enhanced thematic mapper plus (ETM+) data, advanced space-borne thermal emission and reflection radiometer, and digital elevation model along with other secondary data were analysed to create various thematic maps, viz., land use/land cover, geology, NDVI and slopes used in modelling land degradation in the Kashmir Himalayan region. The vegetation condition, elevation and land use/land cover information of the area were integrated to assess the land degradation scenario in the area using the ArcGIS ‘Spatial Analyst Module’. The results reveal that about 13.19% of the study area has undergone moderate to high degradation, whereas about 44.12% of the area has undergone slight degradation.

Five watersheds (W1, W2, W3, W4 and W5) in the upper Indus basin were chosen for detailed studies to understand the influences of geomorphology, drainage basin morphometry and vegetation patterns on hydrology. From the morphometric analysis, it is evident that the hydrologic response of these watersheds changes significantly in response to spatial variations in morphometric parameters. Results indicate that W1, W2 and W5 contribute higher surface runoff than W3 and W4. Further, the topographic and land cover analyses reveal that W1, W2 and W5 generate quick runoff that may result in flooding over prolonged rainy spells. A physically based semi-distributed hydrologic model (soil and water assessment tool, SWAT) was used for simulating the hydrological response from the watersheds. As per the simulations, W5 watershed produces the highest runoff of 11.17 mm/year followed by W1 (7.9 mm/year), W2 (6.6 mm/year), W4 (5.33 mm/year) and W3 (4.29 mm/year). Thus, W5 is particularly more vulnerable to flooding during high rain spells followed by W1, W2, W4 and W3, respectively. Synthetic unit hydrograph analysis of the five watersheds also reveals high peak discharge for W5. The simulated results on the hydrological response from the five watersheds are quite in agreement with those of the morphometric, topographic, vegetation and unit hydrograph analyses. Therefore, it is quite evident that these factors have significant impact on the hydrological response from the watersheds and can be used to predict flood peaks, sediment yield and water discharge from the ungauged watersheds.