Supraglacial debris (SGD) cover on mountain glaciers is known to greatly influence various glacier processes and alter their response to climate change. In this study, vital glacier parameters of five glaciers with varying debris coverage (about 7–26%), located in Zanskar basin, Ladakh Himalaya, were monitored using Landsat imagery (from 1977 to 2013) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM). Results reveal how varying amounts of SGD induce categorically distinct responses on glaciers, sharing same geographical settings. The clean glaciers (CG) in the area were found to have higher retreat rates (about 8–19 m year⁻¹), comparable areal shrinkage (about 13–15%), higher accumulation area ratios (AARs) (>0.5), rapid increase in SGD (about 1.6–3.0-fold), and association with increasing numbers of peri- and proglacial lakes (2–8 per glacier). The debris-covered glaciers (DCG) showed minimal frontal changes (about 2–5 m year⁻¹), higher areal shrinkage (about 14–21%), low AARs (<0.5), slow SGD changes (about ≤1.2-fold), and association with increasing numbers of peri- and supraglacial lakes (SGLs) (2–39 per glacier). Moreover, while changes in SGD had a strong negative correlation with changes in glacier area, retreat rates, and AAR, they were positively related with increase in area of SGLs.

Remote sensing science has proven fruitful for land surface temperature (LST) determination contrary to other techniques used especially for the rugged terrain like the Himalayan mountain system. In this study, an attempt has been made to estimate the land surface temperature in parts of Chenab basin, Jammu & Kashmir, by using Landsat-7 ETM+, TM, and Terra ASTER satellite data. The current study basically utilizes different surface temperature estimation techniques i.e. Reference Channel Method (RCM), Emissivity Normalization Method (ENM), Classification based and Stefan Boltzmann’s approach to inter-compare various temperature estimation techniques and to examine the influence of the difference in sensor characteristics on the estimated surface temperature on a glacier terrain. For the effect of spatial resolution variation in the determined (LST) values for ETM+ and TM was estimated and for radiometric resolution, effect comparison was carried between the ETM+ and ASTER-derived LST image. Furthermore, an effect of spatial resolution has been quantified and has been evaluated successfully due to the fact that two sensors used for the purpose did not differ much in their characteristics features.

The current study was carried out to monitor the changing land use/cover and assess the impact of solid waste on water quality of Dal Lake in Srinagar city (India). Various data sets were used for analysis of geomorphology studies such as socio-economic changes and water quality status. The study reveals that agriculture land decreased from 13 to 11.39%, forests from 2.55 to 1.41%, water from 22.05 to 19.85%, and plantation from 22.28 to 14.65%. Although the study also reveals there has been an increase in built-up from 8.87 to 23.90%, aquatic vegetation increased from 10.25 to 17.03%. Finally, changes in all categories were correlated and it was found that the wards surrounding the Dal Lake show the dynamic change in land use/cover and solid waste parameters which in turn changed the water quality of Dal Lake. It was observed that solid waste generated varies from ward to ward depending upon land use cover and socio-economics. In order to protect the lake basin, controlled human activities, land use and water resources within the catchments are to be done in cooperation between the government departments, local authorities and the general local community around Dal Lake catchment.

LST variability in a region is significantly impacted by changes in LULC. The current study makes use of satellite data to examine the historical link between LULC and LST in Kashmir Valley. Using the Mono-window algorithm method, the study area has seen substantial changes in LST owing to the conversion of various LULC classes. Results reveal that in LULC agriculture has been transformed to horticulture and built up area with around 80% of the area of Kashmir valley seeing a consequent shift in LST patterns from low category of LST to medium and high category LST. These rapid changes can mainly be attributed to changing economic structure, population growth, the resultant increase in settlements and infrastructure activities, and vegetation dynamics. Strong policy measures are needed to mitigate the impacts of rapid land system changes on the environment keeping in view the sensitivity of the mountainous Kashmir Himalayan region.

Forecasting groundwater levels is vital for the sustainable management of aquifers. In this study, we explore the application of two ARIMA models (Damped Holt Model - 0,1,2 and Basic exponential smoothing - 0,1,1) to predict pre- and post-monsoon depth to water level (m,bgl) in observation wells located in Jammu Himalaya from 2015 to 2034. Historical data spanning 1994 to 2014 is used to develop the model, and validation is performed using data from 2009 to 2014. The model development process comprises four crucial steps: model selection, diagnostics, validation, and prediction. By evaluating the residuals from the autocorrelation function (ACF) and partial autocorrelation function (PACF), we determine the best-fit ARIMA model with the lowest AIC values. The selected ARIMA model (0,1,1) is further validated through a close comparison of the predicted and actual pre- and post-monsoon depth to water level (m,bgl) values from 2009 to 2014, yielding a high level of agreement based on R2 values. The forecasted results indicate a decline in groundwater levels, with depths anticipated to reach 8.4 (m,bgl) during the premonsoon season and 6.6 (m,bgl) during the post-monsoon season from 2015 to 2034. With the reliability of these forecasting methods, our study provides valuable insights for the sustainable management of groundwater resources, supporting informed decision-making to ensure their optimal and responsible utilization.