Altitude plays a crucial role in determining habitat distribution, species diversity, and ecological resources, which support livelihoods and employment in the Himalayan region. Covering 18% of India's territory, the Himalayas house over 50% of the country's forest cover and 40% of the Indian subcontinent's endemic species, providing ecosystem services to 115 million people. However, the relationships between elevation, ecological services, and population resource dependency are poorly understood. This study examines the spatial linkages between elevation, climate, and ecosystem distribution, as well as the relationship between ecosystem services and population density using livelihood indicators. Spatial analysis reveals an inverse relationship between population density and relative relief (-0.69; P<0.05). Population density is concentrated (14.44%) along the fertile Alaknanda and Bhagirathi River valleys (900–2200m), which cover 14.95% of the area. Conversely, 5.33% of the population is scattered across 41% of the region, with higher elevations (>2000m) relying on non-timber forest products (NTFPs) for over 30% of income. These findings highlight critical patterns in population distribution, resource dependency, and ecosystem services, offering valuable insights for policymakers to promote biodiversity conservation, equitable resource sharing, and sustainable development in the Himalayan region.

Climate is a natural process that influences weather patterns across different regions.  The term average climate refers to the typical weather conditions observed in a specific area over a long period. In India, agriculture is largely dependent on rainfall and variations in climatic factors significantly impacting the crop production. This study analyzes climate trends in the agro-climatic zones of Satara district using data procured from NASA’s Prediction of Worldwide Energy Resources (POWER) (1984-2022). The study examines key climatic parameters, including annual rainfall, maximum and minimum temperatures, relative humidity, soil wetness and soil moisture. To assess climate trends using various statistical methods such as the non-parametric Mann-Kendall test, Sen’s slope estimator and linear regression were applied. The results indicate notable fluctuations in climatic factors over the past four decades. The ghat zone covering areas like Mahabaleshwar, Wai, and Patan has recorded the highest rainfall and lowest temperatures. In contrast, the scarcity zone, including Man, Khatav, and Khandala tehsils, has experienced lower rainfall and a rise in annual maximum temperatures. These findings suggest that the agro-climatic zones of Satara district are continuously influenced by changing climatic conditions. Understanding these trends is crucial for farmers, local administrators, researchers, and policymakers to develop effective agricultural and environmental management strategies.

The Gumbel Extreme Value Type-I (GEVI) probability distribution is applied to investigate magnitude and frequency of floods on the Kaveri River using Annual Maximum Series data for 17 to 47 years. The GEVI is used for future probabilities of occurrences of floods and to estimate the recurrence interval of average annual peak discharges (\(\bar{Q}\)), large floods (Qlf) and actually observed maximum annual peak discharges (Qmax). The discharges have been estimated for 2-yr, 5-yr, 10-yr, 25-yr, 50-yr, 100-yr, 500-yr and 1000-yr floods that range from 9 to 10408 m³s^-1. As per GEVI, the   has a recurrence interval of 2.33 years, Qlf has 6.93 years. However, recurrence interval of Qmax range between 36 and 636 years. The curves portrayed on GEVI probability paper provide dependable estimates of floods. The GEVI probability distribution, therefore, can be reliably and conveniently used to estimate the recurrence intervals for given magnitude and vice versa.

Soil profile studies especially identification of different soil layers is a vital component in soil survey. The present study was undertaken to assess the applicability of ground penetrating radar (GPR), a widely adopted geophysical technique and instrument for soil profile studies under different landforms (piedmont and alluvial plain) located in the Indo-Gangetic Plain region in Saharanpur district of Uttar Pradesh. GPR survey was conducted using dual frequency antennas (200 and 600 Mhz) at specific locations corresponding to landforms of piedmont and alluvial plain along transect. The radargrams generated by standard processing of ground scan data showed widely varying patterns in both the landforms, corresponding to the variations in soil layer distribution. From the radargrams generated, a clear distinction could be made between the soils of piedmont as well as alluvial plain. The radargram of alluvial plain showed very smooth transition between soil layers whereas in case of piedmont plain, the profile appears to be discontinuous as well as irregular. The soils of alluvial plain showed clear/distinct soil layer distribution till nearly 75cm depth in contrast to the piedmont soils which exhibited parabola patterns in radargram indicating the presence of stones/boulders within very short depth from the surface. The results regarding identification of contrasting soil layers using GPR were validated and found to be in agreement with standard soil profile information of the sampling sites in different landforms. GPR being a non-destructive technique could help in acquiring large number of such observations in much lesser time providing vital information for land use planning as well as soil mapping activities.