Large areas of Himalayas covered with seasonal snow during winter are rapidly changing during summer, significantly affects the stream flow of many rivers originating from Himalayas.

Hydrological modelling of large river catchments is a challenging task for water resources engineers due to its complexity in collecting and handling of both spatial and non-spatial data such as rainfall, gauge discharges, and topographic parameters.

Remotely sensed data can provide useful information in understanding the distribution of groundwater, an important source of water supply throughout the world. In the present study, the modern geomatic technologies, namely remote sensing and GIS were used in the identification of groundwater potential zones in the Kanyakumari and Nambiyar basins of Tamil Nadu in India.

Markov chains have been used to model spatial changes in a variety of spheres. Changes in social situations, economic standards, natural resource availability, and even weather conditions have been explored and predicted using Markov Random Function (MRF) and Markov Random Chains (MRC).

Over the last four decades exploitation of natural resources to meet increasing societal demands for land based products has caused significant changes in land use and land cover not only in nature's best gifted regions but also environmentally sensitive arid regions.

Land use and land cover changes due to human activities in a time sequence. Detection of such changes may help decision makers and planners to understand the factors in land use and land cover change in order to take effective and useful measures. Remote sensing and GIS techniques may be used as efficient tools to detect and assess land use change.

Planning based on agro-ecological zoning aims at scientific management of regional resources to meet the food, fibre, fodder and fuel wood requirements without adversely affecting the status of natural resources and environment.

The planning of conservation measures to conserve water and soil resources taking hydrological planning unit as micro-watershed is considered to be effective.

Involving local communities is a prerequisite to sustainable disaster risk reduction. Local communities are both the primary victims and the first to respond to emergencies when disasters strike. Nobody is more interested in reducing disaster risk than the community whose survival and well-being is at stake.