This paper describes the results of a groundwater potentiality and quality assessment conducted in Koduvan Ar sub-watershed of Meenachil river basin, Kottayam district of Kerala state.

The India Remote Sensing data on 1:50,000 scale revealed the occurrence of permanent waterlogging in low-lying flats and depressions of the Indira Gandhi Nahar Pariyojona (IGNP) command area. Such data also indicated seasonal dynamics of waterlogging and soil salinization in irrigated areas.

Crop yield estimation has an important role on economy development and its accuracy and speed influence yield price and helps in deciding the excess or deficit production conditions. The water productivity evaluates the irrigation command through water use efficiency (WUE).

Watershed prioritization has gained importance in natural resources management, especially in the context of watershed management, especially in the context of watershed management. Morphometric analysis has been commonly applied to prioritization of watersheds.

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.

In this study, evaluation of tiger habitat in Corbett Tiger reserve is carried out using remote sensing, ground and other ancillary sources and is integrated using GIS using multi-criteria model.