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Drought is one of the major water-related natural hazards. Understanding the spatial and temporal variation of rainfall is of great importance in water resources planning and management as it is related with food security and management of scarce water resource, which becomes critical in case of drought events. The advent of GIS to produce spatially interpolated drought map helps the water managers to undertake appropriate measures in drought relief and prioritization of drought mitigation works. Limitation of literature on Tripura suggests that study of drought over Tripura could help in strengthening of mitigation planes and rationalization of disaster management policies. Hence, the present study is focused to investigate the drought persistence and severity in the Tripura state of India during the period 1980-2013, using Standardized Precipitation Evapotranspiration Index (SPEI). Three time scale i.e., 3, 6 and 12 month time scales were opted for the study. Gridded monthly precipitation data distributed over the four districts of Tripura was used for drought analysis. Significant drought events were detected over the study area during the selected period. Annual analysis of SPI time series showed that the study area received the intense drought during the year 1985. Geospatial technique was used to generate the SPEI drought map for the year 1985.

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India has vast inland water resources having immense potential for aquaculture. Assessment of water quality parameters is a pre-requisite to any scientific intervention as they are of prime importance in fisheries perspective. However, monitoring water quality parameters of such vast area is not an easy task with the conventional tools and methods. In the present study, water quality parameters and chlorophyll pigment concentration were assessed using IRS P-6 remote sensing imagery in the Cauvery watershed of Karnataka State, India. Images captured by optical satellite sensors are often obscured by atmospheric effects. Hence, the images were rectified by Dark pixel subtraction method before analysing data in order to extract useful information from the imagery. The study revealed that there was significant correlation between spectral reflectance and in-situ water quality parameters. Near infra-red band (0.77-0.86 µm), was useful to assess the water quality parameters like depth, specific conductivity, total alkalinity, chlorinity, salinity and turbidity. Similarly, short wave infrared band (1.55-1.70 µm) was useful for assessing chlorophyll-a. However, the models were found to be region specific and they appear to have potential for monitoring water quality of large water bodies at regular intervals.