Remote sensing based agricultural drought assessment in Palar basin of Tamil Nadu state,India

Agricultural drought has been a recurrent phenomenon in many parts of India. Remote sensing plays a vital role in real time monitoring of the agricultural drought conditions over large area, there by effectively supplementing the ground mechanism. Conventional drought monitoring is based on subjective data. The satellite based monitoring such as National Agricultural Drought Assessment and Monitoring System (NADAMS) is based on the crop condition, which is an integrated effect of soil, effective rainfall, weather, etc. Drought causes changes in the external appearance of vegetation, which can clearly be identified (by their changed spectral response) and judged using satellite sensors through the use of vegetation indices. These indices are functions of rate of growth of the plants and are sensitive to the changes of moisture stress in vegetation. The satellite based drought assessment methodology was developed based on relationship obtained between previous year’s Normalised Difference Vegetation Index (NDVI) profiles with corresponding agricultural performance available at district/block level. Palar basin, one of the major river basins in Tamil Nadu state was selected as the study area. The basin covers 3 districts, which contain 44 blocks. Wide Image Field Sensor (WiFS) of 188m spatial resolution from Indian Remote Sensing Satellite (IRS) data was used for the analysis. Satellite based vegetation index NDVI, was generated for Samba and Navarai seasons in the years 1998 and 1999. An attempt has been made to estimate the area under paddy. It was also observed that, there was reduction in the crop area as well as vigour in the vegetation in both Samba and Navarai seasons in 1999 when compared with 1998. Drought severity maps were prepared in GIS environment giving blockwise agricultural water deficiency status.     

Evaluation of indicators for desertification risk assessment in part of Thar Desert Region of Rajasthan using geospatial techniques

Desertification has emerged as a major economic, social and environmental problem in the western part of India. The best way of dealing with desertification is to take appropriate measures to arrest land degradation, especially in areas prone to desertification. This requires an early warning system for desertification based on scientific inputs. Hence, in the present study, an attempt has been made to develop a comprehensive model for the assessment of desertification risk in the Jodhpur district of Rajasthan, India, using 23 desertification indicators. Indicators including soil, climate, vegetation and socio-economic parameters were integrated into a GIS environment to get environmental sensitive areas (ESAs) to desertification. Desertification risk index (DRI) was calculated based on ESAs to desertification, the degree of land degradation and significant desertification indicators obtained from the stepwise multiple regression model. DRI was validated by using independent indicators such as soil organic matter content and cation exchange capacity. Multiple regression analysis shows that 16 indicators out of 23 were found to be significant for assessing desertification risk at a 99% confidence interval with \(R^{2}=0.83\). The proposed methodology provides a series of effective indicators that would help to identify where desertification is a current or potential problem, and what could be the actions to alleviate the problem over time.