ASSESSMENT AND MITIGATION OF AGRICULTURAL VULNERABILITY IN INDIA USING GLOBAL DATASETS

Kaushalya Ramachandran, Shubhasmita Sahani, D.V.S.Sarma, V. Praveen Kumar

Abstract: Global datasets of NDVI data products obtained from NOAA-AVHRR and MODIS-TERRA (1982-2012) satellites were used to assess agricultural vulnerability in India for which a methodology was developed. Use of bio-physical indicators like NDVI to assess agricultural vulnerability adds a new dimension to this field of research dominated by socio-economic analysis. Timeseries vegetation index data from NOAA- AVHRR and MODIS - TERRA satellites (1982 to 2012) provided a valuable insight into the slow and imperceptible impact of climate change on variations in length-of-crop-growing-period, cropping pattern and agricultural production systems besides changes in vegetation cover, land use and on agricultural sustainability in rainfed regions where millions of small and marginal farmers subsist on small holdings. A study was carried out using tools and techniques of Geo-informatics that formed the basis for a comprehensive assessment of agricultural vulnerability in India to assess the sensitivity of agricultural systems, its exposure to climate hazards and to ascertain the adaptive capacity of farmers to withstand climatic stresses. Till date there are no comprehensive studies reporting the use of bio-physical indicator like vegetation index and tools of geo-informatics to assess agricultural vulnerability. Hence this study is unique as it has for the first time indicated that of the 74 million ha (Mha) under agriculture in 122 districts in India, over 47 Mha of Net Sown Area was vulnerable to climate change. Coarse AVHRR NDVI dataset indicated that over 29 Mha of Net Sown Area, an underestimation due to difficulty in classifying mixed pixels at coarse resolution. Notwithstanding variations in the spatial extent estimated, it is notable that nearly 1/5th to 1/3rd of Net Sown Area in India out of a total of 142 Mha was vulnerable to climate change. Rainwater harvesting and its use for supplementing irrigation through watershed projects have shown promise and could help in improving adaptive capacity of farmers. Information on spatial extent of agricultural vulnerability and types of hazards impacting agriculture could help in prioritizing and targeting implementation of development projects for agriculture. Free access to global datasets and open-source GIS has facilitated this study. Finer resolution datasets could greatly improve accuracy of estimation of agricultural vulnerability in India and elsewhere.

Keywords: Geo-informatics, agricultural vulnerability, climate change, NDVI, LGP, watershed development program

DOI: https://doi.org/10.15623/ijret.2015.0423001