Analysis of Seasonal Precipitation, Potential Evapotranspiration, Aridity, Future Precipitation Anomaly and Major Crops at District Level of India

Abstract

Climate-induced risks are very significant in these days and will impact the agriculture crop production because of the change in hydro-climatic condition. Remote sensing and GIS framework provide scientific understanding in practical application systems with the sustainable solution in new climate change reality and support significantly in resilience to mitigate the future risk. The paper deals with long-term (1970–2000) monthly thematic datasets and analyzed the seasonal (kharif, rabi and zaid) pattern of precipitation, potential evapotranspiration and aridity index to scale of district level of India. Additionally, we have used the predicted (2025) monthly precipitation anomalies data (climate change scenario) to examine the seasonal precipitation pattern at the district level of India. The major agriculture crops (rice, wheat, and maize) for the year 2005 were also evaluated during those seasons. Such analysis gives better understanding and knowledge of district-wise seasonal spatial pattern at country level (India) of climate stress, crop water demand and suitably applied to make strategies/ synergic approach toward agriculture resilience. The long-term seasonal aridity index pattern analysis varies significantly throughout India during kharif, rabi and zaid seasons which were manifested by cropping pattern adopted by farmers as per land potentiality. Several districts in some of the states of India receive adequate precipitation during kharif season and manifest low aridity index in rabi and zaid season which can be recommended for rainwater conservation at the watershed level to boost the agriculture crop production. Farmer’s suicide hot spot districts in the arid and semiarid regions need policy intervention to develop a concrete plan including integrated watershed management strategies with traditional ecological knowledge for long-term sustainable management for climate resilience because these districts showed significantly low aridity index value in all seasons. The remote sensing and GIS-based evaluation/results of this study in conjugation with in situ ancillary datasets will support significantly to address the climate-induced risk of farmers to achieve sustainability in food security, enhancing the livelihood, eradication of poverty and magnifying the farm household resilience.