Climatic variability and its impact on the indigenous agricultural system using panel data analysis in the Sikkim Himalaya, India

Climate-induced extreme events with fluctuations in climatic indicators like temperature and precipitation highly influence crop productivity. This study deals with quantitative analysis of climatic variability and crop production (1990-2018) using panel data regression analysis. The focus is on variability of three crops, i.e., paddy, maize, and wheat in the Rangit river basin of Sikkim Himalaya, India. Meterological data were acquired from the Indian Meteorological Department, agricultural data from the state agricultural department and a field survey were also conducted with the farmers, using a structured questionnaire, focused group discussion, and key informant observations. The acquired data was analyzed with the help of correlation and multiple linear regression analysis to analyze the relationship between climatic variability and crop production. The result of the study shows that all three crops are dependent on rainfall; however, paddy was the most sensitive to climatic variability. It was found that the overall grain production had an inverse relation to temperature, but it had a positive correlation with rainfall. It was observed that there was a continuous decline in the overall production of paddy and wheat. During deficiency years, it was found that when - 11.33% rainfall was deficient, paddy yield declined by - 1.52%. Further, a deviation of - 13.48% led to a decline of - 54.78% in wheat. The study advocates that timely policy interventions and strategies shall reduce climatic shocks and improve productivity. This would strengthen the livelihood security of the local communities, overcome the challenges of food security, and ensure long-term sustainability of Rangit River basin.