Impact of Climate Change on Crop Production and Its Consequences on Human Health

Abstract

Climate change and water availability directly impact the agricultural practices around the globe. Humans are dependent on agriculture for their food needs. Changing climatic conditions like the delayed onset of monsoon, less rainfall, and increasing temperature are profoundly impacting agriculture practices. Therefore, this has a direct or indirect impact on human health. According to FAO, only 12% of global land is available for crop production and that too is not increasing proportionately with the continuously increasing world population. Climatic stresses may cause insufficiency to food security. Hence, this type of study is quite significant for decision making. In the Indian scenario, approximately 61% of the total net sown area is rainfed. In this huge proportion of rainfed areas, there are many types of changing climatic conditions that impact crop productivity. Geoinformation science-based big data encompasses enormous opportunities for addressing issues like climate modeling, its impact on crops, and production alteration. This chapter discusses the real-world problems, their impacts as well as the way forward for sustainable solutions by utilizing the strength of remote sensing big data. Here, time series analysis, machine learning-based predictive multivariate modeling approaches have been exploited to detect the climatic impact on crop production for rice and cotton crops of the highest productive districts of Maharashtra state. After delineation of climatic implications on agriculture, its consequences on human health issues have been discussed. The ML-driven partial least squares regression (PLSR) technique was proved better over other investigated techniques. The results of this study illustrate that with the rise in temperature and rainfall during 2050, cotton production is projected to decline by 1–35%, whereas rice production looks to be increased by 0.4–20% by nullifying high temperature with excess rainfall except for one district.