ICARDA Scientists Study the Impact of Climate Change on Crop Production and Its Consequences on Human Health

Published Date
October 26, 2021
Published by
ICARDA Communication Team
Remote sensing plays a crucial role in providing weather parameters for future accurate predictions and decisions.
Remote sensing plays a crucial role in providing weather parameters for future accurate predictions and decisions.

Around the world, especially in dry areas, agricultural practices are affected by climate change and water availability. The shift in rainfall patterns, growing seasons, and extreme temperatures, sometimes occurring altogether, significantly impacts farming and yield production, with brutal consequences on human health resulting from food insecurity and lower income for rural communities. To strengthen the resilience of farmers affected by climate change, ICARDA studies the patterns and trends of these climatic changes. 

Recent research by ICARDA scientists and national partners published in Springer Link outlines the Impact of Climate Change on Crop Production and Its Consequences on Human Health. The team used geoinformatics science-based big data and machine learning to quantify the impact of climate change on crops and production.   

One case study assessed the impact of climate change on the production of cotton and rice crops grown in the Kharif (monsoon) season in Maharashtra state in India. The results of this study illustrate that with the rise in temperature and rainfall expected by 2050, cotton production is projected to decline by 1–35%, whereas rice production will increase by 0.4–20%. Both outcomes are caused by high temperatures with excess rainfall, except for in one district. 

The study concludes that spatio-temporal (belonging to both space and time) trends are effective in understanding the implications of climate change on crop production, allowing time for farmers and governments to adapt in advance. The study also demonstrates the power of providing accurate outcomes and modeling, through remote sensing and machine learning, in order to provide a vital contribution to the development of high-throughput and climate-resilient crop varieties. 

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