Modeling the Impact of Climate Change on the Productivity of the Agrarian Sector

Abstract

The article proposes a conceptual approach to modeling the impact of climate change on the productivity of the agrarian sector, substantiates the factors of climate change, and forms the information base of the study. Specifically, rainfall data was taken from the Climate Hazards Group InfraRed Precipitation with Station database (CHIRPS), which is a quasi-global dataset of precipitation amounts over 30+ years. CHIRPS incorporates 0.05° resolution satellite imagery together with data from local stations to create gridded rainfall time series to analyze trends and monitor seasonal drought. In order to obtain rainfall data for each of the selected countries, the Large-Scale International Borders (LSIB) database was used. This data is taken from two other datasets: the LSIB Lines Vector File and the World Vector Shoreline (WVS) from the National Geospatial-Intelligence Agency (NGA). Additional precipitation information was obtained using the Google Earth Engine after performing procedures with a sample of geolocation data for each country, obtaining actual precipitation data for the observation period, exporting the data and processing them to bring the results to the annual figure. The formed information base on the factors of climate change has allowed to develop models of productivity of grain production in the countries that are the largest wheat producers in the world. The results of the development of models led to the conclusion that climate change affects crop yields in countries that are leading producers of cereals. The obtained results can be used to predict changes in yield and production depending on climatic parameters such as temperature and precipitation, as well as to determine the optimal and extreme values of climatic factors.

Keywords

• climate change
• agrarian sector
• productivity