Abstract:
Continued pressure on agricultural land, food insecurity, and required adaptation to climate change have made integrated assessment and modelling of future agro-ecosystems development increasingly important. Compound climate extreme events (CEs) can pose significant threats to societies, economies, and ecosystems around the world. When modelling past and future occurrences of CEs, the most suitable tools can result from the interconnectivity of growth models, economic models, and climate models using Geospatial artificial intelligence. Such information, in the form of geographical maps, can be effectively used as climate and weather risk assessment and integrated into future risk analyses, since they will improve the understanding of how CEs respond to near-term climate. GeoAI will also help users deal with regional crop production problems and issues related to CEs and cropping system management under climate change. Cropping system models offer the potential for integrating the physiological understanding of crop characteristics and for examining how potential growth and major limitations to production might vary in different environments and with different management scenarios. GeoAI, crop models, and decision support systems can be useful tools for researchers, teachers, scientists, extension personnel, policymakers, and planners to help and support the application and evaluation of sustainable and long-term alternative management practices.
