Reviewed by Danielle Ellis, B.Sc.Sep 19 2024
Researchers from the University of Sharjah have created new artificial intelligence algorithms that can virtually forecast future drought conditions. Their study, published in the journal Scientific Reports, demonstrates the significant benefits of employing AI models instead of traditional drought indicators for forecasting the origins and severity of conditions that result in a water shortage and rain.
The results were promising. The AI models were able to predict future drought conditions with high accuracy. The AI models demonstrated strong correlations with multiple drought indicators and consistently outperformed existing indices.
Dr. Mohamed Abdallah, Associate Professor and Study Lead Author, University of Sharjah
The research is important because it can help officials monitor the drought and develop appropriate reaction plans. By integrating artificial intelligence, the authors provide more accurate drought projections than those previously accessible.
The authors blame changing hydroclimatic conditions and the complexity of the phenomena for the lack of accurate drought forecasts.
They said, “As a result of the inherent complexity of drought phenomena and hydroclimatic condition differences, no universal drought index is available for effectively monitoring drought across the world. Therefore, this study aimed to develop a new meteorological drought index to describe and forecast drought based on various artificial intelligence (AI) models.”
The authors emphasize the limitations of conventional drought indexes in their study. They used historical climatic data and soil moisture levels to train multiple advanced artificial intelligence (AI) models to uncover these shortcomings and improve the accuracy of drought predictions.
“We compared the developed AI-based indices with multiple conventional drought indices based on their correlations with various drought indicators. Our AI models proved to be particularly efficient in capturing extreme climatic changes, with enhanced forecasting accuracy,” said Dr. Abdallah.
This capability is vital in regions where increasing water scarcity and more severe climatic fluctuations pose significant challenges. Our AI models can help in planning water resources more efficiently and mitigating the impacts of droughts on ecosystems. Implementing this data-driven approach is especially important as it allows for better adaptation to the challenges posed by climate change, particularly in regions most susceptible to its effects.
Dr. Mohamed Abdallah, Associate Professor and Study Lead Author, University of Sharjah
According to the research, artificial intelligence (AI) can be a potent tool for assessing droughts, which could lead to more proactive and successful management techniques to address water scarcity.
The authors said, “Overall, the findings proved that soft computing models could be considered robust approaches for the rapid and accurate modeling of drought. This paper presented novel high-performing drought indices that can provide decision-makers with a reliable tool for drought management and monitoring.”
According to Dr. Abdallah, the conclusions reached by him and his associates were not just theoretical but also had important ramifications.
Dr. Abdallah adds, “These advancements are not merely academic; they represent a transformative step toward revolutionizing drought preparedness and response, ensuring communities can better withstand and adapt to the evolving climate realities.”
“The significance of this project lies in its potential to revolutionize drought management practices. By providing more accurate and timely predictions, the developed AI-based drought indices can help policymakers, rural planners, and farmers make better-informed decisions, potentially mitigating the adverse effects of droughts on agriculture and water resources,” noted Dr. Abdallah.
For the Middle East, for instance, where water resources are precariously poised, the ability to predict and mitigate drought impacts can steer the region away from potential socio-economic and geo-political crises and promote stability in agricultural output and water management. This breakthrough holds critical implications for securing economic stability and environmental resilience in arid regions increasingly threatened by climate change.
Abdulrahman Abdeljaber, Research Assistant and Study Co-Author, Department of Civil and Environmental Engineering, University of Sharjah
Concerning the available data on climate and environment, the research creates a methodology that can be adapted to the particular requirements of other places.
“This approach provides practical implications by enhancing drought monitoring systems, which enable earlier warnings. Such advancements allow governments and farmers to optimize water usage and storage strategies during dry spells.”
As climate change intensifies, the creative AI tool the authors create is even intended to help with improved resource allocation, agricultural planning, and catastrophe management, guaranteeing that water and food security are not jeopardized.
The technology will enable arid regions to better prepare for and deal with the harsh reality of drought caused by climate change by delivering more accurate data and early warnings.
The study's Lead Author, Mhamd Oyounalsoud, a Research Assistant in the civil and environmental engineering department at the University of Sharjah, said it was evidence that artificial intelligence (AI) is a useful tool for monitoring and assessing droughts, giving specialists the ability to implement “mitigation strategies in water-scarce regions.”
More efficient water management methods are expected to be made possible by AI-based drought indicators, such as the ones the authors construct. These strategies are critical for preserving food security, especially in a world where a severe climate crisis is raging.
“By integrating AI into drought monitoring, we offer a transformative approach that enhances decision-making in resource allocation, critical for regions facing persistent water scarcity,” said Dr. Abdullah Yilmaz, Senior Lecturer and Study Co-Author at the Australian La Trobe University’s School of Computing.
Journal Reference:
Oyounalsoud, S. A., et al. (2024) Drought prediction using artificial intelligence models based on climate data and soil moisture. Scientific Reports. doi.org/10.1038/s41598-024-70406-6.