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Auteur
Dr. Omid Rahmati is a Geo-environmental Researcher and Assistant Professor at the AREEO institute, Iran. He has widespread research interests in risk, modeling, uncertainty, and decision-making in relation to natural hazards and natural resources management. He has published over 70 articles in international peer-reviewed journals and has been cited over 7000 times. He has been selected as the Highly Cited Researchers (the world's top 1% scientists) in 2022 and 2023 based on the Web of Science (Clarivate) who has demonstrated broad and significant influence reflected in his publications over the last decade.
Professor Assefa M. Melesse is a Professor of Water Resources Engineering at Florida International University. He earned his ME (2000) and PhD (2002) from the University of Florida in Agricultural Engineering. His areas of research and experience include climate change impact modeling, watershed modeling, ecohydrology, sediment transport, surface and groundwater interactions modeling, waterenergycarbon fluxes coupling and simulations, remote sensing hydrology, river basin management, and land cover change detection and scaling. Dr. Melesse is a registered Professional Engineer (PE) and also Diplomate of Water Resources Engineer (D. WRE) with over 30 years of teaching and research experience, and has authored/edited 7 books, over 215 journal articles, and over 90 book chapters.Amir Naghibi is an Assistant Professor in the division of Water Resources Engineering and Center for Advanced Middle Eastern Studies at Lund University, in Sweden. He has Broad research interests in hydrology, climate change impact modeling, watershed modeling, surface and groundwater interactions modeling, natural hazards modeling, remote sensing hydrology, and artificial intelligence. He develops AI-based decision support systems on water, agriculture, environment, and natural hazards in order to facilitate decision-making procedure with a transboundary, international, and systematic mindset at national, continental, and global scales. He has published more than 40 papers and in international peer-reviewed journals and his publications have been cited over 4000 times who has demonstrated broad and significant influence reflected in his publications over the last decade.
Texte du rabat
Drought and the condition of water scarcity lead to several socio-economic, social and environmental impacts. Whatever the approaches of drought management, policymakers and planners require novel methods to analyze data and model drought processes and its connection with water scarcity. In recent years, artificial intelligence-based and earth observation approaches have been progressively developed and applied in domain of water-related disasters. The target of this book is to present new advances and achievements in the fields of drought monitoring, analyzing, and modeling using artificial intelligence algorithms (e.g., machine learning, deep learning, etc.), statistical indices, and a diverse range of satellite remote sensing and geo-spatial data sets. Water Scarcity Management: Towards the Application of Artificial Intelligence and Earth Observation Data will help students gain knowledge on drought prediction using new free-access earth observation data and machine learning models. It will also guide scientists, researchers, and urban planners with the monitoring of water resources and key elements of hydrological cycle.
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