American International Journal of Research and Innovation

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Water Resource Management Using Remote Sensing and Artificial Intelligence

Author(s) Prof. Mukand S. Babel
Country United States
Abstract Water resources are essential for ecological balance, agricultural productivity, economic development, and human survival. However, increasing population growth, climate variability, pollution, and inefficient water management practices have created significant challenges for sustainable water resource management. Traditional water monitoring approaches often face limitations related to spatial coverage, data availability, and real-time assessment capabilities. The integration of remote sensing technologies and artificial intelligence (AI) provides innovative opportunities for improving water monitoring, prediction, and management.
This study examines the application of remote sensing and artificial intelligence in sustainable water resource management through the analysis of satellite-based observation systems, machine learning models, predictive analytics, and intelligent decision-support frameworks. The research adopts a conceptual analytical approach based on existing scientific literature, environmental monitoring studies, and technological frameworks. The study evaluates how remote sensing and AI contribute to water availability assessment, drought prediction, flood monitoring, water quality evaluation, and efficient resource allocation.
The findings indicate that AI-enhanced remote sensing systems significantly improve the accuracy, efficiency, and scalability of water resource monitoring. These technologies enable analysis of large-scale environmental datasets and support proactive decision-making for water conservation and climate adaptation. However, challenges related to data quality, computational requirements, technical expertise, and infrastructure availability continue to influence implementation.
The study concludes that integrating remote sensing with artificial intelligence represents a transformative approach for sustainable water resource management. By combining advanced observation capabilities with intelligent analytical systems, these technologies can support resilient water governance and improve long-term water security.
Keywords Remote Sensing, Artificial Intelligence, Water Resource Management, Machine Learning, Water Monitoring, Sustainable Water Management, Environmental Data Analytics
Field Engineering
Published In Volume 4, Issue 3, May-June 2022
Published On 2022-06-26
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