Integrating knowledge management practices in higher education with sustainable smart hydrological ecosystems: an AI-driven approach to green innovation Open Access

This study investigates the dual impact of knowledge management (KM) practices within higher education and their application in sustainable smart hydrological ecosystems, aimed at fostering green innovation. By leveraging data collected from university students and faculty regarding KM practices, alongside environmental data from hydrological sensors and monitoring systems, this research bridges educational insights with environmental sustainability. The study utilizes radial basis function networks to analyze complex, multi-source data, including real-time environmental parameters and knowledge dissemination metrics within educational institutions. The findings reveal how effective KM practices within higher education can influence broader environmental sustainability outcomes, particularly in enhancing the resilience of hydrological ecosystems. This integrated approach underscores the potential of AI-driven KM systems to contribute significantly to both educational excellence and global green innovation efforts.

• Integrates knowledge management practices with hydrological management, linking academic knowledge to practical water sustainability.

• Applies radial basis function (RBF) networks for enhanced predictive accuracy in water resource management.

• Bridges education and environmental sustainability through artificial intelligence-driven analysis.

• Improves climate adaptation strategies in water management.

• Provides a scalable framework for global water sustainability.