Optimizing Water Resource Management Through Big Data Analytics and Artificial Intelligence: A Proposal for an Adoption Model – Case Study of HBA Souss Massa in Morocco
Year: 2026
Type: article
Abstract: Big data analytics and artificial intelligence are transformative technologies driving innovation across industries, including water resource management. These technologies provide promising solutions to optimize water management globally by enabling informed, data-driven decision-making. Implementing robust big data and AI architectures in Morocco offers a strategic advantage in addressing critical water management challenges. This study presents an overview of water resource management practices in Morocco. It explores how big data analytics combined with AI can enhance operational efficiency, predict water demand, and improve resource allocation. We analyze five prominent big data and AI architectures from existing research, examining their use cases and limitations in water management contexts. Based on these insights, we propose an adoption model and a prototype framework that equips adopters with a structured approach for selecting suitable tools at each architecture stage. Our proposed model offers a customizable roadmap, empowering Moroccan water authorities to effectively deploy a comprehensive big data and AI-based management system. This approach provides a clear understanding of big data pipelines and AI integration and establishes a scalable foundation for optimized water resource management in Morocco.
Institution: Université Ibn-Tofail
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7160291361
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