| Issue |
E3S Web Conf.
Volume 708, 2026
7th International Conference on Smart Applications and Water Information Systems: “Intelligent Systems, Geospatial Technologies and Modeling for the Sustainable Management of Water Resources” (SAWIS 2025)
|
|
|---|---|---|
| Article Number | 03011 | |
| Number of page(s) | 6 | |
| Section | GIS, AI Applications, and Risk Assessment | |
| DOI | https://doi.org/10.1051/e3sconf/202670803011 | |
| Published online | 30 April 2026 | |
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
1 Laboratory of Engineering Sciences, National School of Applied Sciences, Ibn Tofaïl University, Kenitra 14000, Morocco.
2 Laboratory of Natural Resources and Sustainable Development, Ibn Tofaïl University, Kenitra 14000, Morocco.
3 Sous Massa Hydraulic Bassin agency
4 Managir Director Lenidit, France
5 Managing Director Geosphere, Morocco
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
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.
Key words: Big data analytics / Water resource management / Morocco / Artificial Intelligence (IA) / Optimization / Adoption Model
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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