| 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 | 03006 | |
| Number of page(s) | 7 | |
| Section | GIS, AI Applications, and Risk Assessment | |
| DOI | https://doi.org/10.1051/e3sconf/202670803006 | |
| Published online | 30 April 2026 | |
Analysis of water segregation in Morocco: Using GIS and machine learning approaches
1 Faculty of Economics and Management, Ibn Tofail University, Kenitra, Morocco
2,3 Faculty of Economics and Management, Ibn Zohr University, Morocco
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Water accessibility in Morocco manifests itself in multiple ways this is complex. In some areas, there is enough water due to climate and geography. Some people can't get enough water easily for their everyday need while there are others who have to deal with it daily. The study looks at how and why these shortages are happening. In addition, how economic and geographical factors affect water use and delivery across the country. To represent an entire picture, we merged together spatial maps, statistics and economic data as to how water-linked trouble in each region imposes a cost on its economy. Key importance was given to the quantum of water needed under ideal conditions; the level of water stress at each location; and the economic returns of water usage in agricultural, industrial and other use. Some local fixes show up in the findings, which require no investment. Fixing leaking pipes and reservoirs, carrying out public information campaigns to reduce waste, and commencing new projects to use underused resources such as groundwater or to build desalination plants.
© 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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