Summary of Integrated Water Resource Management in the Segura Hydrographic Basin: An Artificial Intelligence Approach, by Urtzi Otamendi et al.
Integrated Water Resource Management in the Segura Hydrographic Basin: An Artificial Intelligence Approach
by Urtzi Otamendi, Mikel Maiza, Igor G. Olaizola, Basilio Sierra, Markel Flores, Marco Quartulli
First submitted to arxiv on: 11 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed framework integrates advanced physical modelling, remote sensing techniques, and Artificial Intelligence algorithms to accurately predict water availability, estimate demand, and optimize resource allocation on both short- and long-term basis. The approach combines a comprehensive hydrological model, agronomic crop models for precise demand estimation, and Mixed-Integer Linear Programming for efficient resource distribution. In the study case of the Segura Hydrographic Basin, the approach successfully allocated approximately 642 million cubic meters (hm^3) of water over six months, minimizing the deficit to 9.7% of the total estimated demand. The methodology demonstrated significant environmental benefits, reducing CO2 emissions while optimizing resource distribution. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper presents a new way to manage water resources effectively by using computer algorithms and remote sensing technology. It helps predict how much water will be available, estimate how much is needed, and decide how to share it fairly. In one example, this method was used in Spain’s Segura Hydrographic Basin and successfully managed 642 million cubic meters of water over six months. |
