Investigating the salinity vulnerability potential of Ajab-Shir plain aquifer using GALDIT framework and improving it with artificial intelligence

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Nouri Sangarab Soraya; Asghari Moghaddam-Heris Asghar; Jabraili Andaryan Nasser

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Journal: GEOSCIENCES Year:2025 | Volume: | Issue: Page(s): 85-100

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Information Journal Paper

Title

Investigating the salinity vulnerability potential of Ajab-Shir plain aquifer using GALDIT framework and improving it with artificial intelligence

Author(s)

Nouri Sangarab Soraya | Asghari Moghaddam-Heris Asghar | Jabraili Andaryan Nasser | Issue Writer Certificate

Keywords

Coastal Aquifer

salinity vulnerability potential

Ajab-Shir plain

GALDIT

Abstract

In recent years, the salinization in Coastal Aquifers, where agriculture is always developing, requires the investigation of aquifer vulnerability to water salinity. In the Ajab-Shir aquifer, to investigate the GALDIT vulnerability framework, which includes six layers such as type of aquifer (G), Aquifer hydraulic conductivity (A), Groundwater level above the sea level (L), distance from the coastline (D), quality Impact of saline water intrusion (I) and Aquifer thickness (T) used. Meanwhile, TDS values used to validate zoned vulnerability map. Also, to ensure the certainty of the available data, as well as to improve the weight and fix expert's errors in determining the weight of GALDIT layers, fuzzy logic (Sugeno), genetic algorithm (GA), random subspace algorithm (RS) and decision tree algorithm (M5P) were used. The results showed the correlation coefficient of about 0.5, 0.81, 0.6, 0.8, and 0.8 between GALDIT, GALDIT-F, GALDIT-GA, GALDIT-RS, and GALDIT-M5P with TDS, respectively. The south and south-east parts of the plain show the highest salinity potential and correlation values showed the good performance of GALDIT-F, GALDIT-RS and GALDIT-M5P methods in this study.

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