The Application of Generative Artificial Intelligence in Evaluating and Ranking the Key Factors Influencing the Performance of Rainwater Harvesting Systems

Emami-Skardi, Mohammad Javad; Hedayati Marzooni, Reza; Samaei, Yasaman

doi:10.22112/jwwse.2025.500951.1441

The Application of Generative Artificial Intelligence in Evaluating and Ranking the Key Factors Influencing the Performance of Rainwater Harvesting Systems

Articles in Press

Authors

Mohammad Javad Emami-Skardi ¹

Reza Hedayati Marzooni ²

Yasaman Samaei ³

¹ Civil Engineering Department- Faculty of Engineering and Technology- University of Mazandaran

² Master's student in Bionic Architecture Technology, Mazandaran University

³ Masters in Water Resources Engineering, Imam Khomeini University

10.22112/jwwse.2025.500951.1441

Abstract

Rainwater harvesting systems have been recognized as one of the fundamental strategies in water resource management. Considering climate change and the growing demand for water, many regions are facing water scarcity. These systems can be utilized as a sustainable and cost-effective approach to address these issues. This study aims to identify and rank suitable areas for rainwater harvesting. Using the Generative Artificial Intelligence, Analytical Hierarchy Process (AHP) and geographic data analysis in GIS software, potential areas in Mazandaran province have been identified for this purpose. ChatGPT-4 artificial intelligence was employed to simulate expert opinions in pairwise comparisons. The results of this research, in addition to aiding the development of rainwater harvesting systems, can also evaluate the use of AI in the water resources management and engineering. Among the obtained results, slope had the highest weight with a final value of 0.2412, while geomorphology had the lowest weight with a final value of 0.0372. The findings indicate that the use of AI can facilitate decision-making under uncertainty and challenges in water resource engineering and management.

Keywords

Rainwater Harvesting

Artificial Intelligence

Multi-Criteria Decision Making

Prioritization