Abstract
This study explores innovative approaches to fog water collection by introducing a novel cylindrical mesh design, deviating from the traditional flat mesh. Motivated by the need to address the impact of variable wind directions on collection efficiency, field and laboratory experiments were conducted. Field experiments incorporated both square and cylindrical mesh designs, strategically placed to accommodate natural wind variations. Simultaneously, laboratory experiments considered two wind speeds (7 and 9 km/h) for both designs. Results indicated higher water collection quantities at 7 km/h compared to 9 km/h for both designs. The study emphasizes the critical role of wind direction stability. In regions with consistent wind directions during fog and rain events, the square design proves more effective. Conversely, in areas with fluctuating wind patterns, the cylindrical design emerges as a practical choice, showcasing heightened suitability for regions with variable wind patterns. Due to the insufficient water collected for agricultural use, machine learning, specifically artificial neural networks (ANN), was employed. "Model 3" incorporating mean daily temperature, relative humidity, and wind speed as inputs with 20 neurons, demonstrated credible results post-optimization, with an MSE of 1.306 and an R of 0.9574. This underscores the model's efficacy in fog water collection modeling. These findings hold promise for optimizing fog water harvesting strategies and contributing to sustainable water resource management, especially in regions with variable wind patterns. Leveraging the capabilities of ANN, particularly "Model 3" can guide future research endeavors and enhance the feasibility assessment of fog water collection.
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Acknowledgements
The authors extend their appreciation to The Researchers Supporting Project (number RSPD2024R820), King Saud University, Riyadh, Saudi Arabia.
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Researchers Supporting Project Number (RSPD2024R820), King Saud University, Riyadh, Saudi Arabia.
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Mahmoud Mosa and Farid Radwan: Data curation, Formal analysis, Methodology, Software, Validation, Writing—original draft, Writing—Reviewing and Editing. Hussein Al-Ghobari, Hesham Fouli, and Abdulrahman Ali Alazba: Reviewing and Editing. All authors have read and agreed to the published version of the manuscript.
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Communicated by: H. Babaie
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Mosa, M., Radwan, F., Al-Ghobari, H. et al. Impact of varied fog collector designs on fog and rainwater harvesting under fluctuating wind speed and direction. Earth Sci Inform 17, 617–631 (2024). https://doi.org/10.1007/s12145-023-01195-1
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DOI: https://doi.org/10.1007/s12145-023-01195-1