Stormwater management modeling and machine learning for flash flood susceptibility prediction in Wadi Qows, Saudi Arabia-Reference-Cited by-同舟云学术

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Stormwater management modeling and machine learning for flash flood susceptibility prediction in Wadi Qows, Saudi Arabia

Published:2023 Issue:3 Volume:17 Page:62-68
ISSN:1882-3416
Container-title:Hydrological Research Letters
language:en
Short-container-title:Hydrological Research Letters

Author:

Alamoudi Fahad¹,Saber Mohamed²,A. Kantoush Sameh²,Boulmaiz Tayeb³,Abdrabo Karim I.¹,Abdelmoneim Hadir⁴,Sumi Tetsuya²

Affiliation:

1. Graduate School of Engineering, Kyoto University, ‎Japan

2. Disaster Prevention Research Institute, Kyoto University, ‎Japan

3. Materials, Energy Systems Technology and Environment Laboratory, Ghardaia ‎University, Algeria

4. Faculty of Engineering, Alexandria University, ‎Egypt

Publisher

Japan Society of Hydrology and Water Resources

Subject

Earth and Planetary Sciences (miscellaneous),Water Science and Technology

Link

https://www.jstage.jst.go.jp/article/hrl/17/3/17_62/_pdf

Reference26 articles.

1. Abdel-Fattah M, Kantoush SA, Saber M, Sumi T. 2018. Rainfall-runoff modeling for extreme flash floods in wadi samail, oman. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) 74: I_691–I_696. DOI: 10.2208/jscejhe.74.5_i_691.

2. Abdrabo KI, Kantoush SA, Saber M, Sumi T, Habiba OM, Elleithy D, Elboshy B. 2020. Integrated methodology for urban flood risk mapping at the microscale in ungauged regions: A case study of Hurghada, Egypt. Remote Sensing 12: 3548. DOI: 10.3390/rs12213548.

3. Al-Areeq AM, Abba SI, Yassin MA, Benaafi M, Ghaleb M, Aljundi IH. 2022. Computational machine learning approach for flood susceptibility assessment integrated with remote sensing and GIS techniques from Jeddah, Saudi Arabia. Remote Sensing 14: 5515. DOI: 10.3390/rs14215515.

4. Ali SA, Parvin F, Pham QB, Vojtek M, Vojteková J, Costache R, Linh NTT, Nguyen HQ, Ahmad A, Ghorbani MA. 2020. GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve bayes tree, bivariate statistics and logistic regression: A case of Topl’a Basin, Slovakia. Ecological Indicators 117: 106620. DOI: 10.1016/j.ecolind.2020.106620.

5. Arabameri A, Saha S, Mukherjee K, Blaschke T, Chen W, Thi Ngo P-T, Band SS. 2020. Modeling spatial flood using novel ensemble artificial intelligence approaches in northern Iran. Remote Sensing 12: 3423. DOI: 10.3390/rs12203423.

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