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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

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Showing 1-25 of 88 citing articles:

Flood hazard mapping methods: A review
Rofiat Bunmi Mudashiru, Nuridah Sabtu, Ismail Abustan, et al.
Journal of Hydrology (2021) Vol. 603, pp. 126846-126846
Closed Access | Times Cited: 233
Predicting flood susceptibility using LSTM neural networks
Zhice Fang, Yi Wang, Ling Peng, et al.
Journal of Hydrology (2020) Vol. 594, pp. 125734-125734
Open Access | Times Cited: 208
Spatial prediction of flood potential using new ensembles of bivariate statistics and artificial intelligence: A case study at the Putna river catchment of Romania
Romulus Costache, Dieu Tien Bui
The Science of The Total Environment (2019) Vol. 691, pp. 1098-1118
Closed Access | Times Cited: 149
Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Mapping
Peyman Yariyan, Saeid Janizadeh, Tran Van Phong, et al.
Water Resources Management (2020) Vol. 34, Iss. 9, pp. 3037-3053
Closed Access | Times Cited: 148
Mapping the spatial and temporal variability of flood hazard affected by climate and land-use changes in the future
Saeid Janizadeh, Subodh Chandra Pal, Asish Saha, et al.
Journal of Environmental Management (2021) Vol. 298, pp. 113551-113551
Open Access | Times Cited: 128
A novel hybrid of meta-optimization approach for flash flood-susceptibility assessment in a monsoon-dominated watershed, Eastern India
Dipankar Ruidas, Rabin Chakrabortty, Abu Reza Md. Towfiqul Islam, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 5
Closed Access | Times Cited: 94
Enhancing flood risk assessment through integration of ensemble learning approaches and physical-based hydrological modeling
Mohamed Saber, Tayeb Boulmaiz, Mawloud Guermoui, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 52
Identification of areas prone to flash-flood phenomena using multiple-criteria decision-making, bivariate statistics, machine learning and their ensembles
Romulus Costache, Dieu Tien Bui
The Science of The Total Environment (2020) Vol. 712, pp. 136492-136492
Closed Access | Times Cited: 134
Earth fissure hazard prediction using machine learning models
Bahram Choubin, Amir Mosavi, Esmail Heydari Alamdarloo, et al.
Environmental Research (2019) Vol. 179, pp. 108770-108770
Closed Access | Times Cited: 133
Examining LightGBM and CatBoost models for wadi flash flood susceptibility prediction
Mohamed Saber, Tayeb Boulmaiz, Mawloud Guermoui, et al.
Geocarto International (2021) Vol. 37, Iss. 25, pp. 7462-7487
Open Access | Times Cited: 102
A Novel GIS-Based Random Forest Machine Algorithm for the Spatial Prediction of Shallow Landslide Susceptibility
Viet-Hung Dang, Nhat‐Duc Hoang, Le-Mai-Duyen Nguyen, et al.
Forests (2020) Vol. 11, Iss. 1, pp. 118-118
Open Access | Times Cited: 78
Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms
Alireza Arabameri, Subodh Chandra Pal, Romulus Costache, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 469-498
Open Access | Times Cited: 77
Flood susceptibility mapping of Northeast coastal districts of Tamil Nadu India using Multi-source Geospatial data and Machine Learning techniques
Subbarayan Saravanan, Devanantham Abijith
Geocarto International (2022) Vol. 37, Iss. 27, pp. 15252-15281
Closed Access | Times Cited: 46
Exploring the additional value of class imbalance distributions on interpretable flash flood susceptibility prediction in the Black Warrior River basin, Alabama, United States
Ömer Ekmekcioğlu, Kerim Koç, Mehmet Özger, et al.
Journal of Hydrology (2022) Vol. 610, pp. 127877-127877
Closed Access | Times Cited: 45
Explainable step-wise binary classification for the susceptibility assessment of geo-hydrological hazards
Ömer Ekmekcioğlu, Kerim Koç
CATENA (2022) Vol. 216, pp. 106379-106379
Closed Access | Times Cited: 44
Computational Machine Learning Approach for Flood Susceptibility Assessment Integrated with Remote Sensing and GIS Techniques from Jeddah, Saudi Arabia
Ahmed M. Al‐Areeq, Sani I. Abba, Mohamed A. Yassin, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5515-5515
Open Access | Times Cited: 43
Flood susceptibility prediction using tree-based machine learning models in the GBA
Hai‐Min Lyu, Zhen‐Yu Yin
Sustainable Cities and Society (2023) Vol. 97, pp. 104744-104744
Closed Access | Times Cited: 38
Evaluation of flood susceptibility prediction based on a resampling method using machine learning
Septianto Aldiansyah, Farida Wardani
Journal of Water and Climate Change (2023) Vol. 14, Iss. 3, pp. 937-961
Open Access | Times Cited: 23
A novel approach to flood risk assessment: Synergizing with geospatial based MCDM-AHP model, multicollinearity, and sensitivity analysis in the Lower Brahmaputra Floodplain, Assam
Pranab Dutta, Sujit Deka
Journal of Cleaner Production (2024) Vol. 467, pp. 142985-142985
Closed Access | Times Cited: 15
Flash Flood Susceptibility Modelling Using Soft Computing-Based Approaches: From Bibliometric to Meta-Data Analysis and Future Research Directions
Gilbert Hinge, Mohamed A. Hamouda, Mohamed Mostafa Mohamed
Water (2024) Vol. 16, Iss. 1, pp. 173-173
Open Access | Times Cited: 12
Implication of novel hybrid machine learning model for flood subsidence susceptibility mapping: A representative case study in Saudi Arabia
Ahmed M. Al‐Areeq, Radhwan A. A. Saleh, Mustafa Ghaleb, et al.
Journal of Hydrology (2024) Vol. 630, pp. 130692-130692
Closed Access | Times Cited: 10
Evaluating the impact of check dam construction on runoff processes in Al-Dayer watershed using a physically-based hydrologic model
Ahmed M. Al‐Areeq, Isam H. Aljundi
Geomatics Natural Hazards and Risk (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 1
A New Hybrid Firefly–PSO Optimized Random Subspace Tree Intelligence for Torrential Rainfall-Induced Flash Flood Susceptible Mapping
Viet‐Ha Nhu, Phuong Thao Thi Ngo, Tien Dat Pham, et al.
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2688-2688
Open Access | Times Cited: 68
New neural fuzzy-based machine learning ensemble for enhancing the prediction accuracy of flood susceptibility mapping
Romulus Costache, Roxana Ţîncu, Ismail Elkhrachy, et al.
Hydrological Sciences Journal (2020) Vol. 65, Iss. 16, pp. 2816-2837
Closed Access | Times Cited: 65
Predicting flood insurance claims with hydrologic and socioeconomic demographics via machine learning: Exploring the roles of topography, minority populations, and political dissimilarity
James Knighton, Brian Buchanan, Christian D. Guzmán, et al.
Journal of Environmental Management (2020) Vol. 272, pp. 111051-111051
Open Access | Times Cited: 55
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