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13. Above the Ravines: Flood Vulnerability Assessment of Earthen Architectural Heritage in Quito (Ecuador) F. Trizio et al. 10.3390/app122311932
14. Predictive applications of Australian flood loss models after a temporal and spatial transfer R. Hasanzadeh Nafari & T. Ngo 10.1080/19475705.2018.1445666
15. Flood vulnerability and risk assessment of urban traditional buildings in a heritage district of Kuala Lumpur, Malaysia D. D'Ayala et al. 10.5194/nhess-20-2221-2020
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19. Assessing the impact of climate change on fluvial flood losses in urban areas: a case study of Pamplona (Spain) E. Soriano et al. 10.1080/02626667.2023.2246452
20. Environmental Inequalities in Flood Exposure: A Matter of Scale C. Poussard et al. 10.3389/frwa.2021.633046
21. A generic physical vulnerability model for floods: review and concept for data-scarce regions M. Malgwi et al. 10.5194/nhess-20-2067-2020
22. Development of a flood damage mitigation index for flood management capacity assessment using regression function parameters H. Park & S. Seo 10.1007/s11069-025-07605-5
23. Machine learning models to predict myocardial infarctions from past climatic and environmental conditions L. Marien et al. 10.5194/nhess-22-3015-2022
24. The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models M. Drews et al. 10.1016/j.scitotenv.2023.164962
25. A coupled probabilistic hydrologic and hydraulic modelling framework to investigate the uncertainty of flood loss estimates E. Ahmadisharaf & A. Kalyanapu 10.1111/jfr3.12536
26. Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam D. Chinh et al. 10.3390/w9050313
27. Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale H. Kreibich et al. 10.5194/piahs-373-179-2016
28. Pluvial flood risk assessment for 2021–2050 under climate change scenarios in the Metropolitan City of Venice E. Allegri et al. 10.1016/j.scitotenv.2024.169925
29. Context-specificity of tsunami vulnerability models for roads and buildings T. Putra et al. 10.1016/j.ijdrr.2025.105454
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32. Exploring drought hazard, vulnerability, and related impacts on agriculture in Brandenburg F. Brill et al. 10.5194/nhess-24-4237-2024
33. Flooding: Contributing factors to residential flood damage in Canada B. Deschamps et al. 10.1016/j.ijdrr.2025.105348
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35. Integrating socio-economic variables in urban flood damage assessments: a case study of Bengaluru, India A. Pathak et al. 10.1007/s11069-024-07019-9
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37. Flood damage functions based on a single physics- and data-based impact parameter that jointly accounts for water depth and velocity T. Lazzarin et al. 10.1016/j.jhydrol.2022.127485
38. Flood risk assessment of cultural heritage at large spatial scales: Framework and application to mainland Portugal R. Figueiredo et al. 10.1016/j.culher.2019.11.007
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41. A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
42. Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs. weather-generator-based approach B. Winter et al. 10.5194/nhess-20-1689-2020
43. Natural Disasters Intensity Analysis and Classification Based on Multispectral Images Using Multi-Layered Deep Convolutional Neural Network M. Aamir et al. 10.3390/s21082648
44. Comprehensive Understanding the Disaster-Causing Mechanism, Governance Dilemma and Targeted Countermeasures of Urban Pluvial Flooding in China F. Kong et al. 10.3390/w13131762
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50. Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures R. Hasanzadeh Nafari et al. 10.5194/nhess-17-1047-2017
51. Multi-Variate Analyses of Flood Loss in Can Tho City, Mekong Delta D. Chinh et al. 10.3390/w8010006
52. Probabilistic Flood Loss Models for Companies L. Schoppa et al. 10.1029/2020WR027649
53. Multi-variable flood damage modelling with limited data using supervised learning approaches D. Wagenaar et al. 10.5194/nhess-17-1683-2017
54. Commercial Real-Estate at Risk: An Examination of Commercial Building and Economic Impacts in the United States Using a High-Precision Flood Risk Assessment Tool J. Porter et al. 10.3389/frwa.2022.875995
55. The socioeconomic impact of climate-related hazards: flash flood impact assessment in Kuala Lumpur, Malaysia T. Bhuiyan et al. 10.1007/s11069-021-04887-3
56. Uncovering Drivers of Atmospheric River Flood Damage Using Interpretable Machine Learning C. Bowers et al. 10.1061/NHREFO.NHENG-1995
57. Mapping flood susceptibility in mountainous areas on a national scale in China G. Zhao et al. 10.1016/j.scitotenv.2017.10.037
58. Is anthropogenic land subsidence a possible driver of riverine flood-hazard dynamics? A case study in Ravenna, Italy F. Carisi et al. 10.1080/02626667.2017.1390315
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60. Surface water floods in Switzerland: what insurance claim records tell us about the damage in space and time D. Bernet et al. 10.5194/nhess-17-1659-2017
61. Global-Scale Assessment of Economic Losses Caused by Flood-Related Business Interruption R. Taguchi et al. 10.3390/w14060967
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65. Review Article: A comparison of flood and earthquake vulnerability assessment indicators M. de Ruiter et al. 10.5194/nhess-17-1231-2017
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70. Economic Value of Flood Forecasts and Early Warning Systems: A Review G. Van Houtven 10.1061/NHREFO.NHENG-2094
71. Leveraging data driven approaches for enhanced tsunami damage modelling: Insights from the 2011 Great East Japan event M. Di Bacco et al. 10.1016/j.envsoft.2022.105604
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74. Review Article: Economic evaluation of flood damage to agriculture – review and analysis of existing methods P. Brémond et al. 10.5194/nhess-13-2493-2013
75. A data-driven approach for regional-scale fine-resolution disaster impact prediction under tropical cyclones P. Lin & N. Wang 10.1007/s11069-024-06527-y
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77. Significance of chloride penetration controlling parameters in concrete: Ensemble methods W. Taffese & E. Sistonen 10.1016/j.conbuildmat.2017.02.014
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83. Construction and Application of Reservoir Flood Control Operation Rules Using the Decision Tree Algorithm Y. Diao et al. 10.3390/w13243654
84. BN-FLEMOΔ: a Bayesian-network-based flood loss estimation model for adaptation planning in Ho Chi Minh City, Vietnam K. Shahi et al. 10.5194/nhess-25-2845-2025
85. Developing a multivariable lookup table function for estimating flood damages of rice crop in Vietnam using a secondary research approach N. Nguyen et al. 10.1016/j.ijdrr.2021.102208
86. Regional Rainfall Damage Functions to Estimate Direct Economic Losses in Rainstorms: A Case Study of the 2016 Extreme Rainfall Event in Hebei Province of China X. Chen et al. 10.1007/s13753-024-00577-3
87. Estimating exposure of residential assets to natural hazards in Europe using open data D. Paprotny et al. 10.5194/nhess-20-323-2020
88. Spatial Dependence Modeling of Flood Risk Using Max-Stable Processes: The Example of Austria H. Albrecher et al. 10.3390/w12061805
89. INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium) A. Scorzini et al. 10.5194/nhess-22-1743-2022
90. Fluvial Flood Losses in the Contiguous United States Under Climate Change M. Rashid et al. 10.1029/2022EF003328
91. Study on Influencing Factors of Flood Damage to Single Houses using Field Survey Data C. Choi et al. 10.9798/KOSHAM.2018.18.7.535
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93. Flood loss models for residential buildings, based on the 2013 Colorado floods D. Deniz et al. 10.1007/s11069-016-2615-3
94. Floods across the eastern United States are projected to last longer H. Kim & G. Villarini 10.1038/s44304-024-00021-y
95. Survey of computational intelligence as basis to big flood management: challenges, research directions and future work F. Fotovatikhah et al. 10.1080/19942060.2018.1448896
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121. Multi-variate residential flood loss estimation model for Jakarta: an approach based on a combination of statistical techniques R. Wahab & R. Tiong 10.1007/s11069-016-2716-z
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