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20. Probabilistic Models Significantly Reduce Uncertainty in Hurricane Harvey Pluvial Flood Loss Estimates V. Rözer et al. 10.1029/2018EF001074
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31. Calibration and validation of FLFA<sub>rs</sub> -- a new flood loss function for Australian residential structures R. Hasanzadeh Nafari et al. 10.5194/nhess-16-15-2016
32. Above the Ravines: Flood Vulnerability Assessment of Earthen Architectural Heritage in Quito (Ecuador) F. Trizio et al. 10.3390/app122311932
33. Predictive applications of Australian flood loss models after a temporal and spatial transfer R. Hasanzadeh Nafari & T. Ngo 10.1080/19475705.2018.1445666
34. 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
35. The object-specific flood damage database HOWAS 21 P. Kellermann et al. 10.5194/nhess-20-2503-2020
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39. 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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43. A generic physical vulnerability model for floods: review and concept for data-scarce regions M. Malgwi et al. 10.5194/nhess-20-2067-2020
44. Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT‐FLEMO H. Kreibich et al. 10.1111/risa.12650
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46. Urban Flood Risk Assessment Based on a Combination of Subjective and Objective Multi-Weight Methods J. Chen et al. 10.3390/app14093694
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48. Machine learning models to predict myocardial infarctions from past climatic and environmental conditions L. Marien et al. 10.5194/nhess-22-3015-2022
49. The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models M. Drews et al. 10.1016/j.scitotenv.2023.164962
50. Dynamic vulnerability factors for impact-based flash flood prediction G. Terti et al. 10.1007/s11069-015-1910-8
51. A coupled probabilistic hydrologic and hydraulic modelling framework to investigate the uncertainty of flood loss estimates E. Ahmadisharaf & A. Kalyanapu 10.1111/jfr3.12536
52. A hybrid deep learning model for predictive flood warning and situation awareness using channel network sensors data S. Dong et al. 10.1111/mice.12629
53. Flood vulnerability assessment in the flood prone area of Khyber Pakhtunkhwa, Pakistan M. Ibrahim et al. 10.3389/fenvs.2024.1303976
54. A data-mining approach towards damage modelling for El Niño events in Peru F. Brill et al. 10.1080/19475705.2020.1818636
55. Improvements and Operational Application of a Zero-Order Quick Assessment Model for Flood Damage: A Case Study in Italy L. Manselli et al. 10.3390/w14030373
56. Flood Loss Models and Risk Analysis for Private Households in Can Tho City, Vietnam D. Chinh et al. 10.3390/w9050313
57. 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
58. Characterization of damages in buildings after floods in Vega Baja County (Spain) in 2019. The case study of Almoradí municipality R. Moya Barbera et al. 10.1016/j.cscm.2024.e03004
59. 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
60. Flood Damage Analysis Using Machine Learning Techniques . Snehil & R. Goel 10.1016/j.procs.2020.06.011
61. Improving flood impact estimations T. Sieg & A. Thieken 10.1088/1748-9326/ac6d6c
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65. Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
66. The construction of flood loss ratio function in cities lacking loss data based on dynamic proportional substitution and hierarchical Bayesian model H. Lv et al. 10.1016/j.jhydrol.2020.125797
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69. Contribution of insurance data to cost assessment of coastal flood damage to residential buildings: insights gained from Johanna (2008) and Xynthia (2010) storm events C. André et al. 10.5194/nhess-13-2003-2013
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73. Testing empirical and synthetic flood damage models: the case of Italy M. Amadio et al. 10.5194/nhess-19-661-2019
74. Flood loss estimation using 3D city models and remote sensing data K. Schröter et al. 10.1016/j.envsoft.2018.03.032
75. A Comparison of Factors Driving Flood Losses in Households Affected by Different Flood Types G. Mohor et al. 10.1029/2019WR025943
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86. A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
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90. Natural Disasters Intensity Analysis and Classification Based on Multispectral Images Using Multi-Layered Deep Convolutional Neural Network M. Aamir et al. 10.3390/s21082648
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