72 citations as recorded by crossref.

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2. The value of multi-source data for improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0 M. Di Bacco et al. 10.5194/nhess-24-1681-2024
3. A Bayesian network approach for multi-sectoral flood damage assessment and multi-scenario analysis R. Harris et al. 10.1016/j.crm.2022.100410
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5. The role of socio-economic and property variables in the establishment of flood depth-damage curve for the data-scarce area in Malaysia S. Sulong & N. Romali 10.1080/1573062X.2022.2099292
6. The potential of open-access data for flood estimations: uncovering inundation hotspots in Ho Chi Minh City, Vietnam, through a normalized flood severity index L. Scheiber et al. 10.5194/nhess-23-2313-2023
7. Flood Depth Estimation in Agricultural Lands From L and C-Band Synthetic Aperture Radar Images and Digital Elevation Model S. Surampudi & V. Kumar 10.1109/ACCESS.2023.3234742
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10. Cost–benefit analysis of coastal flood defence measures in the North Adriatic Sea M. Amadio et al. 10.5194/nhess-22-265-2022
11. Flood damage assessment model of industrial sectors in a Megacity: Derivation from business survey data in the Bangkok Metropolitan Region S. Darnkachatarn & Y. Kajitani 10.1016/j.ijdrr.2025.105221
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13. Measurement Approach to Develop Flood-Based Damage Fragilities for Residential Buildings Following Repeat Inundation Events P. Shane Crawford et al. 10.1061/AJRUA6.0001219
14. Attributing Venice Acqua Alta events to a changing climate and evaluating the efficacy of MoSE adaptation strategy D. Faranda et al. 10.1038/s41612-023-00513-0
15. Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. 10.1016/j.envsoft.2020.104798
16. A data-driven framework for enhancing coastal flood resilience in resource-crunched developing nations A. Narendr et al. 10.1080/19475705.2024.2396892
17. Brief Communication: Simple-INSYDE, development of a new tool for flood damage evaluation from an existing synthetic model M. Galliani et al. 10.5194/nhess-20-2937-2020
18. Optimal Domain Scale for Stochastic Urban Flood Damage Assessment Considering Triple Spatial Uncertainties H. Lv et al. 10.1029/2021WR031552
19. Flood Vulnerability Models and Household Flood Damage Mitigation Measures: An Econometric Analysis of Survey Data T. Endendijk et al. 10.1029/2022WR034192
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21. A methodology for development of flood-depth-velocity damage functions for improved estimation of pluvial flood risk in cities D. Adeke & S. Mugume 10.1016/j.jhydrol.2025.132736
22. Flood risk assessment of the European road network K. van Ginkel et al. 10.5194/nhess-21-1011-2021
23. Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
24. The middle Huaihe River stability analysis and optimization of hydrological chaos forecasting model Y. Duan et al. 10.1080/19475705.2020.1815870
25. 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
26. Evaluation of residential building damage for the July 2021 flood in Westport, New Zealand R. Paulik et al. 10.1186/s40562-024-00323-z
27. Historical comparison of the damage caused by the propagation of a dam break wave in a pre-alpine valley R. Bonomelli et al. 10.1016/j.ejrh.2023.101467
28. Tracking a Decade of Hydrogeological Emergencies in Italian Municipalities A. Gatto et al. 10.3390/data8100151
29. A GIS-based flood damage index for cultural heritage C. Arrighi et al. 10.1016/j.ijdrr.2023.103654
30. Spatial Transferability of Residential Building Damage Models between Coastal and Fluvial Flood Hazard Contexts R. Paulik et al. 10.3390/jmse11101960
31. 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
32. CERCA (Cascading Effects in Risk Consequences Assessment): An operational tool for geo-hydrological scenario risk assessment and cascading effects evaluation D. Biondi et al. 10.2166/nh.2023.088
33. Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction D. Wagenaar et al. 10.1111/risa.13575
34. Toward an adequate level of detail in flood risk assessments T. Sieg et al. 10.1111/jfr3.12889
35. 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
36. Investigating the Role of the Key Conditioning Factors in Flood Susceptibility Mapping Through Machine Learning Approaches K. Al-Kindi & Z. Alabri 10.1007/s41748-023-00369-7
37. Are flood damage models converging to “reality”? Lessons learnt from a blind test D. Molinari et al. 10.5194/nhess-20-2997-2020
38. A Global Scale Analysis of River Flood Risk of UNESCO World Heritage Sites C. Arrighi 10.3389/frwa.2021.764459
39. Flood-Triggering Rainfall and Potential Losses—The Copula-Based Approach on the Example of the Upper Nysa Kłodzka River A. Perz et al. 10.3390/w15101958
40. Evaluating targeted heuristics for vulnerability assessment in flood impact model chains A. Zischg et al. 10.1111/jfr3.12736
41. Study on urban flood early warning system considering flood loss Y. Zang et al. 10.1016/j.ijdrr.2022.103042
42. Simplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area D. Marín-García et al. 10.1016/j.scs.2022.104251
43. 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
44. Residential flood loss estimated from Bayesian multilevel models G. Mohor et al. 10.5194/nhess-21-1599-2021
45. Empirical flash flood vulnerability functions for residential buildings C. Arrighi et al. 10.1007/s42452-020-2696-1
46. A Method for Assessing Flood Vulnerability Based on Vulnerability Curves and Online Data of Residential Buildings—A Case Study of Shanghai Z. Li et al. 10.3390/w14182840
47. Hydrodynamic Modelling of Floods and Estimating Socio-economic Impacts of Floods in Ugandan River Malaba Sub-catchment A. Mubialiwo et al. 10.1007/s41748-021-00283-w
48. INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium) A. Scorzini et al. 10.5194/nhess-22-1743-2022
49. Flood depth-damage and fragility functions derived with structured expert judgment G. Pita et al. 10.1016/j.jhydrol.2021.126982
50. Multi-scenario flash flood hazard assessment based on rainfall–runoff modeling and flood inundation modeling: a case study Y. Zhang et al. 10.1007/s11069-020-04345-6
51. Building-scale flood loss estimation through vulnerability pattern characterization: application to an urban flood in Milan, Italy A. Taramelli et al. 10.5194/nhess-22-3543-2022
52. Measuring community resilience of flash floods using a multilevel interpretive structure model: Quantification and time-varying responses M. Zhong et al. 10.1016/j.ecolind.2025.113335
53. Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe D. Paprotny et al. 10.1016/j.scitotenv.2020.140011
54. Construction of flood loss function for cities lacking disaster data based on three-dimensional (object-function-array) data processing H. Lv et al. 10.1016/j.scitotenv.2021.145649
55. Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study D. Rajapaksha et al. 10.3390/buildings14061864
56. A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
57. Invited perspectives: How machine learning will change flood risk and impact assessment D. Wagenaar et al. 10.5194/nhess-20-1149-2020
58. The public finance response to floods of local governments in Italy C. Lodi et al. 10.1016/j.jenvman.2023.117352
59. Examining direct and indirect flood damages in residential and business sectors through an empirical lens S. Kabirzad et al. 10.2166/wst.2024.202
60. 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
61. Mapping the exposure of tourism to weather extremes: the need for a spatially-explicit gridded dataset for disaster risk reduction N. Camatti et al. 10.1088/1748-9326/ad3e91
62. Exploring machine learning potential for climate change risk assessment F. Zennaro et al. 10.1016/j.earscirev.2021.103752
63. The Use of Weather Radar Data: Possibilities, Challenges and Advanced Applications M. Binetti et al. 10.3390/earth3010012
64. Flood Depth‒Damage Curves for Spanish Urban Areas E. Martínez-Gomariz et al. 10.3390/su12072666
65. Unzipping flood vulnerability and functionality loss: tale of struggle for existence of riparian buildings D. Gautam et al. 10.1007/s11069-022-05433-5
66. Probabilistic Assessment of Pluvial Flood Risk Across 20 European Cities: A Demonstrator of the Copernicus Disaster Risk Reduction Service for Pluvial Flood Risk in Urban Areas A. Essenfelder et al. 10.1142/S2382624X22400070
67. To dam or not to dam? Actionable socio-hydrology modeling to inform robust adaptation to water scarcity and water extremes L. Gil-García et al. 10.1016/j.envsci.2023.03.012
68. XGBoost-based method for flash flood risk assessment M. Ma et al. 10.1016/j.jhydrol.2021.126382
69. Flood vulnerability assessment of urban buildings based on integrating high-resolution remote sensing and street view images Z. Xing et al. 10.1016/j.scs.2023.104467
70. 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
71. Flood Damage Assessment: A Review of Microscale Methodologies for Residential Buildings O. Aribisala et al. 10.3390/su142113817
72. Examining direct and indirect flood damages in residential and business sectors through an empirical lens S. Kabirzad et al. 10.2166/wst.2024.202