77 citations as recorded by crossref.

1. Multi-model ensembles for assessment of flood losses and associated uncertainty R. Figueiredo et al. 10.5194/nhess-18-1297-2018
2. Estimating exposure of residential assets to natural hazards in Europe using open data D. Paprotny et al. 10.5194/nhess-20-323-2020
3. Evaluation of residential building damage for the July 2021 flood in Westport, New Zealand R. Paulik et al. 10.1186/s40562-024-00323-z
4. The object-specific flood damage database HOWAS 21 P. Kellermann et al. 10.5194/nhess-20-2503-2020
5. 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
6. A review of flood damage analysis for a building structure and contents M. Marvi 10.1007/s11069-020-03941-w
7. Testing empirical and synthetic flood damage models: the case of Italy M. Amadio et al. 10.5194/nhess-19-661-2019
8. Historical development and future outlook of the flood damage potential of residential areas in the Alpine Lech Valley (Austria) between 1971 and 2030 H. Cammerer & A. Thieken 10.1007/s10113-013-0407-9
9. Estimating changes in flood risks and benefits of non-structural adaptation strategies - a case study from Tyrol, Austria A. Thieken et al. 10.1007/s11027-014-9602-3
10. Spatially coherent flood risk assessment based on long-term continuous simulation with a coupled model chain D. Falter et al. 10.1016/j.jhydrol.2015.02.021
11. Continuous, large‐scale simulation model for flood risk assessments: proof‐of‐concept D. Falter et al. 10.1111/jfr3.12105
12. Flood frequencies and durations and their response to El Niño Southern Oscillation: Global analysis P. Ward et al. 10.1016/j.jhydrol.2016.05.045
13. Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. 10.1016/j.envsoft.2020.104798
14. Damage assessment of lake floods: Insured damage to private property during two lake floods in Sweden 2000/2001 T. Grahn & R. Nyberg 10.1016/j.ijdrr.2014.10.003
15. Flood Damage Modeling on the Basis of Urban Structure Mapping Using High-Resolution Remote Sensing Data T. Gerl et al. 10.3390/w6082367
16. Validation of flood risk models: Current practice and possible improvements D. Molinari et al. 10.1016/j.ijdrr.2018.10.022
17. Review article: Assessing the costs of natural hazards – state of the art and knowledge gaps V. Meyer et al. 10.5194/nhess-13-1351-2013
18. Exploring the potential of multivariate depth‐damage and rainfall‐damage models L. Van Ootegem et al. 10.1111/jfr3.12284
19. Quantifying Flood Vulnerability Reduction via Private Precaution N. Sairam et al. 10.1029/2018EF000994
20. Adaptability and transferability of flood loss functions in residential areas H. Cammerer et al. 10.5194/nhess-13-3063-2013
21. A Review of Flood Loss Models as Basis for Harmonization and Benchmarking T. Gerl et al. 10.1371/journal.pone.0159791
22. A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. 10.1007/s11069-020-04413-x
23. Multi-variate flood damage assessment: a tree-based data-mining approach B. Merz et al. 10.5194/nhess-13-53-2013
24. Changes in flood damage with global warming on the eastern coast of Spain M. Cortès et al. 10.5194/nhess-19-2855-2019
25. A new approach to flood vulnerability assessment for historic buildings in England V. Stephenson & D. D'Ayala 10.5194/nhess-14-1035-2014
26. Bayesian network learning for natural hazard analyses K. Vogel et al. 10.5194/nhess-14-2605-2014
27. Identifying Driving Factors in Flood‐Damaging Processes Using Graphical Models K. Vogel et al. 10.1029/2018WR022858
28. How useful are complex flood damage models? K. Schröter et al. 10.1002/2013WR014396
29. From hazard to impact: flood damage assessment tools for mega cities A. Chen et al. 10.1007/s11069-016-2223-2
30. Drivers of flood risk change in residential areas F. Elmer et al. 10.5194/nhess-12-1641-2012
31. How do changes along the risk chain affect flood risk? A. Metin et al. 10.5194/nhess-18-3089-2018
32. A spatial Bayesian network model to assess the benefits of early warning for urban flood risk to people S. Balbi et al. 10.5194/nhess-16-1323-2016
33. Simulation of flood hazard and risk in the Danube basin with the Future Danube Model F. Hattermann et al. 10.1016/j.cliser.2018.07.001
34. Understanding the Costs of Inaction–An Assessment of Pluvial Flood Damages in Two European Cities H. Nicklin et al. 10.3390/w11040801
35. A novel expert opinion-based approach to compute estimations of flood damage to property in dense urban environments. Barcelona case study E. Martínez-Gomariz et al. 10.1016/j.jhydrol.2021.126244
36. Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes N. Sairam et al. 10.1029/2019WR025068
37. Assessment of flood loss model transferability considering changes in precaution of flood-affected residents in Germany S. Kienzler et al. 10.1051/e3sconf/20160713002
38. Development and evaluation of FLFAcs – A new Flood Loss Function for Australian commercial structures R. Hasanzadeh Nafari et al. 10.1016/j.ijdrr.2016.03.007
39. 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
40. 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
41. Large-scale flood risk assessment using a coupled model chain B. Merz et al. 10.1051/e3sconf/20160711005
42. Spatial Dependence Modeling of Flood Risk Using Max-Stable Processes: The Example of Austria H. Albrecher et al. 10.3390/w12061805
43. 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
44. Advancing flood damage modeling for coastal Alabama residential properties: A multivariable machine learning approach M. Museru et al. 10.1016/j.scitotenv.2023.167872
45. Flood risk assessments at different spatial scales H. de Moel et al. 10.1007/s11027-015-9654-z
46. An Assessment of the Effectiveness of Tree-Based Models for Multi-Variate Flood Damage Assessment in Australia R. Hasanzadeh Nafari et al. 10.3390/w8070282
47. The role of spatial dependence for large-scale flood risk estimation A. Metin et al. 10.5194/nhess-20-967-2020
48. RiskScape: a flexible multi-hazard risk modelling engine R. Paulik et al. 10.1007/s11069-022-05593-4
49. Regional and Temporal Transferability of Multivariable Flood Damage Models D. Wagenaar et al. 10.1029/2017WR022233
50. Mitigation of the Adverse Consequences of Floods for Human Life, Infrastructure, and the Environment M. Zeleňáková et al. 10.1061/(ASCE)NH.1527-6996.0000255
51. 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
52. A hurricane surge risk assessment framework using the joint probability method and surge response functions C. Hsu et al. 10.1007/s11069-017-3108-8
53. Economic Value of Flood Forecasts and Early Warning Systems: A Review G. Van Houtven 10.1061/NHREFO.NHENG-2094
54. Comparative flood damage model assessment: towards a European approach B. Jongman et al. 10.5194/nhess-12-3733-2012
55. A Consistent Approach for Probabilistic Residential Flood Loss Modeling in Europe S. Lüdtke et al. 10.1029/2019WR026213
56. How are flood risk estimates affected by the choice of return-periods? P. Ward et al. 10.5194/nhess-11-3181-2011
57. Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT‐FLEMO H. Kreibich et al. 10.1111/risa.12650
58. Evaluating the spatial application of multivariable flood damage models R. Paulik et al. 10.1111/jfr3.12934
59. The relationship between precipitation and insurance data for floods in a Mediterranean region (northeast Spain) M. Cortès et al. 10.5194/nhess-18-857-2018
60. Capturing Regional Differences in Flood Vulnerability Improves Flood Loss Estimation N. Sairam et al. 10.3389/frwa.2022.817625
61. A Probabilistic Analysis of Surface Water Flood Risk in London K. Jenkins et al. 10.1111/risa.12930
62. 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
63. What are the hydro-meteorological controls on flood characteristics? M. Nied et al. 10.1016/j.jhydrol.2016.12.003
64. Probabilistic Flood Loss Models for Companies L. Schoppa et al. 10.1029/2020WR027649
65. An Empirical, Functional approach to Depth Damages W. Lehman et al. 10.1051/e3sconf/20160705002
66. Scoring, selecting, and developing physical impact models for multi-hazard risk assessment R. Gentile et al. 10.1016/j.ijdrr.2022.103365
67. Multi-variable flood damage modelling with limited data using supervised learning approaches D. Wagenaar et al. 10.5194/nhess-17-1683-2017
68. How reliable are projections of future flood damage? P. Bubeck et al. 10.5194/nhess-11-3293-2011
69. Drivers of future fluvial flood risk change for residential buildings in Europe M. Steinhausen et al. 10.1016/j.gloenvcha.2022.102559
70. Multivariate pluvial flood damage models L. Van Ootegem et al. 10.1016/j.eiar.2015.05.005
71. The Delphi method to identify attributes for a valuation approach for residential property exposed to flood risk S. Zulkarnain & M. Razali 10.1108/PM-10-2020-0067
72. Tracing the value of data for flood loss modelling K. Schröter et al. 10.1051/e3sconf/20160705005
73. Safety Evaluation of a RC Structure with Multiple Openings under High Water Depth Inundations Y. Endo & T. Yasue 10.3390/app11094297
74. Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. 10.5194/nhess-21-643-2021
75. Floods in the north-western Mediterranean region: presentation of the HYMEX database and comparison with pre-existing global databases C. Llasat et al. 10.1051/lhb/2013001
76. Preface: Flood-risk analysis and integrated management P. Bubeck et al. 10.5194/nhess-16-1005-2016
77. 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