84 citations as recorded by crossref.

1. Multi-model ensembles for assessment of flood losses and associated uncertainty R. Figueiredo et al. https://doi.org/10.5194/nhess-18-1297-2018
2. Estimating exposure of residential assets to natural hazards in Europe using open data D. Paprotny et al. https://doi.org/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. https://doi.org/10.1186/s40562-024-00323-z
4. The object-specific flood damage database HOWAS 21 P. Kellermann et al. https://doi.org/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. https://doi.org/10.1007/s13753-024-00577-3
6. A review of flood damage analysis for a building structure and contents M. Marvi https://doi.org/10.1007/s11069-020-03941-w
7. Testing empirical and synthetic flood damage models: the case of Italy M. Amadio et al. https://doi.org/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 https://doi.org/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. https://doi.org/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. https://doi.org/10.1016/j.jhydrol.2015.02.021
11. Continuous, large‐scale simulation model for flood risk assessments: proof‐of‐concept D. Falter et al. https://doi.org/10.1111/jfr3.12105
12. Flood frequencies and durations and their response to El Niño Southern Oscillation: Global analysis P. Ward et al. https://doi.org/10.1016/j.jhydrol.2016.05.045
13. Bayesian Data-Driven approach enhances synthetic flood loss models N. Sairam et al. https://doi.org/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 https://doi.org/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. https://doi.org/10.3390/w6082367
16. Validation of flood risk models: Current practice and possible improvements D. Molinari et al. https://doi.org/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. https://doi.org/10.5194/nhess-13-1351-2013
18. Exploring the potential of multivariate depth‐damage and rainfall‐damage models L. Van Ootegem et al. https://doi.org/10.1111/jfr3.12284
19. Quantifying Flood Vulnerability Reduction via Private Precaution N. Sairam et al. https://doi.org/10.1029/2018EF000994
20. Adaptability and transferability of flood loss functions in residential areas H. Cammerer et al. https://doi.org/10.5194/nhess-13-3063-2013
21. A Review of Flood Loss Models as Basis for Harmonization and Benchmarking T. Gerl et al. https://doi.org/10.1371/journal.pone.0159791
22. A probabilistic approach to estimating residential losses from different flood types D. Paprotny et al. https://doi.org/10.1007/s11069-020-04413-x
23. Multi-variate flood damage assessment: a tree-based data-mining approach B. Merz et al. https://doi.org/10.5194/nhess-13-53-2013
24. Changes in flood damage with global warming on the eastern coast of Spain M. Cortès et al. https://doi.org/10.5194/nhess-19-2855-2019
25. A new approach to flood vulnerability assessment for historic buildings in England V. Stephenson & D. D'Ayala https://doi.org/10.5194/nhess-14-1035-2014
26. Bayesian network learning for natural hazard analyses K. Vogel et al. https://doi.org/10.5194/nhess-14-2605-2014
27. Identifying Driving Factors in Flood‐Damaging Processes Using Graphical Models K. Vogel et al. https://doi.org/10.1029/2018WR022858
28. How useful are complex flood damage models? K. Schröter et al. https://doi.org/10.1002/2013WR014396
29. From hazard to impact: flood damage assessment tools for mega cities A. Chen et al. https://doi.org/10.1007/s11069-016-2223-2
30. Drivers of flood risk change in residential areas F. Elmer et al. https://doi.org/10.5194/nhess-12-1641-2012
31. How do changes along the risk chain affect flood risk? A. Metin et al. https://doi.org/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. https://doi.org/10.5194/nhess-16-1323-2016
33. Unveiling the future: predicting unforeseen natural environmental disasters in the Mediterranean and Balkan areas in the face of climate change G. Halkos & A. Zisiadou https://doi.org/10.1007/s11069-025-07636-y
34. Simulation of flood hazard and risk in the Danube basin with the Future Danube Model F. Hattermann et al. https://doi.org/10.1016/j.cliser.2018.07.001
35. Understanding the Costs of Inaction–An Assessment of Pluvial Flood Damages in Two European Cities H. Nicklin et al. https://doi.org/10.3390/w11040801
36. 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. https://doi.org/10.1016/j.jhydrol.2021.126244
37. Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes N. Sairam et al. https://doi.org/10.1029/2019WR025068
38. Assessment of flood loss model transferability considering changes in precaution of flood-affected residents in Germany S. Kienzler et al. https://doi.org/10.1051/e3sconf/20160713002
39. Development and evaluation of FLFAcs – A new Flood Loss Function for Australian commercial structures R. Hasanzadeh Nafari et al. https://doi.org/10.1016/j.ijdrr.2016.03.007
40. Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale H. Kreibich et al. https://doi.org/10.5194/piahs-373-179-2016
41. Building-scale flood loss estimation through vulnerability pattern characterization: application to an urban flood in Milan, Italy A. Taramelli et al. https://doi.org/10.5194/nhess-22-3543-2022
42. Large-scale flood risk assessment using a coupled model chain B. Merz et al. https://doi.org/10.1051/e3sconf/20160711005
43. Spatial Dependence Modeling of Flood Risk Using Max-Stable Processes: The Example of Austria H. Albrecher et al. https://doi.org/10.3390/w12061805
44. Study on Influencing Factors of Flood Damage to Single Houses using Field Survey Data C. Choi et al. https://doi.org/10.9798/KOSHAM.2018.18.7.535
45. Advancing flood damage modeling for coastal Alabama residential properties: A multivariable machine learning approach M. Museru et al. https://doi.org/10.1016/j.scitotenv.2023.167872
46. A Novel and Practically Applicable Simulation–Optimization Framework for River Cross-Section Modification: Integrating the HEC-RAS Simulation with the Grasshopper Optimization Algorithm M. Malekpour et al. https://doi.org/10.1061/JHYEFF.HEENG-6567
47. Flood risk assessments at different spatial scales H. de Moel et al. https://doi.org/10.1007/s11027-015-9654-z
48. An Assessment of the Effectiveness of Tree-Based Models for Multi-Variate Flood Damage Assessment in Australia R. Hasanzadeh Nafari et al. https://doi.org/10.3390/w8070282
49. The role of spatial dependence for large-scale flood risk estimation A. Metin et al. https://doi.org/10.5194/nhess-20-967-2020
50. RiskScape: a flexible multi-hazard risk modelling engine R. Paulik et al. https://doi.org/10.1007/s11069-022-05593-4
51. Regional and Temporal Transferability of Multivariable Flood Damage Models D. Wagenaar et al. https://doi.org/10.1029/2017WR022233
52. Mitigation of the Adverse Consequences of Floods for Human Life, Infrastructure, and the Environment M. Zeleňáková et al. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000255
53. Surface water floods in Switzerland: what insurance claim records tell us about the damage in space and time D. Bernet et al. https://doi.org/10.5194/nhess-17-1659-2017
54. A hurricane surge risk assessment framework using the joint probability method and surge response functions C. Hsu et al. https://doi.org/10.1007/s11069-017-3108-8
55. Economic Value of Flood Forecasts and Early Warning Systems: A Review G. Van Houtven https://doi.org/10.1061/NHREFO.NHENG-2094
56. Comparative flood damage model assessment: towards a European approach B. Jongman et al. https://doi.org/10.5194/nhess-12-3733-2012
57. A Consistent Approach for Probabilistic Residential Flood Loss Modeling in Europe S. Lüdtke et al. https://doi.org/10.1029/2019WR026213
58. How are flood risk estimates affected by the choice of return-periods? P. Ward et al. https://doi.org/10.5194/nhess-11-3181-2011
59. Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT‐FLEMO H. Kreibich et al. https://doi.org/10.1111/risa.12650
60. Evaluating the spatial application of multivariable flood damage models R. Paulik et al. https://doi.org/10.1111/jfr3.12934
61. The relationship between precipitation and insurance data for floods in a Mediterranean region (northeast Spain) M. Cortès et al. https://doi.org/10.5194/nhess-18-857-2018
62. Capturing Regional Differences in Flood Vulnerability Improves Flood Loss Estimation N. Sairam et al. https://doi.org/10.3389/frwa.2022.817625
63. A Probabilistic Analysis of Surface Water Flood Risk in London K. Jenkins et al. https://doi.org/10.1111/risa.12930
64. Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures R. Hasanzadeh Nafari et al. https://doi.org/10.5194/nhess-17-1047-2017
65. What are the hydro-meteorological controls on flood characteristics? M. Nied et al. https://doi.org/10.1016/j.jhydrol.2016.12.003
66. Probabilistic Flood Loss Models for Companies L. Schoppa et al. https://doi.org/10.1029/2020WR027649
67. An Empirical, Functional approach to Depth Damages W. Lehman et al. https://doi.org/10.1051/e3sconf/20160705002
68. Scoring, selecting, and developing physical impact models for multi-hazard risk assessment R. Gentile et al. https://doi.org/10.1016/j.ijdrr.2022.103365
69. Multi-variable flood damage modelling with limited data using supervised learning approaches D. Wagenaar et al. https://doi.org/10.5194/nhess-17-1683-2017
70. How reliable are projections of future flood damage? P. Bubeck et al. https://doi.org/10.5194/nhess-11-3293-2011
71. Drivers of future fluvial flood risk change for residential buildings in Europe M. Steinhausen et al. https://doi.org/10.1016/j.gloenvcha.2022.102559
72. Multivariate pluvial flood damage models L. Van Ootegem et al. https://doi.org/10.1016/j.eiar.2015.05.005
73. The Delphi method to identify attributes for a valuation approach for residential property exposed to flood risk S. Zulkarnain & M. Razali https://doi.org/10.1108/PM-10-2020-0067
74. Event-Based Seismic Risk Assessment for Indonesia’s Post-Disaster Fund to Stimulate House Damage Recovery F. Atmaja et al. https://doi.org/10.20965/jdr.2025.p0765
75. BN-FLEMOΔ: a Bayesian-network-based flood loss estimation model for adaptation planning in Ho Chi Minh City, Vietnam K. Shahi et al. https://doi.org/10.5194/nhess-25-2845-2025
76. Tracing the value of data for flood loss modelling K. Schröter et al. https://doi.org/10.1051/e3sconf/20160705005
77. Safety Evaluation of a RC Structure with Multiple Openings under High Water Depth Inundations Y. Endo & T. Yasue https://doi.org/10.3390/app11094297
78. Are OpenStreetMap building data useful for flood vulnerability modelling? M. Cerri et al. https://doi.org/10.5194/nhess-21-643-2021
79. A quantitative methodology for analysing physical damage and recovery dynamics from concurrent and consecutive hazards: forensic insights from Puerto Rico A. Borre et al. https://doi.org/10.5194/nhess-26-4763-2026
80. Floods in the north-western Mediterranean region: presentation of the HYMEX database and comparison with pre-existing global databases C. Llasat et al. https://doi.org/10.1051/lhb/2013001
81. Preface: Flood-risk analysis and integrated management P. Bubeck et al. https://doi.org/10.5194/nhess-16-1005-2016
82. Calibration and validation of FLFArs -- a new flood loss function for Australian residential structures R. Hasanzadeh Nafari et al. https://doi.org/10.5194/nhess-16-15-2016
83. Key Drivers of Flash Flood Damage to Private Households D. Rodríguez Castro et al. https://doi.org/10.1111/jfr3.70088
84. Emerging strategies for addressing flood-damage modeling issues: A review S. Redondo-Tilano et al. https://doi.org/10.1016/j.ijdrr.2024.105058