Dennis Wagenaar
Cited by
Cited by
Uncertainty in flood damage estimates and its potential effect on investment decisions.
DJ Wagenaar, KM De Bruijn, LM Bouwer, H Moel
Natural Hazards & Earth System Sciences 16 (1), 2016
Multi-variable flood damage modelling with limited data using supervised learning approaches
D Wagenaar, J Jong, LM Bouwer
Natural Hazards and Earth System Sciences 17 (9), 1683-1696, 2017
Regional and Temporal Transferability of Multivariable Flood Damage Models
D Wagenaar, S Lüdtke, K Schröter, LM Bouwer, H Kreibich
Water Resources Research 54 (5), 3688-3703, 2018
New, risk-based standards for flood protection in the Netherlands
H Van der Most, I Tánczos, KM De Bruijn, D Wagenaar
6th International Conference on Flood Management (ICFM6), 19-21, 2014
Room for Rivers: Risk Reduction by Enhancing the Flood Conveyance Capacity of The Netherlands’ Large Rivers
F Klijn, N Asselman, D Wagenaar
Geosciences 8 (6), 224, 2018
Evaluating adaptation measures for reducing flood risk: A case study in the city of Colombo, Sri Lanka
DJ Wagenaar, RJ Dahm, FLM Diermanse, WPS Dias, D Dissanayake, ...
International Journal of Disaster Risk Reduction 37, 101162, 2019
Development of damage functions for flood risk assessment in the city of Colombo (Sri Lanka)
P Dias, N Arambepola, K Weerasinghe, KDN Weerasinghe, D Wagenaar, ...
Procedia engineering 212, 332-339, 2018
Invited perspectives: How machine learning will change flood risk and impact assessment.
D Wagenaar, A Curran, M Balbi, A Bhardwaj, R Soden, E Hartato, ...
Natural Hazards & Earth System Sciences 20 (4), 2020
The significance of flood duration for flood damage assessment
DJ Wagenaar
A probabilistic approach to estimating residential losses from different flood types
D Paprotny, H Kreibich, O Morales-Nápoles, D Wagenaar, A Castellarin, ...
Natural Hazards, 1-33, 2020
Bayesian Data-Driven approach enhances synthetic flood loss models
N Sairam, K Schröter, F Carisi, D Wagenaar, A Domeneghetti, D Molinari, ...
Environmental Modelling & Software 132, 104798, 2020
Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction
D Wagenaar, T Hermawan, M van den Homberg, JCJH Aerts, H Kreibich, ...
Risk Analysis, 2020
Taking Ethics, Fairness, and Bias Seriously in Machine Learning for Disaster Risk Management
R Soden, D Wagenaar, D Luo, A Tjieesen
arXiv preprint arXiv:1912.05538, 2019
Flood exposure and vulnerability estimation methods for residential and commercial assets in Europe
D Paprotny, H Kreibich, O Morales-Nápoles, D Wagenaar, A Castellarin, ...
EGU General Assembly Conference Abstracts, 4753, 2020
Capturing Complexity: Transferable flood impact models with Machine Learning
DJ Wagenaar
Testing the cross-country transfer of multi-variable flood damage models
D Wagenaar, S Lüdtke, K Schröter, L Bouwer, H Kreibich
EGUGA, 7591, 2018
Cross-country transferability of multi-variable damage models
D Wagenaar, S Lüdtke, H Kreibich, L Bouwer
EGUGA, 4418, 2017
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