Advances in machine learning for natural hazards risk assessment
Advances in machine learning for natural hazards risk assessment
Editor(s): Vitor Silva, Caroline M. Gevaert, David Lallemant, Sabine Loos, and Philip Ward More information

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01 Dec 2022
Comparison of machine learning techniques for reservoir outflow forecasting
Orlando García-Feal, José González-Cao, Diego Fernández-Nóvoa, Gonzalo Astray Dopazo, and Moncho Gómez-Gesteira
Nat. Hazards Earth Syst. Sci., 22, 3859–3874, https://doi.org/10.5194/nhess-22-3859-2022,https://doi.org/10.5194/nhess-22-3859-2022, 2022
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22 Nov 2022
Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides
Kamal Rana, Nishant Malik, and Ugur Ozturk
Nat. Hazards Earth Syst. Sci., 22, 3751–3764, https://doi.org/10.5194/nhess-22-3751-2022,https://doi.org/10.5194/nhess-22-3751-2022, 2022
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10 Nov 2022
Reduced order digital twin and latent data assimilation for global wildfire prediction
Caili Zhang, Sibo Cheng, Matthew Kasoar, and Rossella Arcucci
EGUsphere, https://doi.org/10.5194/egusphere-2022-1167,https://doi.org/10.5194/egusphere-2022-1167, 2022
Revised manuscript under review for NHESS (discussion: final response, 4 comments)
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28 Oct 2022
Review article: Current State of Deep Learning Application to Water-related Disaster Management in Developing Countries
Kola Yusuff Kareem, Yeonjeong Seong, Shiksha Bastola, and Younghun Jung
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-249,https://doi.org/10.5194/nhess-2022-249, 2022
Preprint under review for NHESS (discussion: open, 2 comments)
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24 Oct 2022
What weather variables are important for wet and slab avalanches under a changing climate in a low-altitude mountain range in Czechia?
Markéta Součková, Roman Juras, Kryštof Dytrt, Vojtěch Moravec, Johanna Ruth Blöcher, and Martin Hanel
Nat. Hazards Earth Syst. Sci., 22, 3501–3525, https://doi.org/10.5194/nhess-22-3501-2022,https://doi.org/10.5194/nhess-22-3501-2022, 2022
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10 Oct 2022
Probabilistic and Machine Learning Methods for Uncertainty Quantification in Power Outage Prediction due to Extreme Events
Prateek Arora and Luis Ceferino
EGUsphere, https://doi.org/10.5194/egusphere-2022-975,https://doi.org/10.5194/egusphere-2022-975, 2022
Preprint under review for NHESS (discussion: final response, 4 comments)
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04 Oct 2022
Machine learning nowcasting of the Vögelsberg deep-seated landslide: why predicting slow deformation is not so easy
Adriaan L. van Natijne, Thom A. Bogaard, Thomas Zieher, Jan Pfeiffer, and Roderik C. Lindenbergh
EGUsphere, https://doi.org/10.5194/egusphere-2022-950,https://doi.org/10.5194/egusphere-2022-950, 2022
Preprint under review for NHESS (discussion: open, 2 comments)
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16 Sep 2022
Machine learning models to predict myocardial infarctions from past climatic and environmental conditions
Lennart Marien, Mahyar Valizadeh, Wolfgang zu Castell, Christine Nam, Diana Rechid, Alexandra Schneider, Christine Meisinger, Jakob Linseisen, Kathrin Wolf, and Laurens M. Bouwer
Nat. Hazards Earth Syst. Sci., 22, 3015–3039, https://doi.org/10.5194/nhess-22-3015-2022,https://doi.org/10.5194/nhess-22-3015-2022, 2022
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01 Sep 2022
Development of a Seismic Loss Prediction Model for Residential Buildings using Machine Learning – Christchurch, New Zealand
Samuel Roeslin, Quincy Ma, Pavan Chigullapally, Joerg Wicker, and Liam Wotherspoon
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-227,https://doi.org/10.5194/nhess-2022-227, 2022
Preprint under review for NHESS (discussion: final response, 5 comments)
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20 Jul 2022
Using machine learning algorithms to identify predictors of social vulnerability in the event of an earthquake: Istanbul case study
Oya Kalaycioglu, Serhat Emre Akhanli, Emin Yahya Mentese, Mehmet Kalaycioglu, and Sibel Kalaycioglu
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-198,https://doi.org/10.5194/nhess-2022-198, 2022
Revised manuscript under review for NHESS (discussion: final response, 4 comments)
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13 Jul 2022
Forecasting the cost of drought events in France by super learning
Geoffrey Ecoto and Antoine Chambaz
EGUsphere, https://doi.org/10.5194/egusphere-2022-541,https://doi.org/10.5194/egusphere-2022-541, 2022
Revised manuscript under review for NHESS (discussion: final response, 10 comments)
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