Articles | Volume 23, issue 5
https://doi.org/10.5194/nhess-23-1665-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-23-1665-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Probabilistic and machine learning methods for uncertainty quantification in power outage prediction due to extreme events
Prateek Arora
CORRESPONDING AUTHOR
Civil and Urban Engineering Department, New York University, Brooklyn, NY 11201, USA
Luis Ceferino
Civil and Urban Engineering Department, New York University, Brooklyn, NY 11201, USA
Center for Urban Science and Progress, New York University, Brooklyn, NY 11201, USA
Related subject area
Risk Assessment, Mitigation and Adaptation Strategies, Socioeconomic and Management Aspects
Public intention to participate in sustainable geohazard mitigation: an empirical study based on an extended theory of planned behavior
An assessment of short–medium-term interventions using CAESAR-Lisflood in a post-earthquake mountainous area
Review article: Design and evaluation of weather index insurance for multi-hazard resilience and food insecurity
Design and application of a multi-hazard risk rapid assessment questionnaire for hill communities in the Indian Himalayan region
Identifying the drivers of private flood precautionary measures in Ho Chi Minh City, Vietnam
Performance of the flood warning system in Germany in July 2021 – insights from affected residents
Differences in volcanic risk perception among Goma's population before the Nyiragongo eruption of May 2021, Virunga volcanic province (DR Congo)
Empirical tsunami fragility modelling for hierarchical damage levels
Quantifying the potential benefits of risk-mitigation strategies on future flood losses in Kathmandu Valley, Nepal
Review article: Potential of nature-based solutions to mitigate hydro-meteorological risks in sub-Saharan Africa
Invited perspectives: An insurer's perspective on the knowns and unknowns in natural hazard risk modelling
Classifying marine faults for hazard assessment offshore Israel: a new approach based on fault size and vertical displacement
Assessing agriculture's vulnerability to drought in European pre-Alpine regions
Tsunami risk perception in central and southern Italy
Brief communication: Critical infrastructure impacts of the 2021 mid-July western European flood event
Multi-scenario urban flood risk assessment by integrating future land use change models and hydrodynamic models
Building-scale flood loss estimation through vulnerability pattern characterization: application to an urban flood in Milan, Italy
Process-based flood damage modelling relying on expert knowledge: a methodological contribution applied to the agricultural sector
Dynamic risk assessment of compound hazards based on VFS–IEM–IDM: a case study of typhoon–rainstorm hazards in Shenzhen, China
Integrated seismic risk assessment in Nepal
Machine learning models to predict myocardial infarctions from past climatic and environmental conditions
Reliability of flood marks and practical relevance for flood hazard assessment in southwestern Germany
Invited perspectives: Managed realignment as a solution to mitigate coastal flood risks – optimizing success through knowledge co-production
Invited perspectives: Views of 350 natural hazard community members on key challenges in natural hazards research and the Sustainable Development Goals
Estimating return intervals for extreme climate conditions related to winter disasters and livestock mortality in Mongolia
Surveying the surveyors to address risk perception and adaptive-behaviour cross-study comparability
Comparison of sustainable flood risk management by four countries – the United Kingdom, the Netherlands, the United States, and Japan – and the implications for Asian coastal megacities
Projected impact of heat on mortality and labour productivity under climate change in Switzerland
Full-scale experiments to examine the role of deadwood in rockfall dynamics in forests
Predicting drought and subsidence risks in France
Scenario-based multi-risk assessment from existing single-hazard vulnerability models. An application to consecutive earthquakes and tsunamis in Lima, Peru
The determinants affecting the intention of urban residents to prepare for flood risk in China
Strategic framework for natural disaster risk mitigation using deep learning and cost-benefit analysis
Risk communication during seismo-volcanic crises: the example of Mayotte, France
Invited perspectives: Challenges and step changes for natural hazard – perspectives from the German Committee for Disaster Reduction (DKKV)
Invited perspectives: When research meets practice: challenges, opportunities, and suggestions from the implementation of the Floods Directive in the largest Italian river basin
Rapid landslide risk zoning toward multi-slope units of the Neikuihui tribe for preliminary disaster management
INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium)
Effective uncertainty visualization for aftershock forecast maps
Invited perspectives: A research agenda towards disaster risk management pathways in multi-(hazard-)risk assessment
Education, financial aid, and awareness can reduce smallholder farmers' vulnerability to drought under climate change
Large-scale risk assessment on snow avalanche hazard in alpine regions
Regional county-level housing inventory predictions and the effects on hurricane risk
Brief communication: Key papers of 20 years in Natural Hazards and Earth System Sciences
Invited Perspectives: “Small country, big challenges – Switzerland's hazard prevention research”
Invited perspectives: Challenges and future directions in improving bridge flood resilience
Bangladesh's vulnerability to cyclonic coastal flooding
A geography of drought indices: mismatch between indicators of drought and its impacts on water and food securities
Cost–benefit analysis of coastal flood defence measures in the North Adriatic Sea
About the return period of a catastrophe
Huige Xing, Ting Que, Yuxin Wu, Shiyu Hu, Haibo Li, Hongyang Li, Martin Skitmore, and Nima Talebian
Nat. Hazards Earth Syst. Sci., 23, 1529–1547, https://doi.org/10.5194/nhess-23-1529-2023, https://doi.org/10.5194/nhess-23-1529-2023, 2023
Short summary
Short summary
Disaster risk reduction requires public power. The aim of this study is to investigate the factors influencing the public's intention to participate in disaster risk reduction. An empirical study was conducted using structural equation modeling data analysis methods. The findings show that public attitudes, perceptions of those around them, ability to participate, and sense of participation are important factors.
Di Wang, Ming Wang, Kai Liu, and Jun Xie
Nat. Hazards Earth Syst. Sci., 23, 1409–1423, https://doi.org/10.5194/nhess-23-1409-2023, https://doi.org/10.5194/nhess-23-1409-2023, 2023
Short summary
Short summary
The short–medium-term intervention effect on the post-earthquake area was analysed by simulations in different scenarios. The sediment transport patterns varied in different sub-regions, and the relative effectiveness in different scenarios changed over time with a general downward trend, where the steady stage implicated the scenario with more facilities performing better in controlling sediment output. Therefore, the simulation methods could support optimal rehabilitation strategies.
Marcos Roberto Benso, Gabriela Chiquito Gesualdo, Roberto Fray Silva, Greicelene Jesus Silva, Luis Miguel Castillo Rápalo, Fabricio Alonso Richmond Navarro, Patricia Angélica Alves Marques, José Antônio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 23, 1335–1354, https://doi.org/10.5194/nhess-23-1335-2023, https://doi.org/10.5194/nhess-23-1335-2023, 2023
Short summary
Short summary
This article is about how farmers can better protect themselves from disasters like droughts, extreme temperatures, and floods. The authors suggest that one way to do this is by offering insurance contracts that cover these different types of disasters. By having this insurance, farmers can receive financial support and recover more quickly. The article elicits different ideas about how to design this type of insurance and suggests ways to make it better.
Shivani Chouhan and Mahua Mukherjee
Nat. Hazards Earth Syst. Sci., 23, 1267–1286, https://doi.org/10.5194/nhess-23-1267-2023, https://doi.org/10.5194/nhess-23-1267-2023, 2023
Short summary
Short summary
The Himalayas are prone to multi-hazards. To minimise loss, proper planning and execution are necessary. Data collection is the basis of any risk assessment process. This enhanced survey form is easy to understand and pictorial and identifies high-risk components of any building (structural and non-structural) surrounded by multi-hazards. Its results can help to utilise the budget in a prioritised way. A SWOT (strengths, weaknesses, threats and opportunities) analysis has been performed.
Thulasi Vishwanath Harish, Nivedita Sairam, Liang Emlyn Yang, Matthias Garschagen, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 23, 1125–1138, https://doi.org/10.5194/nhess-23-1125-2023, https://doi.org/10.5194/nhess-23-1125-2023, 2023
Short summary
Short summary
Coastal Asian cities are becoming more vulnerable to flooding. In this study we analyse the data collected from flood-prone houses in Ho Chi Minh City to identify what motivates the households to adopt flood precautionary measures. The results revealed that educating the households about the available flood precautionary measures and communicating the flood protection measures taken by the government encourage the households to adopt measures without having to experience multiple flood events.
Annegret H. Thieken, Philip Bubeck, Anna Heidenreich, Jennifer von Keyserlingk, Lisa Dillenardt, and Antje Otto
Nat. Hazards Earth Syst. Sci., 23, 973–990, https://doi.org/10.5194/nhess-23-973-2023, https://doi.org/10.5194/nhess-23-973-2023, 2023
Short summary
Short summary
In July 2021 intense rainfall caused devastating floods in western Europe with 184 fatalities in the German federal states of North Rhine-Westphalia (NW) and Rhineland-Palatinate (RP), calling their warning system into question. An online survey revealed that 35 % of respondents from NW and 29 % from RP did not receive any warning. Many of those who were warned did not expect severe flooding, nor did they know how to react. The study provides entry points for improving Germany's warning system.
Blaise Mafuko Nyandwi, Matthieu Kervyn, François Muhashy Habiyaremye, François Kervyn, and Caroline Michellier
Nat. Hazards Earth Syst. Sci., 23, 933–953, https://doi.org/10.5194/nhess-23-933-2023, https://doi.org/10.5194/nhess-23-933-2023, 2023
Short summary
Short summary
Risk perception involves the processes of collecting, selecting and interpreting signals about the uncertain impacts of hazards. It may contribute to improving risk communication and motivating the protective behaviour of the population living near volcanoes. Our work describes the spatial variation and factors influencing volcanic risk perception of 2204 adults of Goma exposed to Nyiragongo. It contributes to providing a case study for risk perception understanding in the Global South.
Fatemeh Jalayer, Hossein Ebrahimian, Konstantinos Trevlopoulos, and Brendon Bradley
Nat. Hazards Earth Syst. Sci., 23, 909–931, https://doi.org/10.5194/nhess-23-909-2023, https://doi.org/10.5194/nhess-23-909-2023, 2023
Short summary
Short summary
Assessing tsunami fragility and the related uncertainties is crucial in the evaluation of incurred losses. Empirical fragility modelling is based on observed tsunami intensity and damage data. Fragility curves for hierarchical damage levels are distinguished by their laminar shape; that is, the curves should not intersect. However, this condition is not satisfied automatically. We present a workflow for hierarchical fragility modelling, uncertainty propagation and fragility model selection.
Carlos Mesta, Gemma Cremen, and Carmine Galasso
Nat. Hazards Earth Syst. Sci., 23, 711–731, https://doi.org/10.5194/nhess-23-711-2023, https://doi.org/10.5194/nhess-23-711-2023, 2023
Short summary
Short summary
Flood risk is expected to increase in many regions worldwide due to rapid urbanization and climate change. The benefits of risk-mitigation measures remain inadequately quantified for potential future events in some multi-hazard-prone areas such as Kathmandu Valley (KV), Nepal, which this paper addresses. The analysis involves modeling two flood occurrence scenarios and using four residential exposure inventories representing current urban system or near-future development trajectories for KV.
Kirk B. Enu, Aude Zingraff-Hamed, Mohammad A. Rahman, Lindsay C. Stringer, and Stephan Pauleit
Nat. Hazards Earth Syst. Sci., 23, 481–505, https://doi.org/10.5194/nhess-23-481-2023, https://doi.org/10.5194/nhess-23-481-2023, 2023
Short summary
Short summary
In sub-Saharan Africa, there is reported uptake of at least one nature-based solution (NBS) in 71 % of urban areas in the region for mitigating hydro-meteorological risks. These NBSs are implemented where risks exist but not where they are most severe. With these NBSs providing multiple ecosystem services and four out of every five NBSs creating livelihood opportunities, NBSs can help address major development challenges in the region, such as water and food insecurity and unemployment.
Madeleine-Sophie Déroche
Nat. Hazards Earth Syst. Sci., 23, 251–259, https://doi.org/10.5194/nhess-23-251-2023, https://doi.org/10.5194/nhess-23-251-2023, 2023
Short summary
Short summary
This paper proves the need to conduct an in-depth review of the existing loss modelling framework and makes it clear that only a transdisciplinary effort will be up to the challenge of building global loss models. These two factors are essential to capture the interactions and increasing complexity of the three risk drivers (exposure, hazard, and vulnerability), thus enabling insurers to anticipate and be equipped to face the far-ranging impacts of climate change and other natural events.
May Laor and Zohar Gvirtzman
Nat. Hazards Earth Syst. Sci., 23, 139–158, https://doi.org/10.5194/nhess-23-139-2023, https://doi.org/10.5194/nhess-23-139-2023, 2023
Short summary
Short summary
This study aims to provide a practical and relatively fast solution for early-stage planning of marine infrastructure that must cross a faulted zone. Instead of investing huge efforts in finding whether each specific fault meets a pre-defined criterion of activeness, we map the subsurface and determine the levels of fault hazard based on the amount of displacement and the fault's plane size. This allows for choosing the least problematic infrastructure routes at an early planning stage.
Ruth Stephan, Stefano Terzi, Mathilde Erfurt, Silvia Cocuccioni, Kerstin Stahl, and Marc Zebisch
Nat. Hazards Earth Syst. Sci., 23, 45–64, https://doi.org/10.5194/nhess-23-45-2023, https://doi.org/10.5194/nhess-23-45-2023, 2023
Short summary
Short summary
This study maps agriculture's vulnerability to drought in the European pre-Alpine regions of Thurgau (CH) and Podravska (SI). We combine region-specific knowledge with quantitative data mapping; experts of the study regions, far apart, identified a few common but more region-specific factors that we integrated in two vulnerability scenarios. We highlight the benefits of the participatory approach in improving the quantitative results and closing the gap between science and practitioners.
Lorenzo Cugliari, Massimo Crescimbene, Federica La Longa, Andrea Cerase, Alessandro Amato, and Loredana Cerbara
Nat. Hazards Earth Syst. Sci., 22, 4119–4138, https://doi.org/10.5194/nhess-22-4119-2022, https://doi.org/10.5194/nhess-22-4119-2022, 2022
Short summary
Short summary
The Tsunami Alert Centre of the National Institute of Geophysics and Volcanology (CAT-INGV) has been promoting the study of tsunami risk perception in Italy since 2018. A total of 7342 questionnaires were collected in three survey phases (2018, 2020, 2021). In this work we present the main results of the three survey phases, with a comparison among the eight surveyed regions and between the coastal regions and some coastal metropolitan cities involved in the survey.
Elco E. Koks, Kees C. H. van Ginkel, Margreet J. E. van Marle, and Anne Lemnitzer
Nat. Hazards Earth Syst. Sci., 22, 3831–3838, https://doi.org/10.5194/nhess-22-3831-2022, https://doi.org/10.5194/nhess-22-3831-2022, 2022
Short summary
Short summary
This study provides an overview of the impacts to critical infrastructure and how recovery has progressed after the July 2021 flood event in Germany, Belgium and the Netherlands. The results show that Germany and Belgium were particularly affected, with many infrastructure assets severely damaged or completely destroyed. This study helps to better understand how infrastructure can be affected by flooding and can be used for validation purposes for future studies.
Qinke Sun, Jiayi Fang, Xuewei Dang, Kepeng Xu, Yongqiang Fang, Xia Li, and Min Liu
Nat. Hazards Earth Syst. Sci., 22, 3815–3829, https://doi.org/10.5194/nhess-22-3815-2022, https://doi.org/10.5194/nhess-22-3815-2022, 2022
Short summary
Short summary
Flooding by extreme weather events and human activities can lead to catastrophic impacts in coastal areas. The research illustrates the importance of assessing the performance of different future urban development scenarios in response to climate change, and the simulation study of urban risks will prove to decision makers that incorporating disaster prevention measures into urban development plans will help reduce disaster losses and improve the ability of urban systems to respond to floods.
Andrea Taramelli, Margherita Righini, Emiliana Valentini, Lorenzo Alfieri, Ignacio Gatti, and Simone Gabellani
Nat. Hazards Earth Syst. Sci., 22, 3543–3569, https://doi.org/10.5194/nhess-22-3543-2022, https://doi.org/10.5194/nhess-22-3543-2022, 2022
Short summary
Short summary
This work aims to support decision-making processes to prioritize effective interventions for flood risk reduction and mitigation for the implementation of flood risk management concepts in urban areas. Our findings provide new insights into vulnerability spatialization of urban flood events for the residential sector, demonstrating that the nature of flood pathways varies spatially and is influenced by landscape characteristics, as well as building features.
Pauline Brémond, Anne-Laurence Agenais, Frédéric Grelot, and Claire Richert
Nat. Hazards Earth Syst. Sci., 22, 3385–3412, https://doi.org/10.5194/nhess-22-3385-2022, https://doi.org/10.5194/nhess-22-3385-2022, 2022
Short summary
Short summary
It is impossible to protect all issues against flood risk. To prioritise protection, economic analyses are conducted. The French Ministry of the Environment wanted to make available damage functions that we have developed for several sectors. For this, we propose a methodological framework and apply it to the model we have developed to assess damage to agriculture. This improves the description, validation, transferability and updatability of models based on expert knowledge.
Wenwu Gong, Jie Jiang, and Lili Yang
Nat. Hazards Earth Syst. Sci., 22, 3271–3283, https://doi.org/10.5194/nhess-22-3271-2022, https://doi.org/10.5194/nhess-22-3271-2022, 2022
Short summary
Short summary
We propose a model named variable fuzzy set and information diffusion (VFS–IEM–IDM) to assess the dynamic risk of compound hazards, which takes into account the interrelations between the hazard drivers, deals with the problem of data sparsity, and considers the temporal dynamics of the occurrences of the compound hazards. To examine the efficacy of the proposed VFS–IEM–IDM model, a case study of typhoon–rainstorm risks in Shenzhen, China, is presented.
Sanish Bhochhibhoya and Roisha Maharjan
Nat. Hazards Earth Syst. Sci., 22, 3211–3230, https://doi.org/10.5194/nhess-22-3211-2022, https://doi.org/10.5194/nhess-22-3211-2022, 2022
Short summary
Short summary
This is a comprehensive approach to risk assessment that considers the dynamic relationship between loss and damage. The study combines physical risk with social science to mitigate the disaster caused by earthquakes in Nepal, taking socioeconomical parameters into account such that the risk estimates can be monitored over time. The main objective is to recognize the cause of and solutions to seismic hazard, building the interrelationship between individual, natural, and built-in environments.
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
Short summary
Short summary
Myocardial infarctions (MIs; heart attacks) are influenced by temperature extremes, air pollution, lack of green spaces and ageing population. Here, we apply machine learning (ML) models in order to estimate the influence of various environmental and demographic risk factors. The resulting ML models can accurately reproduce observed annual variability in MI and inter-annual trends. The models allow quantification of the importance of individual factors and can be used to project future risk.
Annette Sophie Bösmeier, Iso Himmelsbach, and Stefan Seeger
Nat. Hazards Earth Syst. Sci., 22, 2963–2979, https://doi.org/10.5194/nhess-22-2963-2022, https://doi.org/10.5194/nhess-22-2963-2022, 2022
Short summary
Short summary
Encouraging a systematic use of flood marks for more comprehensive flood risk management, we collected a large number of marks along the Kinzig, southwestern Germany, and tested them for plausibility and temporal continuance. Despite uncertainty, the marks appeared to be an overall consistent and practical source that may also increase flood risk awareness. A wide agreement between the current flood hazard maps and the collected flood marks moreover indicated a robust local hazard assessment.
Mark Schuerch, Hannah L. Mossman, Harriet E. Moore, Elizabeth Christie, and Joshua Kiesel
Nat. Hazards Earth Syst. Sci., 22, 2879–2890, https://doi.org/10.5194/nhess-22-2879-2022, https://doi.org/10.5194/nhess-22-2879-2022, 2022
Short summary
Short summary
Coastal nature-based solutions to adapt to sea-level rise, such as managed realignments (MRs), are becoming increasingly popular amongst scientists and coastal managers. However, local communities often oppose these projects, partly because scientific evidence for their efficiency is limited. Here, we propose a framework to work with stakeholders and communities to define success variables of MR projects and co-produce novel knowledge on the projects’ efficiency to mitigate coastal flood risks.
Robert Šakić Trogrlić, Amy Donovan, and Bruce D. Malamud
Nat. Hazards Earth Syst. Sci., 22, 2771–2790, https://doi.org/10.5194/nhess-22-2771-2022, https://doi.org/10.5194/nhess-22-2771-2022, 2022
Short summary
Short summary
Here we present survey responses of 350 natural hazard community members to key challenges in natural hazards research and step changes to achieve the Sustainable Development Goals. Challenges identified range from technical (e.g. model development, early warning) to governance (e.g. co-production with community members). Step changes needed are equally broad; however, the majority of answers showed a need for wider stakeholder engagement, increased risk management and interdisciplinary work.
Masahiko Haraguchi, Nicole Davi, Mukund Palat Rao, Caroline Leland, Masataka Watanabe, and Upmanu Lall
Nat. Hazards Earth Syst. Sci., 22, 2751–2770, https://doi.org/10.5194/nhess-22-2751-2022, https://doi.org/10.5194/nhess-22-2751-2022, 2022
Short summary
Short summary
Mass livestock mortality during severe winters (dzud in Mongolian) is a compound event. Summer droughts are a precondition for dzud. We estimate the return levels of relevant variables: summer drought conditions and minimum winter temperature. The result shows that the return levels of drought conditions vary over time. Winter severity, however, is constant. We link climatic factors to socioeconomic impacts and draw attention to the need for index insurance.
Samuel Rufat, Mariana Madruga de Brito, Alexander Fekete, Emeline Comby, Peter J. Robinson, Iuliana Armaş, W. J. Wouter Botzen, and Christian Kuhlicke
Nat. Hazards Earth Syst. Sci., 22, 2655–2672, https://doi.org/10.5194/nhess-22-2655-2022, https://doi.org/10.5194/nhess-22-2655-2022, 2022
Short summary
Short summary
It remains unclear why people fail to act adaptively to reduce future losses, even when there is ever-richer information available. To improve the ability of researchers to build cumulative knowledge, we conducted an international survey – the Risk Perception and Behaviour Survey of Surveyors (Risk-SoS). We find that most studies are exploratory and often overlook theoretical efforts that would enable the accumulation of evidence. We offer several recommendations for future studies.
Faith Ka Shun Chan, Liang Emlyn Yang, Gordon Mitchell, Nigel Wright, Mingfu Guan, Xiaohui Lu, Zilin Wang, Burrell Montz, and Olalekan Adekola
Nat. Hazards Earth Syst. Sci., 22, 2567–2588, https://doi.org/10.5194/nhess-22-2567-2022, https://doi.org/10.5194/nhess-22-2567-2022, 2022
Short summary
Short summary
Sustainable flood risk management (SFRM) has become popular since the 1980s. This study examines the past and present flood management experiences in four developed countries (UK, the Netherlands, USA, and Japan) that have frequently suffered floods. We analysed ways towards SFRM among Asian coastal cities, which are still reliant on a hard-engineering approach that is insufficient to reduce future flood risk. We recommend stakeholders adopt mixed options to undertake SFRM practices.
Zélie Stalhandske, Valentina Nesa, Marius Zumwald, Martina S. Ragettli, Alina Galimshina, Niels Holthausen, Martin Röösli, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 22, 2531–2541, https://doi.org/10.5194/nhess-22-2531-2022, https://doi.org/10.5194/nhess-22-2531-2022, 2022
Short summary
Short summary
We model the impacts of heat on both mortality and labour productivity in Switzerland in a changing climate. We estimate 658 heat-related death currently per year in Switzerland and CHF 665 million in losses in labour productivity. Should we remain on a high-emissions pathway, these values may double or even triple by the end of the century. Under a lower-emissions scenario impacts are expected to slightly increase and peak by around mid-century.
Adrian Ringenbach, Elia Stihl, Yves Bühler, Peter Bebi, Perry Bartelt, Andreas Rigling, Marc Christen, Guang Lu, Andreas Stoffel, Martin Kistler, Sandro Degonda, Kevin Simmler, Daniel Mader, and Andrin Caviezel
Nat. Hazards Earth Syst. Sci., 22, 2433–2443, https://doi.org/10.5194/nhess-22-2433-2022, https://doi.org/10.5194/nhess-22-2433-2022, 2022
Short summary
Short summary
Forests have a recognized braking effect on rockfalls. The impact of lying deadwood, however, is mainly neglected. We conducted 1 : 1-scale rockfall experiments in three different states of a spruce forest to fill this knowledge gap: the original forest, the forest including lying deadwood and the cleared area. The deposition points clearly show that deadwood has a protective effect. We reproduced those experimental results numerically, considering three-dimensional cones to be deadwood.
Arthur Charpentier, Molly James, and Hani Ali
Nat. Hazards Earth Syst. Sci., 22, 2401–2418, https://doi.org/10.5194/nhess-22-2401-2022, https://doi.org/10.5194/nhess-22-2401-2022, 2022
Short summary
Short summary
Predicting consequences of drought episodes is complex, all the more when focusing on subsidence. We use 20 years of insurer data to derive a model to predict both the intensity and the severity of such events, using geophysical and climatic information located in space and time.
Juan Camilo Gómez Zapata, Massimiliano Pittore, Nils Brinckmann, Juan Lizarazo-Marriaga, Sergio Medina, Nicola Tarque, and Fabrice Cotton
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-183, https://doi.org/10.5194/nhess-2022-183, 2022
Revised manuscript accepted for NHESS
Short summary
Short summary
To investigate cumulative damage on extended building portfolios, we propose an alternative and modular method to probabilistically integrate sets of single-hazard vulnerability models that are being constantly developed by experts from various research fields to be used within a multi-risk context. We demonstrate its application by assessing the economic losses expected for the residential building stock of Lima, Peru, a megacity commonly exposed to consecutive earthquake and tsunami scenarios.
Tiantian Wang, Yunmeng Lu, Tiezhong Liu, Yujiang Zhang, Xiaohan Yan, and Yi Liu
Nat. Hazards Earth Syst. Sci., 22, 2185–2199, https://doi.org/10.5194/nhess-22-2185-2022, https://doi.org/10.5194/nhess-22-2185-2022, 2022
Short summary
Short summary
To identify the main determinants influencing urban residents' intention to prepare for flood risk in China, we developed an integrated theoretical framework based on protection motivation theory (PMT) and validated it with structural equation modeling. The results showed that both threat perception and coping appraisal were effective in increasing residents' intention to prepare. In addition, individual heterogeneity and social context also had an impact on preparedness intentions.
Ji-Myong Kim, Sang-Guk Yum, Hyunsoung Park, and Junseo Bae
Nat. Hazards Earth Syst. Sci., 22, 2131–2144, https://doi.org/10.5194/nhess-22-2131-2022, https://doi.org/10.5194/nhess-22-2131-2022, 2022
Short summary
Short summary
Insurance data has been utilized with deep learning techniques to predict natural disaster damage losses in South Korea.
Maud Devès, Robin Lacassin, Hugues Pécout, and Geoffrey Robert
Nat. Hazards Earth Syst. Sci., 22, 2001–2029, https://doi.org/10.5194/nhess-22-2001-2022, https://doi.org/10.5194/nhess-22-2001-2022, 2022
Short summary
Short summary
This paper focuses on the issue of population information about natural hazards and disaster risk. It builds on the analysis of the unique seismo-volcanic crisis on the island of Mayotte, France, that started in May 2018 and lasted several years. We document the gradual response of the actors in charge of scientific monitoring and risk management. We then make recommendations for improving risk communication strategies in Mayotte and also in contexts where comparable geo-crises may happen.
Benni Thiebes, Ronja Winkhardt-Enz, Reimund Schwarze, and Stefan Pickl
Nat. Hazards Earth Syst. Sci., 22, 1969–1972, https://doi.org/10.5194/nhess-22-1969-2022, https://doi.org/10.5194/nhess-22-1969-2022, 2022
Short summary
Short summary
The worldwide challenge of the present as well as the future is to navigate the global community to a sustainable and secure future. Humanity is increasingly facing multiple risks under more challenging conditions. The continuation of climate change and the ever more frequent occurrence of extreme, multi-hazard, and cascading events are interacting with increasingly complex and interconnected societies.
Tommaso Simonelli, Laura Zoppi, Daniela Molinari, and Francesco Ballio
Nat. Hazards Earth Syst. Sci., 22, 1819–1823, https://doi.org/10.5194/nhess-22-1819-2022, https://doi.org/10.5194/nhess-22-1819-2022, 2022
Short summary
Short summary
The paper discusses challenges (and solutions) emerged during a collaboration among practitioners, stakeholders, and scientists in the definition of flood damage maps in the Po River District. Social aspects were proven to be fundamental components of the risk assessment; variety of competences in the working group was key in finding solutions and revealing weaknesses of intermediate proposals. This paper finally highlights the need of duplicating such an experience at a broader European level.
Chih-Chung Chung and Zih-Yi Li
Nat. Hazards Earth Syst. Sci., 22, 1777–1794, https://doi.org/10.5194/nhess-22-1777-2022, https://doi.org/10.5194/nhess-22-1777-2022, 2022
Short summary
Short summary
The Neikuihui tribe in northern Taiwan faces landslides during rainfall events. Since the government needs to respond with disaster management for the most at-risk tribes, this study develops rapid risk zoning, which involves the susceptibility, activity, exposure, and vulnerability of each slope unit of the area. Results reveal that one of the slope units of the Neikuihui tribal area has a higher risk and did suffer a landslide during the typhoon in 2016.
Anna Rita Scorzini, Benjamin Dewals, Daniela Rodriguez Castro, Pierre Archambeau, and Daniela Molinari
Nat. Hazards Earth Syst. Sci., 22, 1743–1761, https://doi.org/10.5194/nhess-22-1743-2022, https://doi.org/10.5194/nhess-22-1743-2022, 2022
Short summary
Short summary
This study presents a replicable procedure for the adaptation of synthetic, multi-variable flood damage models among countries that may have different hazard and vulnerability features. The procedure is exemplified here for the case of adaptation to the Belgian context of a flood damage model, INSYDE, for the residential sector, originally developed for Italy. The study describes necessary changes in model assumptions and input parameters to properly represent the new context of implementation.
Max Schneider, Michelle McDowell, Peter Guttorp, E. Ashley Steel, and Nadine Fleischhut
Nat. Hazards Earth Syst. Sci., 22, 1499–1518, https://doi.org/10.5194/nhess-22-1499-2022, https://doi.org/10.5194/nhess-22-1499-2022, 2022
Short summary
Short summary
Aftershock forecasts are desired for risk response, but public communications often omit their uncertainty. We evaluate three uncertainty visualization designs for aftershock forecast maps. In an online experiment, participants complete map-reading and judgment tasks relevant across natural hazards. While all designs reveal which areas are likely to have many or no aftershocks, one design can also convey that areas with high uncertainty can have more aftershocks than forecasted.
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
Short summary
Short summary
The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Marthe L. K. Wens, Anne F. van Loon, Ted I. E. Veldkamp, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 22, 1201–1232, https://doi.org/10.5194/nhess-22-1201-2022, https://doi.org/10.5194/nhess-22-1201-2022, 2022
Short summary
Short summary
In this paper, we present an application of the empirically calibrated drought risk adaptation model ADOPT for the case of smallholder farmers in the Kenyan drylands. ADOPT is used to evaluate the effect of various top-down drought risk reduction interventions (extension services, early warning systems, ex ante cash transfers, and low credit rates) on individual and community drought risk (adaptation levels, food insecurity, poverty, emergency aid) under different climate change scenarios.
Gregor Ortner, Michael Bründl, Chahan M. Kropf, Thomas Röösli, Yves Bühler, and David N. Bresch
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-112, https://doi.org/10.5194/nhess-2022-112, 2022
Revised manuscript accepted for NHESS
Short summary
Short summary
This paper presents a new approach to assess avalanche risk on a large scale in mountainous regions. It combines a large scale avalanche modeling method with a state of the art probilistic risk tool. Over 40'000 individual avalanches were simulated and a building dataset with over 13'000 single buildings was investigated. With this new method, risk hotspots can be identified and surveyed. This enables current and future risk analysis to assist decision makers in risk reduction and adaptation.
Caroline J. Williams, Rachel A. Davidson, Linda K. Nozick, Joseph E. Trainor, Meghan Millea, and Jamie L. Kruse
Nat. Hazards Earth Syst. Sci., 22, 1055–1072, https://doi.org/10.5194/nhess-22-1055-2022, https://doi.org/10.5194/nhess-22-1055-2022, 2022
Short summary
Short summary
A neural network model based on publicly available data was developed to forecast the number of housing units for each of 1000 counties in the southeastern United States in each of the next 20 years. The estimated number of housing units is almost always (97 % of the time) less than 1 percentage point different than the observed number, which are predictive errors acceptable for most practical purposes. The housing unit projections can help quantify changes in future expected hurricane impacts.
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, https://doi.org/10.5194/nhess-22-985-2022, 2022
Short summary
Short summary
To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
Dorothea Wabbels and Gian Reto Bezzola
Nat. Hazards Earth Syst. Sci., 22, 927–930, https://doi.org/10.5194/nhess-22-927-2022, https://doi.org/10.5194/nhess-22-927-2022, 2022
Short summary
Short summary
Due to its geography and climate, densely populated Switzerland is often affected by water-related hazards such as surface runoff, floods, debris flows, landslides, rockfalls and avalanches. Almost every part of Switzerland is exposed to natural hazards, and anyone can be affected.
Enrico Tubaldi, Christopher J. White, Edoardo Patelli, Stergios Aristoteles Mitoulis, Gustavo de Almeida, Jim Brown, Michael Cranston, Martin Hardman, Eftychia Koursari, Rob Lamb, Hazel McDonald, Richard Mathews, Richard Newell, Alonso Pizarro, Marta Roca, and Daniele Zonta
Nat. Hazards Earth Syst. Sci., 22, 795–812, https://doi.org/10.5194/nhess-22-795-2022, https://doi.org/10.5194/nhess-22-795-2022, 2022
Short summary
Short summary
Bridges are critical infrastructure components of transport networks. A large number of these critical assets cross or are adjacent to waterways and are therefore exposed to the potentially devastating impact of floods. This paper discusses a series of issues and areas where improvements in research and practice are required in the context of risk assessment and management of bridges exposed to flood hazard, with the ultimate goal of guiding future efforts in improving bridge flood resilience.
Aurélia Bernard, Nathalie Long, Mélanie Becker, Jamal Khan, and Sylvie Fanchette
Nat. Hazards Earth Syst. Sci., 22, 729–751, https://doi.org/10.5194/nhess-22-729-2022, https://doi.org/10.5194/nhess-22-729-2022, 2022
Short summary
Short summary
This article reviews current scientific literature in order to define vulnerability in the context of coastal Bangladesh facing cyclonic flooding. A new metric, called the socio-spatial vulnerability index, is defined as a function of both the probability of the cyclonic flood hazard and the sensitivity of delta inhabitants. The main result shows that three very densely populated districts, located in the Ganges delta tidal floodplain, are highly vulnerable to cyclonic flooding.
Sarra Kchouk, Lieke A. Melsen, David W. Walker, and Pieter R. van Oel
Nat. Hazards Earth Syst. Sci., 22, 323–344, https://doi.org/10.5194/nhess-22-323-2022, https://doi.org/10.5194/nhess-22-323-2022, 2022
Short summary
Short summary
The aim of our study was to question the validity of the assumed direct linkage between drivers of drought and its impacts on water and food securities, mainly found in the frameworks of drought early warning systems (DEWSs). We analysed more than 5000 scientific studies leading us to the conclusion that the local context can contribute to drought drivers resulting in these drought impacts. Our research aims to increase the relevance and utility of the information provided by DEWSs.
Mattia Amadio, Arthur H. Essenfelder, Stefano Bagli, Sepehr Marzi, Paolo Mazzoli, Jaroslav Mysiak, and Stephen Roberts
Nat. Hazards Earth Syst. Sci., 22, 265–286, https://doi.org/10.5194/nhess-22-265-2022, https://doi.org/10.5194/nhess-22-265-2022, 2022
Short summary
Short summary
We estimate the risk associated with storm surge events at two case study locations along the North Adriatic Italian coast, considering sea level rise up to the year 2100, and perform a cost–benefit analysis of planned or proposed coastal renovation projects. The study uses nearshore hydrodynamic modelling. Our findings represent a useful indication for disaster risk management, helping to understand the importance of investing in adaptation and estimating the economic return on investments.
Mathias Raschke
Nat. Hazards Earth Syst. Sci., 22, 245–263, https://doi.org/10.5194/nhess-22-245-2022, https://doi.org/10.5194/nhess-22-245-2022, 2022
Short summary
Short summary
We develop the combined return period to stochastically measure hazard and catastrophe events. This is used to estimate a risk curve by stochastic scaling of historical events and averaging corresponding risk parameters in combination with a vulnerability model. We apply the method to extratropical cyclones over Germany and estimate the risk for insured losses. The results are strongly influenced by assumptions about spatial dependence.
Cited articles
Ahsanullah, M., Kibria, B. M. G., and Shakil, M.: Normal Distribution,
7–50, https://link.springer.com/chapter/10.2991/978-94-6239-061-4_2 (last access: 21 September 2022), 2014. a
AJOT: Hurricane Ida caused at least 1.2 million electricity customers to
lose power | AJOT.COM, https://ajot.com/news/hurricane-ida-caused-at-least-1.2-million-electricity-customers-to-lose-power (last access: 21 September, 2022),
2021. a
Arab, A., Khodaei, A., Khator, S. K., and Han, Z.: Electric Power Grid
Restoration Considering Disaster Economics, IEEE Access, 4, 639–649,
https://doi.org/10.1109/ACCESS.2016.2523545, 2016. a
Bjarnadottir, S., Li, Y., and Stewart, M. G.: Hurricane Risk Assessment of
Power Distribution Poles Considering Impacts of a Changing Climate, J. Infrastruct. Sys., 19, 12–24,
https://doi.org/10.1061/(asce)is.1943-555x.0000108, 2013. a, b, c
Brown, R. E.: Electric Power Distribution Reliability,
https://doi.org/10.1201/9780849375682), 2002. a, b, c
Cai, J., Luo, J., Wang, S., and Yang, S.: Feature selection in machine
learning: A new perspective, Neurocomputing, 300, 70–79,
https://doi.org/10.1016/j.neucom.2017.11.077, 2018. a
Cameron, A. C. and Windmeijer, F. A.: R-squared measures for count data
regression models with applications to health-care utilization,
J. Bus. Econ. Stat., 14, 209–220,
https://doi.org/10.1080/07350015.1996.10524648, 1996. a, b, c
Casey, S.: The United States, The Ashgate Research Companion to the Korean
War, 49–60 pp., https://doi.org/10.1007/978-1-349-08679-5_5, 2016. a
Ceferino, L., Kiremidjian, A., and Deierlein, G.: Regional Multiseverity
Casualty Estimation Due to Building Damage following a Mw 8.8 Earthquake
Scenario in Lima, Peru, Earthq. Spectra, 34, 1739–1761,
https://doi.org/10.1193/080617EQS154M, 2018. a
Ceferino, L., Mitrani-Reiser, J., Kiremidjian, A., Deierlein, G., and
Bambarén, C.: Effective plans for hospital system response to
earthquake emergencies, Nat. Commun., 11, 1–12,
https://doi.org/10.1038/s41467-020-18072-w, 2020. a
Chapman, L.: Assessing topographic exposure, Meteorol. Appl., 7,
335–340, https://doi.org/10.1017/S1350482700001729, 2000. a, b
Chavas, D. R., Lin, N., and Emanuel, K.: A model for the complete radial
structure of the tropical cyclone wind field. Part I: Comparison with
observed structure, J. Atmos. Sci., 72, 3647–3662,
https://doi.org/10.1175/JAS-D-15-0014.1, 2015. a, b
Congress.gov: H.R.5760 – 116th Congress (2019-2020): Grid Security Research
and Development Act | Congress.gov | Library of Congress,
https://www.congress.gov/bill/116th-congress/house-bill/5760 (last access: 21 September 2022),
2020. a
EIA.GOV: U.S. Energy Information Administration – EIA – Independent
Statistics and Analysis,
https://www.eia.gov/todayinenergy/detail.php?id=37332 (last access: last access: 21 September 2022), 2018. a
Elamrouss, A.: 75% of power outages reported in Louisiana after Hurricane
Ida have been restored, governor says | CNN,
https://www.cnn.com/2021/09/09/us/hurricane-ida-aftermath-louisiana-thursday/index.html (last access: last access: 21 September 2022),
2021. a
Eskandarpour, R. and Khodaei, A.: Leveraging accuracy-uncertainty tradeoff in
SVM to achieve highly accurate outage predictions,
IEEE T. Power Syst., 33, 1139–1141, https://doi.org/10.1109/TPWRS.2017.2759061, 2018. a
Eskandarpour, R., Khodaei, A., Paaso, A., and Abdullah, N. M.: Artificial
Intelligence Assisted Power Grid Hardening in Response to Extreme Weather
Events, Cornell University, https://doi.org/10.48550/arxiv.1810.02866, 2018. a
Ferrari, S. L. and Cribari-Neto, F.: Beta Regression for Modelling Rates and
Proportions, 31, 799–815,
https://doi.org/10.1080/0266476042000214501, 2010. a
Guttman, N. B.: Comparing the palmer drought index and the standardized
precipitation index, J. Am. Water Resour. As.,
34, 113–121, https://doi.org/10.1111/j.1752-1688.1998.tb05964.x, 1998. a
Hall, D. B.: Zero-Inflated Poisson and Binomial Regression with Random
Effects: A Case Study, Biometrics, 56, 1030–1039,
https://doi.org/10.1111/J.0006-341X.2000.01030.X, 2000. a
Han, S. R., Guikema, S. D., Quiring, S. M., Lee, K. H., Rosowsky, D., and
Davidson, R. A.: Estimating the spatial distribution of power outages during
hurricanes in the Gulf coast region,
Reliab. Eng. Syst. Safe., 94, 199–210, https://doi.org/10.1016/j.ress.2008.02.018, 2009b. a, b, c, d, e, f, g, h, i, j, k
Haseltine, C. and Eman, E. E. S.: Prediction of power grid failure using
neural network learning, Proceedings – 16th IEEE International Conference on
Machine Learning and Applications, ICMLA 2017, 2017–December, 505–510,
https://doi.org/10.1109/ICMLA.2017.0-111, 2017. a
Hosking, J. R. M. and Wallis, J. R.: Regional Frequency Analysis: An Approach
Based on L-Moments, Cambridge University Press, 191–209,
https://doi.org/10.1017/CBO9780511529443, 1997. a
Jaech, A., Zhang, B., Ostendorf, M., and Kirschen, D. S.: Real-Time Prediction
of the Duration of Distribution System Outages,
http://arxiv.org/abs/1804.01189 (last access: 20 January 2023), 2018. a
Kankanala, P., Das, S., and Pahwa, A.: Adaboost+: An ensemble learning
approach for estimating weather-related outages in distribution systems,
IEEE T. Power Syst., 29, 359–367,
https://doi.org/10.1109/TPWRS.2013.2281137, 2014. a, b
Kohavi, R. and John, G. H.: Wrappers for feature subset selection, Artif. Intell., 97, 273–324, https://doi.org/10.1016/S0004-3702(97)00043-X, 1997. a
Krist Jr., F. J., Ellenwood, J. R., Woods, M. E., Mcmahan, A. J., Cowardin,
J. P., Ryerson, D. E., Sapio, F. J., Zweifler, M. O., and Romero, S. A.:
2013–2027 National Insect and Disease Forest Risk Assessment, 87–92, https://doi.org/10.2737/SRS-GTR-209, 2014. a, b
Latto, A., Hagen, A., and Berg, R.: National Hurricane Center Tropical Cyclone
Report. Hurricane Isaias, 1–32 pp., https://www.nhc.noaa.gov/data/tcr/AL092020_Isaias.pdf (last access: 21 September 2022), 2021. a
Li, R. and Peng, L.: Quantile Regression for Left-Truncated Semicompeting
Risks Data, Biometrics, 67, 701–710,
https://doi.org/10.1111/j.1541-0420.2010.01521.x, 2011. a
Liu, H., Davidson, R. A., and Apanasovich, T. V.: Statistical forecasting of
electric power restoration times in hurricanes and ice storms, IEEE
Trans. Power Syst., 22, 2270–2279,
https://doi.org/10.1109/TPWRS.2007.907587, 2007. a, b, c, d
Liu, H., Davidson, R. A., and Apanasovich, T. V.: Spatial generalized linear
mixed models of electric power outages due to hurricanes and ice storms,
Reliab. Eng. Syst. Safe., 93, 897–912,
https://doi.org/10.1016/j.ress.2007.03.038, 2008. a, b, c
Maderia, C. M.: Importance of Tree Species and Precipitation for Modeling
Hurricane-induced Power Outages,
https://oaktrust.library.tamu.edu/handle/1969.1/155728 (last access: 21 September 2022), 2015. a
Meinshausen, N.: Quantile Regression Forests, J. Mach. Learn.
Res., 7, 983–999, 2006. a
Miller, C., Gibbons, M., Beatty, K., and Boissonnade, A.: Topographic speed-up
effects and observed roof damage on Bermuda following Hurricane Fabian
(2003), Weather Forecast., 28, 159–174,
https://doi.org/10.1175/WAF-D-12-00050.1, 2013. a, b
MRLC: All NLCD Land Cover 2019 CONUS Land Cover, MRLC [data set], https://www.mrlc.gov/viewer/ (last access: 21 September, 2022), 2023. a
Napoli, A., Crespi, A., Ragone, F., Maugeri, M., and Pasquero, C.: Variability
of orographic enhancement of precipitation in the Alpine region, Sci.
Rep., 9, 13352, https://doi.org/10.1038/S41598-019-49974-5, 2019. a
National Academies of Sciences, Engineering, and Medicine: Enhancing the
Resilience of the Nation's Electricity System, Enhancing the Resilience of
the Nation's Electricity System, The National Academies Press, 170 pp., https://doi.org/10.17226/24836, 2017. a, b, c
Ouyang, M. and Dueñas-Osorio, L.: Multi-dimensional hurricane resilience
assessment of electric power systems, Struct. Saf., 48, 15–24,
https://doi.org/10.1016/j.strusafe.2014.01.001, 2014. a, b
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J.,
Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.:
Scikit-learn: Machine Learning in {P}ython, J. Mach.
Learn. Res., 12, 2825–2830, 2011. a, b
Petersen, H. C.: Electricity Consumption in Rural Vs. Urban Areas,
Western J. Agr. Econ., 07, 13–18,
http://econpapers.repec.org/RePEc:ags:wjagec:32417 (last access: 21 September 2022), 1982. a
PowerOutage.us: Electric customers
without power, PowerOutage.us [data set], https://poweroutage.us/ (last access: 21 September 2022), 2023. a
Quiring, S. M., Zhu, L., and Guikema, S. D.: Importance of soil and elevation
characteristics for modeling hurricane-induced power outages, Nat.
Hazards, 58, 365–390, https://doi.org/10.1007/s11069-010-9672-9, 2011. a, b, c
Rivera, I., Mckay, R., and Disavino, S.: Puerto Rico power grid no match for
Fiona; residents unsurprised | Reuters,
https://www.reuters.com/business/environment (last access: 21 September 2022),
2022. a
Rudin, C., Waltz, D., Anderson, R., Boulanger, A., Salleb-Aouissi, A., Chow,
M., Dutta, H., Gross, P., Huang, B., Ierome, S., Isaac, D. F., Kressner, A.,
Passonneau, R. J., Radeva, A., and Wu, L.: Machine learning for the New York
City power grid, IEEE T. Pattern Anal., 34, 328–345, https://doi.org/10.1109/TPAMI.2011.108, 2012. a
Sheppard, D. and DiSavino, S.: Superstorm Sandy cuts power to 8.1 million
homes | Reuters,
https://www.reuters.com/article/us-storm-sandy-powercuts (last access: 21 September 2022),
2012. a
Smith, A. B.: U.S. Billion-dollar Weather and Climate Disasters, 1980–present (NCEI Accession 0209268), National Centers for Environmental
Information, https://doi.org/10.25921/STKW-7W73, 2020. a
Sun, C. C., Hahn, A., and Liu, C. C.: Cyber security of a power grid:
State-of-the-art, Int. J. Elec. Power, 99, 45–56, https://doi.org/10.1016/j.ijepes.2017.12.020, 2018. a
Tonn, G. L., Guikema, S. D., Ferreira, C. M., and Quiring, S. M.: Hurricane
Isaac: A Longitudinal Analysis of Storm Characteristics and Power Outage
Risk, Risk Anal., 36, 1936–1947, https://doi.org/10.1111/risa.12552, 2016. a, b
Verleysen, M. and François, D.: The curse of dimensionality in data
mining and time series prediction, Lect. Notes Comput. Sci., 3512,
758–770, https://doi.org/10.1007/11494669_93, 2005. a
Wallach, D. and Goffinet, B.: Mean squared error of prediction as a criterion
for evaluating and comparing system models, Ecol. Modell., 44,
299–306, https://doi.org/10.1016/0304-3800(89)90035-5, 1989. a
Wanik, D. W., Anagnostou, E. N., Hartman, B. M., Frediani, M. E., and Astitha,
M.: Storm outage modeling for an electric distribution network in
Northeastern USA, Nat. Hazards, 79, 1359–1384,
https://doi.org/10.1007/s11069-015-1908-2, 2015. a
Wanik, D. W., Parent, J. R., Anagnostou, E. N., and Hartman, B. M.: Using
vegetation management and LiDAR-derived tree height data to improve outage
predictions for electric utilities, Electr. Pow. Syst. Res., 146,
236–245, https://doi.org/10.1016/j.epsr.2017.01.039, 2017. a, b
Wei, H., Xia, Y., Mitchell, K. E., and Ek, M. B.: Improvement of the Noah land surface model for warm season processes: Evaluation of water and energy flux simulation, Hydrol. Process., 27, 297–303, https://doi.org/10.1002/HYP.9214,
2013. a
Wickham, J., Stehman, S. V., Sorenson, D. G., Gass, L., and Dewitz, J. A.:
Thematic accuracy assessment of the NLCD 2016 land cover for the
conterminous United States, Remote Sens. Environ., 257,
https://doi.org/10.1016/J.RSE.2021.112357, 2021. a
Wood, S. N.: Generalized additive models: An introduction with R, second
edition, Generalized Additive Models: An Introduction with R, Second
Edition, 1–476 pp.,
https://doi.org/10.1201/9781315370279/GENERALIZED-ADDITIVE-MODELS-SIMON-WOOD, 2017. a
Wu, H., Svoboda, M. D., Hayes, M. J., Wilhite, D. A., and Wen, F.: Appropriate
application of the Standardized Precipitation Index in arid locations and dry
seasons, Int. J. Climatol., 27, 65–79,
https://doi.org/10.1002/joc.1371, 2007. a
Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L., Alonge, C., Wei, H., Meng, J., Livneh, B., Lettenmaier, D., Koren, V., Duan, Q., Mo, K., Fan, Y., and Mocko, D.: NCEP/EMC (2014), NLDAS VIC Land Surface Model L4 Hourly 0.125 × 0.125 degree V002, edited by: Mocko, D., NASA/GSFC/HSL, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), https://doi.org/10.5067/ELBDAPAKNGJ9, 2012. a, b, c
Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L.,
Alonge, C., Wei, H., Meng, J., Livneh, B., Lettenmaier, D., Koren, V., Duan,
Q., Mo, K., Fan, Y., and Mocko, D.: Continental-scale water and energy flux
analysis and validation for the North American Land Data Assimilation System
project phase 2 (NLDAS-2): 1. Intercomparison and application of model
products, J. Geophys. Res.-Atmos., 117, 3109,
https://doi.org/10.1029/2011JD016048, 2012.
a, b, c
Xie, J., Alvarez-Fernandez, I., and Sun, W.: A review of machine learning
applications in power system resilience, IEEE Pow. Ener. Soc.
Ge., 2020–August, https://doi.org/10.1109/PESGM41954.2020.9282137, 2020. a
Short summary
Power outage models can help utilities manage risks for outages from hurricanes. Our article reviews the existing outage models during hurricanes and highlights their strengths and limitations. Existing models can give erroneous estimates with outage predictions larger than the number of customers, can struggle with predictions for catastrophic hurricanes, and do not adequately represent infrastructure failure's uncertainties. We suggest models for the future that can overcome these challenges.
Power outage models can help utilities manage risks for outages from hurricanes. Our article...
Special issue
Altmetrics
Final-revised paper
Preprint