Articles | Volume 24, issue 1
https://doi.org/10.5194/nhess-24-79-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-79-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
17 Jan 2024
Review article |
| 17 Jan 2024
| 17 Jan 2024
Review article: Current approaches and critical issues in multi-risk recovery planning of urban areas exposed to natural hazards
Soheil Mohammadi
CORRESPONDING AUTHOR
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, 16145, Italy
Silvia De Angeli
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, 16145, Italy
Giorgio Boni
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, 16145, Italy
Francesca Pirlone
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, 16145, Italy
Serena Cattari
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, 16145, Italy
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Silvia De Angeli, Lorenzo Villani, Giulio Castelli, Maria Rusca, Giorgio Boni, Elena Bresci, and Luigi Piemontese
EGUsphere, https://doi.org/10.5194/egusphere-2024-2207, https://doi.org/10.5194/egusphere-2024-2207, 2024
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Despite droughts are deeply intertwined within sociohydrological systems, traditional top-down approaches often ignore those directly affected. By integrating insights from five research fields, we present a framework to guide the co-creation of knowledge for drought impact assessment. Emphasizing social dynamics and power imbalances, the framework guides a more inclusive approach to drought assessment and adaptation.
Nicola Loglisci, Giorgio Boni, Arianna Cauteruccio, Francesco Faccini, Massimo Milelli, Guido Paliaga, and Antonio Parodi
Nat. Hazards Earth Syst. Sci., 24, 2495–2510, https://doi.org/10.5194/nhess-24-2495-2024, https://doi.org/10.5194/nhess-24-2495-2024, 2024
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We analyse the meteo-hydrological features of the 27 and 28 August 2023 event that occurred in Genoa. Rainfall observations were made using rain gauge networks based on either official networks or citizen science networks. The merged analysis stresses the spatial variability in the precipitation, which cannot be captured by the current spatial density of authoritative stations. Results show that at minimal distances the variations in cumulated rainfall over a sub-hourly duration are significant.
Massimiliano Burlando, Djordje Romanic, Giorgio Boni, Martina Lagasio, and Antonio Parodi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2019-371, https://doi.org/10.5194/nhess-2019-371, 2019
Manuscript not accepted for further review
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This paper investigates the weather conditions during the collapse of the Morandi bridge, which caused 43 fatalities. Despite a thunderstorm developed over the city at the time of collapse, weather is officially ruled out as a contributing factor for it. A meteorological analysis is relevant to support this hypothesis or possibly reconsider it. The analysis, mainly based on measurements complemented with numerical simulations, reveals that quite strong winds occurred at the time of collapse.
Luca Cenci, Luca Pulvirenti, Giorgio Boni, Marco Chini, Patrick Matgen, Simone Gabellani, Giuseppe Squicciarino, and Nazzareno Pierdicca
Adv. Geosci., 44, 89–100, https://doi.org/10.5194/adgeo-44-89-2017, https://doi.org/10.5194/adgeo-44-89-2017, 2017
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This research aims at improving hydrological modelling skills of flash flood prediction by exploiting earth observation data. To this aim, high spatial/moderate temporal resolution soil moisture maps, derived from Sentinel 1 acquisitions, were used in a data assimilation framework. Findings revealed the potential of Sentinel 1-based soil moisture data assimilation for flash flood risk reduction and improved our understanding of the capabilities of the aforementioned satellite-derived product.
Antonio Parodi, Luca Ferraris, William Gallus, Maurizio Maugeri, Luca Molini, Franco Siccardi, and Giorgio Boni
Clim. Past, 13, 455–472, https://doi.org/10.5194/cp-13-455-2017, https://doi.org/10.5194/cp-13-455-2017, 2017
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Initial and boundary condition data from the 20th Century Reanalysis Project in ensemble mode are used to address the feasibility of performing cloud-resolving simulations with 1 km horizontal grid spacing of a historic extreme event that occurred over Liguria: the 1915 San Fruttuoso case. The proposed approach focuses on the ensemble Weather Research and Forecasting model runs that show strong convergence over the Ligurian Sea, as these runs are the ones most likely to best simulate the event.
F. Silvestro, S. Gabellani, R. Rudari, F. Delogu, P. Laiolo, and G. Boni
Hydrol. Earth Syst. Sci., 19, 1727–1751, https://doi.org/10.5194/hess-19-1727-2015, https://doi.org/10.5194/hess-19-1727-2015, 2015
F. Silvestro, S. Gabellani, F. Delogu, R. Rudari, and G. Boni
Hydrol. Earth Syst. Sci., 17, 39–62, https://doi.org/10.5194/hess-17-39-2013, https://doi.org/10.5194/hess-17-39-2013, 2013
Related subject area
Risk Assessment, Mitigation and Adaptation Strategies, Socioeconomic and Management Aspects
Content analysis of multi-annual time series of flood-related Twitter (X) data
Enhancement of state response capability and famine mitigation: a comparative analysis of two drought events in northern China during the Ming dynasty
Flood exposure of environmental assets
A new method for calculating highway blocking due to high-impact weather conditions
Impacts from cascading multi-hazards using hypergraphs: a case study from the 2015 Gorkha earthquake in Nepal
Review article: Insuring the green economy against natural hazards – charting research frontiers in vulnerability assessment
Ready, Set & Go! An anticipatory action system against droughts
Between global risk reduction goals, scientific–technical capabilities and local realities: a modular approach for user-centric multi-risk assessment
Flood risk assessment through large-scale modeling under uncertainty
Migration as a hidden risk factor in seismic fatality: spatial modeling of the Chi-Chi earthquake and suburban syndrome
Simulating the effects of sea level rise and soil salinization on adaptation and migration decisions in Mozambique
Current status of water-related planning for climate change adaptation in the Spree river basin, Germany
Using a convection-permitting climate model to assess wine grape productivity: two case studies in Italy
Volcanic risk ranking and regional mapping of the Central Volcanic Zone of the Andes
Assessing the impact of early warning and evacuation on human losses during the 2021 Ahr Valley flood in Germany using agent-based modelling
Development of a regionally consistent and fully probabilistic earthquake risk model for Central Asia
Critical infrastructure resilience: a guide for building indicator systems based on a multi-criteria framework with a focus on implementable actions
Where to start with climate-smart forest management? Climatic risk for forest-based mitigation
Dynamic response of pile–slab retaining wall structure under rockfall impact
Urban growth and spatial segregation increase disaster risk: lessons learned from the 2023 disaster on the North Coast of São Paulo, Brazil
An impact-chain-based exploration of multi-hazard vulnerability dynamics: the multi-hazard of floods and the COVID-19 pandemic in Romania
Always on my mind: indications of post-traumatic stress disorder among those affected by the 2021 flood event in the Ahr valley, Germany
Earthquake insurance in Iran: solvency of local insurers in light of current market practices
Micro-business participation in collective flood adaptation: lessons from scenario-based analysis in Ho Chi Minh City, Vietnam
Brief communication: Storm Daniel flood impact in Greece in 2023: mapping crop and livestock exposure from synthetic-aperture radar (SAR)
Unravelling the capacity-action gap in flood risk adaptation
Risk reduction through managed retreat? Investigating enabling conditions and assessing resettlement effects on community resilience in Metro Manila
Brief communication: Lessons learned and experiences gained from building up a global survey on societal resilience to changing droughts
Regional seismic risk assessment based on ground conditions in Uzbekistan
Unveiling transboundary challenges in river flood risk management: learning from the Ciliwung River basin
Quantitative study of storm surge risk assessment in an undeveloped coastal area of China based on deep learning and geographic information system techniques: a case study of Double Moon Bay
Mapping vulnerability to climate change for spatial planning in the region of Stuttgart
Adaptive Behavior of Over a Million Individual Farmers Under Consecutive Droughts: A Large-Scale Agent-Based Modeling Analysis in the Bhima Basin, India
Sensitive infrastructures and people with disabilities – Key issues when strengthening resilience in reconstruction
Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas
Simulating multi-hazard event sets for life cycle consequence analysis
Analysis of the effects of urban micro-scale vulnerabilities on tsunami evacuation using an agent-based model – case study in the city of Iquique, Chile
Factors of influence on flood risk perceptions related to Hurricane Dorian: an assessment of heuristics, time dynamics, and accuracy of risk perceptions
From insufficient rainfall to livelihoods: understanding the cascade of drought impacts and policy implications
Anticipating a risky future: long short-term memory (LSTM) models for spatiotemporal extrapolation of population data in areas prone to earthquakes and tsunamis in Lima, Peru
A new regionally consistent exposure database for Central Asia: population and residential buildings
Study on seismic risk assessment model of water supply systems in mainland China
Mapping current and future flood exposure using a 5 m flood model and climate change projections
Brief communication: On the environmental impacts of the 2023 floods in Emilia-Romagna (Italy)
A regional-scale approach to assessing non-residential building, transportation and cropland exposure in Central Asia
Towards a global impact-based forecasting model for tropical cyclones
Individual Flood Risk Adaptation in Germany: Exploring the Role of Different Types of Flooding
Identifying vulnerable populations in urban society: a case study in a flood-prone district of Wuhan, China
An assessment of potential improvements in social capital, risk awareness, and preparedness from digital technologies
Spatial accessibility of emergency medical services under inclement weather: a case study in Beijing, China
Nadja Veigel, Heidi Kreibich, Jens A. de Bruijn, Jeroen C. J. H. Aerts, and Andrea Cominola
Nat. Hazards Earth Syst. Sci., 25, 879–891, https://doi.org/10.5194/nhess-25-879-2025, https://doi.org/10.5194/nhess-25-879-2025, 2025
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This study explores how social media, specifically Twitter (X), can help us understand public reactions to floods in Germany from 2014 to 2021. Using large language models, we extract topics and patterns of behavior from flood-related tweets. The findings offer insights to improve communication and disaster management. Topics related to low-impact flooding contain descriptive hazard-related content, while the focus shifts to catastrophic impacts and responsibilities during high-impact events.
Fangyu Tian, Yun Su, Xudong Chen, and Le Tao
Nat. Hazards Earth Syst. Sci., 25, 591–607, https://doi.org/10.5194/nhess-25-591-2025, https://doi.org/10.5194/nhess-25-591-2025, 2025
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This study developed a model of extreme drought-induced famine processes and response mechanisms in ancient China. The spatial distribution of drought and famine during the Chenghua drought and the Wanli drought was constructed. By categorizing drought-affected counties into three types, a comparative analysis of the differences in famine severity and response effectiveness between the Chenghua and Wanli droughts was conducted.
Gabriele Bertoli, Chiara Arrighi, and Enrica Caporali
Nat. Hazards Earth Syst. Sci., 25, 565–580, https://doi.org/10.5194/nhess-25-565-2025, https://doi.org/10.5194/nhess-25-565-2025, 2025
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Environmental assets are crucial to sustaining and fulfilling life on Earth via ecosystem services (ESs). Studying their flood risk is thus seminal, in addition to being required by several norms. However, this field is not yet adequately developed. We studied the exposure component of flood risk and developed an evaluating methodology based on the ESs provided by environmental assets to discern assets and areas that are more important than others with metrics suitable to large-scale studies.
Duanyang Liu, Tian Jing, Mingyue Yan, Ismail Gultepe, Yunxuan Bao, Hongbin Wang, and Fan Zu
Nat. Hazards Earth Syst. Sci., 25, 493–513, https://doi.org/10.5194/nhess-25-493-2025, https://doi.org/10.5194/nhess-25-493-2025, 2025
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Highway-blocking events are characterized by diurnal variation. A classification method of severity levels of highway blocking is catagorized into five levels. The severity levels of highway blocking due to high-impact weather are evaluated. A method for calculating the degree of highway load in China is proposed. A quantitative assessment of the losses of highway blocking due to dense fog is conducted. The highway losses caused by dense fog are concentrated in North, East, and Southwest China.
Alexandre Dunant, Tom R. Robinson, Alexander L. Densmore, Nick J. Rosser, Ragindra Man Rajbhandari, Mark Kincey, Sihan Li, Prem Raj Awasthi, Max Van Wyk de Vries, Ramesh Guragain, Erin Harvey, and Simon Dadson
Nat. Hazards Earth Syst. Sci., 25, 267–285, https://doi.org/10.5194/nhess-25-267-2025, https://doi.org/10.5194/nhess-25-267-2025, 2025
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Natural hazards like earthquakes often trigger other disasters, such as landslides, creating complex chains of impacts. We developed a risk model using a mathematical approach called hypergraphs to efficiently measure the impact of interconnected hazards. We showed that it can predict broad patterns of damage to buildings and roads from the 2015 Nepal earthquake. The model's efficiency allows it to generate multiple disaster scenarios, even at a national scale, to support preparedness plans.
Harikesan Baskaran, Ioanna Ioannou, Tiziana Rossetto, Jonas Cels, Mathis Joffrain, Nicolas Mortegoutte, Aurelie Fallon Saint-Lo, and Catalina Spataru
Nat. Hazards Earth Syst. Sci., 25, 49–76, https://doi.org/10.5194/nhess-25-49-2025, https://doi.org/10.5194/nhess-25-49-2025, 2025
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There is a global need for insuring green economy assets against natural hazard events. But their complexity and low exposure history mean the data required for vulnerability evaluation by the insurance industry are scarce. A systematic literature review is conducted in this study to determine the suitability of current published literature for this purpose. Knowledge gaps are charted, and a representative asset–hazard taxonomy is proposed to guide future quantitative research.
Gabriela Guimarães Nobre, Jamie Towner, Bernardino Nhantumbo, Célio João da Conceição Marcos Matuele, Isaias Raiva, Massimiliano Pasqui, Sara Quaresima, and Rogério Manuel Lemos Pereira Bonifácio
Nat. Hazards Earth Syst. Sci., 24, 4661–4682, https://doi.org/10.5194/nhess-24-4661-2024, https://doi.org/10.5194/nhess-24-4661-2024, 2024
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The
Ready, Set & Go!system, developed by the World Food Programme and partners, employs seasonal forecasts to tackle droughts in Mozambique. With the Maputo Declaration, efforts to expand early warning systems are aligning with global initiatives for universal protection by 2027. Through advanced forecasting and anticipatory action, it could cover 76 % of districts against severe droughts, reaching 87 % national coverage for the first months of the rainy season.
Elisabeth Schoepfer, Jörn Lauterjung, Torsten Riedlinger, Harald Spahn, Juan Camilo Gómez Zapata, Christian D. León, Hugo Rosero-Velásquez, Sven Harig, Michael Langbein, Nils Brinckmann, Günter Strunz, Christian Geiß, and Hannes Taubenböck
Nat. Hazards Earth Syst. Sci., 24, 4631–4660, https://doi.org/10.5194/nhess-24-4631-2024, https://doi.org/10.5194/nhess-24-4631-2024, 2024
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In this paper, we provide a brief introduction of the paradigm shift from managing disasters to managing risks, followed by single-hazard to multi-risk assessment. We highlight four global strategies that address disaster risk reduction and call for action. Subsequently, we present a conceptual approach for multi-risk assessment which was designed to serve potential users like disaster risk managers, urban planners or operators of critical infrastructure to increase their capabilities.
Luciano Pavesi, Elena Volpi, and Aldo Fiori
Nat. Hazards Earth Syst. Sci., 24, 4507–4522, https://doi.org/10.5194/nhess-24-4507-2024, https://doi.org/10.5194/nhess-24-4507-2024, 2024
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Several sources of uncertainty affect flood risk estimation for reliable assessment for investment, insurance and risk management. Here, we consider the uncertainty of large-scale flood hazard modeling, providing a range of risk values that show significant variability depending on geomorphic factors and land use types. This allows for identifying the critical points where single-value estimates may underestimate the risk and the areas of vulnerability for prioritizing risk reduction efforts.
Tzu-Hsin Karen Chen, Kuan-Hui Elaine Lin, Thung-Hong Lin, Gee-Yu Liu, Chin-Hsun Yeh, and Diana Maria Ceballos
Nat. Hazards Earth Syst. Sci., 24, 4457–4471, https://doi.org/10.5194/nhess-24-4457-2024, https://doi.org/10.5194/nhess-24-4457-2024, 2024
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This study shows migration patterns to be a critical factor in seismic fatalities. Analyzing the Chi-Chi earthquake in Taiwan, we find that lower income and a higher indigenous population at migrants' origins are correlated with higher fatalities at their destinations. This underscores the need for affordable and safe housing on the outskirts of megacities, where migrants from lower-income and historically marginalized groups are more likely to reside due to precarious employment conditions.
Kushagra Pandey, Jens A. de Bruijn, Hans de Moel, W. J. Wouter Botzen, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 24, 4409–4429, https://doi.org/10.5194/nhess-24-4409-2024, https://doi.org/10.5194/nhess-24-4409-2024, 2024
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As sea levels rise, coastal areas will experience more frequent flooding, and salt water will start seeping into the soil, which is a serious issue for farmers who rely on good soil quality for their crops. Here, we studied coastal Mozambique to understand the risks from sea level rise and flooding by looking at how salt intrusion affects farming and how floods damage buildings. We find that 15 %–21 % of coastal households will adapt and 13 %–20 % will migrate to inland areas in the future.
Saskia Arndt and Stefan Heiland
Nat. Hazards Earth Syst. Sci., 24, 4369–4383, https://doi.org/10.5194/nhess-24-4369-2024, https://doi.org/10.5194/nhess-24-4369-2024, 2024
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This study provides an overview of the current status of climate change adaptation in plans for water management, spatial planning and landscape planning in the Spree river basin. Only 39 % of 28 plans analysed specify objectives and measures for adaptation to climate change. To fill this gap, more frequent updates of plans, a stronger focus on multifunctional measures, and the adaptation of best-practice examples for systematic integration of climate change impacts and adaptation are needed.
Laura T. Massano, Giorgia Fosser, Marco Gaetani, and Cécile Caillaud
Nat. Hazards Earth Syst. Sci., 24, 4293–4315, https://doi.org/10.5194/nhess-24-4293-2024, https://doi.org/10.5194/nhess-24-4293-2024, 2024
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Traditional wine-growing regions are threatened by expected climate change. Climate models and observations are used to calculate bioclimatic indices based on both temperature and precipitation. These indices are correlated with grape productivity in two wine-growing regions in Italy. This analysis paves the way for using climate models to study how climate change will affect wine production in the future.
María-Paz Reyes-Hardy, Luigia Sara Di Maio, Lucia Dominguez, Corine Frischknecht, Sébastien Biass, Leticia Freitas Guimarães, Amiel Nieto-Torres, Manuela Elissondo, Gabriela Pedreros, Rigoberto Aguilar, Álvaro Amigo, Sebastián García, Pablo Forte, and Costanza Bonadonna
Nat. Hazards Earth Syst. Sci., 24, 4267–4291, https://doi.org/10.5194/nhess-24-4267-2024, https://doi.org/10.5194/nhess-24-4267-2024, 2024
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The Central Volcanic Zone of the Andes (CVZA) spans four countries with 59 volcanoes. We identify those with the most intense and frequent eruptions and the highest potential impact that require risk mitigation actions. Using multiple risk factors, we encourage the use of regional volcanic risk assessments to analyse the level of preparedness especially of transboundary volcanoes. We hope that our work will motivate further collaborative studies and promote cooperation between CVZA countries.
André Felipe Rocha Silva, Julian Cardoso Eleutério, Heiko Apel, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-183, https://doi.org/10.5194/nhess-2024-183, 2024
Revised manuscript accepted for NHESS
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This work uses agent-based modelling to evaluate the impact of flood warning and evacuation systems on human losses during the 2021 Ahr Valley flood in Germany. While the first flood warning with evacuation instructions is identified as timely, its lack of detail and effectiveness resulted in low public risk awareness. Better dissemination of warnings and improved risk perception and preparedness among the population could reduce casualties by up to 80 %.
Mario A. Salgado-Gálvez, Mario Ordaz, Benjamín Huerta, Osvaldo Garay, Carlos Avelar, Ettore Fagà, Mohsen Kohrangi, Paola Ceresa, Georgios Triantafyllou, and Ulugbek T. Begaliev
Nat. Hazards Earth Syst. Sci., 24, 3851–3868, https://doi.org/10.5194/nhess-24-3851-2024, https://doi.org/10.5194/nhess-24-3851-2024, 2024
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Central Asia is prone to earthquake losses, which can heavily impact different types of assets. This paper presents the details of a probabilistic earthquake risk model which made use of a regionally consistent approach to assess feasible earthquake losses in five countries. Results are presented in terms of commonly used risk metrics, which are aimed at facilitating a policy dialogue regarding different disaster risk management strategies, from risk mitigation to disaster risk financing.
Zhuyu Yang, Bruno Barroca, Ahmed Mebarki, Katia Laffréchine, Hélène Dolidon, and Lionel Lilas
Nat. Hazards Earth Syst. Sci., 24, 3723–3753, https://doi.org/10.5194/nhess-24-3723-2024, https://doi.org/10.5194/nhess-24-3723-2024, 2024
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To integrate resilience assessment into practical management, this study designs a step-by-step guide that enables managers of critical infrastructure (CI) to create specific indicator systems tailored to real cases. This guide considers the consequences of hazards to CI and the cost–benefit analysis and side effects of implementable actions. The assessment results assist managers, as they are based on a multi-criterion framework that addresses several factors valued in practical management.
Natalie Piazza, Luca Malanchini, Edoardo Nevola, and Giorgio Vacchiano
Nat. Hazards Earth Syst. Sci., 24, 3579–3595, https://doi.org/10.5194/nhess-24-3579-2024, https://doi.org/10.5194/nhess-24-3579-2024, 2024
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Natural disturbances are projected to intensify in the future, threatening our forests and their functions such as wood production, protection against natural hazards, and carbon sequestration. By assessing risks to forests from wind and fire damage, alongside the vulnerability of carbon, it is possible to prioritize forest stands at high risk. In this study, we propose a novel methodological approach to support climate-smart forest management and inform better decision-making.
Peng Zou, Gang Luo, Yuzhang Bi, and Hanhua Xu
Nat. Hazards Earth Syst. Sci., 24, 3497–3517, https://doi.org/10.5194/nhess-24-3497-2024, https://doi.org/10.5194/nhess-24-3497-2024, 2024
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The pile–slab retaining wall, an innovative rockfall shield, is widely used in China's western mountains. However, its dynamic impact response and resistance remain unclear due to structural complexity. A comprehensive dynamic analysis of the structure, under various impacts, was done using the finite-element method. The maximum impact energy that the structure can withstand is 905 kJ, and various indexes were obtained.
Cassiano Bastos Moroz and Annegret H. Thieken
Nat. Hazards Earth Syst. Sci., 24, 3299–3314, https://doi.org/10.5194/nhess-24-3299-2024, https://doi.org/10.5194/nhess-24-3299-2024, 2024
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We evaluate the influence of urban processes on the impacts of the 2023 disaster that hit the North Coast of São Paulo, Brazil. The impacts of the disaster were largely associated with rapid urban expansion over the last 3 decades, with a recent occupation of risky areas. Moreover, lower-income neighborhoods were considerably more severely impacted, which evidences their increased exposure to such events. These results highlight the strong association between disaster risk and urban poverty.
Andra-Cosmina Albulescu and Iuliana Armaș
Nat. Hazards Earth Syst. Sci., 24, 2895–2922, https://doi.org/10.5194/nhess-24-2895-2024, https://doi.org/10.5194/nhess-24-2895-2024, 2024
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This study delves into the dynamics of vulnerability within a multi-hazard context, proposing an enhanced impact-chain-based framework that analyses the augmentation of vulnerability. The case study refers to the flood events and the COVID-19 pandemic that affected Romania (2020–2021). The impact chain shows that (1) the unforeseen implications of impacts, (2) the wrongful action of adaptation options, and (3) inaction can form the basis for increased vulnerability.
Marie-Luise Zenker, Philip Bubeck, and Annegret H. Thieken
Nat. Hazards Earth Syst. Sci., 24, 2837–2856, https://doi.org/10.5194/nhess-24-2837-2024, https://doi.org/10.5194/nhess-24-2837-2024, 2024
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Despite the visible flood damage, mental health is a growing concern. Yet, there is limited data in Germany on mental health impacts after floods. A survey in a heavily affected region revealed that 28 % of respondents showed signs of post-traumatic stress disorder 1 year later. Risk factors include gender, serious injury or illness due to flooding, and feeling left alone to cope with impacts. The study highlights the need for tailored mental health support for flood-affected populations.
Mohsen Ghafory-Ashtiany and Hooman Motamed
Nat. Hazards Earth Syst. Sci., 24, 2707–2726, https://doi.org/10.5194/nhess-24-2707-2024, https://doi.org/10.5194/nhess-24-2707-2024, 2024
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Iranian insurers have been offering earthquake coverage since the 1990s. However, despite international best practices, they still do not use modern methods for risk pricing and management. As such, they seem to be accumulating seismic risk over time. This paper examines the viability of this market in Iran by comparing the local market practices with international best practices in earthquake risk pricing (catastrophe modeling) and insurance risk management (European Solvency II regime).
Javier Revilla Diez, Roxana Leitold, Van Tran, and Matthias Garschagen
Nat. Hazards Earth Syst. Sci., 24, 2425–2440, https://doi.org/10.5194/nhess-24-2425-2024, https://doi.org/10.5194/nhess-24-2425-2024, 2024
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Micro-businesses, often overlooked in adaptation research, show surprising willingness to contribute to collective adaptation despite limited finances and local support. Based on a study in Ho Chi Minh City in Vietnam, approximately 70 % are ready for awareness campaigns, and 39 % would provide financial support if costs were shared. These findings underscore the need for increased involvement of micro-businesses in local adaptation plans to enhance collective adaptive capacity.
Kang He, Qing Yang, Xinyi Shen, Elias Dimitriou, Angeliki Mentzafou, Christina Papadaki, Maria Stoumboudi, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 24, 2375–2382, https://doi.org/10.5194/nhess-24-2375-2024, https://doi.org/10.5194/nhess-24-2375-2024, 2024
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About 820 km2 of agricultural land was inundated in central Greece due to Storm Daniel. A detailed analysis revealed that the crop most affected by the flooding was cotton; the inundated area of more than 282 km2 comprised ~ 30 % of the total area planted with cotton in central Greece. In terms of livestock, we estimate that more than 14 000 ornithoids and 21 500 sheep and goats were affected. Consequences for agriculture and animal husbandry in Greece are expected to be severe.
Annika Schubert, Anne von Streit, and Matthias Garschagen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-121, https://doi.org/10.5194/nhess-2024-121, 2024
Revised manuscript accepted for NHESS
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Households play a crucial role in climate adaptation efforts. Yet, households require capacities to implement measures. We explore which capacities enable German households to adapt to flooding. Our results indicate that flood-related capacities such as risk perception, responsibility appraisal and motivation are pivotal, whereas financial assets are secondary. Enhancing these specific capacities, e.g. through collaborations between households and municipalities, could promote local adaptation.
Hannes Lauer, Carmeli Marie C. Chaves, Evelyn Lorenzo, Sonia Islam, and Jörn Birkmann
Nat. Hazards Earth Syst. Sci., 24, 2243–2261, https://doi.org/10.5194/nhess-24-2243-2024, https://doi.org/10.5194/nhess-24-2243-2024, 2024
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In many urban areas, people face high exposure to hazards. Resettling them to safer locations becomes a major strategy, not least because of climate change. This paper dives into the success factors of government-led resettlement in Manila and finds surprising results which challenge the usual narrative and fuel the conversation on resettlement as an adaptation strategy. Contrary to expectations, the location – whether urban or rural – of the new home is less important than safety from floods.
Marina Batalini de Macedo, Marcos Roberto Benso, Karina Simone Sass, Eduardo Mario Mendiondo, Greicelene Jesus da Silva, Pedro Gustavo Câmara da Silva, Elisabeth Shrimpton, Tanaya Sarmah, Da Huo, Michael Jacobson, Abdullah Konak, Nazmiye Balta-Ozkan, and Adelaide Cassia Nardocci
Nat. Hazards Earth Syst. Sci., 24, 2165–2173, https://doi.org/10.5194/nhess-24-2165-2024, https://doi.org/10.5194/nhess-24-2165-2024, 2024
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With climate change, societies increasingly need to adapt to deal with more severe droughts and the impacts they can have on food production. To make better adaptation decisions, drought resilience indicators can be used. To build these indicators, surveys with experts can be done. However, designing surveys is a costly process that can influence how experts respond. In this communication, we aim to deal with the challenges encountered in the development of surveys to help further research.
Vakhitkhan Alikhanovich Ismailov, Sharofiddin Ismatullayevich Yodgorov, Akhror Sabriddinovich Khusomiddinov, Eldor Makhmadiyorovich Yadigarov, Bekzod Uktamovich Aktamov, and Shuhrat Bakhtiyorovich Avazov
Nat. Hazards Earth Syst. Sci., 24, 2133–2146, https://doi.org/10.5194/nhess-24-2133-2024, https://doi.org/10.5194/nhess-24-2133-2024, 2024
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For the basis of seismic risk assessment, maps of seismic intensity increment and an improved map of seismic hazard have been developed, taking into account the engineering-geological conditions of the territory of Uzbekistan and the seismic characteristics of soils. For seismic risk map development, databases were created based on geographic information system platforms, allowing us to systematize and evaluate the regional distribution of information.
Harkunti Pertiwi Rahayu, Khonsa Indana Zulfa, Dewi Nurhasanah, Richard Haigh, Dilanthi Amaratunga, and In In Wahdiny
Nat. Hazards Earth Syst. Sci., 24, 2045–2064, https://doi.org/10.5194/nhess-24-2045-2024, https://doi.org/10.5194/nhess-24-2045-2024, 2024
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Transboundary flood risk management in the Ciliwung River basin is placed in a broader context of disaster management, environmental science, and governance. This is particularly relevant for areas of research involving the management of shared water resources, the impact of regional development on flood risk, and strategies to reduce economic losses from flooding.
Lichen Yu, Hao Qin, Shining Huang, Wei Wei, Haoyu Jiang, and Lin Mu
Nat. Hazards Earth Syst. Sci., 24, 2003–2024, https://doi.org/10.5194/nhess-24-2003-2024, https://doi.org/10.5194/nhess-24-2003-2024, 2024
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This paper proposes a quantitative storm surge risk assessment method for data-deficient regions. A coupled model is used to simulate five storm surge scenarios. Deep learning is used to extract building footprints. Economic losses are calculated by combining adjusted depth–damage functions with inundation simulation results. Zoning maps illustrate risk levels based on economic losses, aiding in disaster prevention measures to reduce losses in coastal areas.
Joanna M. McMillan, Franziska Göttsche, Joern Birkmann, Rainer Kapp, Corinna Schmidt, Britta Weisser, and Ali Jamshed
EGUsphere, https://doi.org/10.5194/egusphere-2024-1407, https://doi.org/10.5194/egusphere-2024-1407, 2024
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Adapting to climate extremes is a challenge for spatial planning. Risk maps that include not just a consideration of hazards but also social vulnerability can help. We develop social vulnerability maps for the Stuttgart region, Germany. We show the maps, describe how and why we developed them, and provide an analysis of practitioners’ needs and their feedback. Insights presented in this paper can help to improve map usability and to better link research and planning practice.
Maurice W. M. L. Kalthof, Jens de Bruijn, Hans de Moel, Heidi Kreibich, and Jeroen C. J. H. Aerts
EGUsphere, https://doi.org/10.5194/egusphere-2024-1588, https://doi.org/10.5194/egusphere-2024-1588, 2024
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Our study explores how farmers in India's Bhima basin respond to consecutive droughts. We simulated all farmers' individual choices—like changing crops or digging wells—and their effects on profits, yields, and water resources. Results show these adaptations, while improving incomes, ultimately increase drought vulnerability and damages. Such insights emphasize the need for alternative adaptations and highlight the value of socio-hydrology models in shaping policies to lessen drought impacts.
Alessa Truedinger, Joern Birkmann, Mark Fleischhauer, and Celso Ferreira
EGUsphere, https://doi.org/10.5194/egusphere-2024-1607, https://doi.org/10.5194/egusphere-2024-1607, 2024
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In post-disaster reconstruction, emphasis should be placed on critical and sensitive infrastructures. In Germany as in other countries, sensitive infrastructures have not yet been focused on – therefore, we developed a method for determining the risk sensitive infrastructures are facing in the context of riverine and pluvial flooding. The easy-to-use assessment framework can be applied to various sensitive infrastructures, e.g. to qualify and accelerate decisions in the reconstruction process.
Stephen B. Ferencz, Ning Sun, Sean W. D. Turner, Brian A. Smith, and Jennie S. Rice
Nat. Hazards Earth Syst. Sci., 24, 1871–1896, https://doi.org/10.5194/nhess-24-1871-2024, https://doi.org/10.5194/nhess-24-1871-2024, 2024
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Drought has long posed an existential threat to society. Population growth, economic development, and the potential for more extreme and prolonged droughts due to climate change pose significant water security challenges. Better understanding the impacts and adaptive responses resulting from extreme drought can aid adaptive planning. The 2008–2015 record drought in the Colorado Basin, Texas, United States, is used as a case study to assess impacts and responses to severe drought.
Leandro Iannacone, Kenneth Otárola, Roberto Gentile, and Carmine Galasso
Nat. Hazards Earth Syst. Sci., 24, 1721–1740, https://doi.org/10.5194/nhess-24-1721-2024, https://doi.org/10.5194/nhess-24-1721-2024, 2024
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The paper presents a review of the available classifications for hazard interactions in a multi-hazard context, and it incorporates such classifications from a modeling perspective. The outcome is a sequential Monte Carlo approach enabling efficient simulation of multi-hazard event sets (i.e., sequences of events throughout the life cycle). These event sets can then be integrated into frameworks for the quantification of consequences for the purposes of life cycle consequence (LCCon) analysis.
Rodrigo Cienfuegos, Gonzalo Álvarez, Jorge León, Alejandro Urrutia, and Sebastián Castro
Nat. Hazards Earth Syst. Sci., 24, 1485–1500, https://doi.org/10.5194/nhess-24-1485-2024, https://doi.org/10.5194/nhess-24-1485-2024, 2024
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This study carries out a detailed analysis of possible tsunami evacuation scenarios in the city of Iquique in Chile. Evacuation modeling and tsunami modeling are integrated, allowing for an estimation of the potential number of people that the inundation may reach under different scenarios by emulating the dynamics and behavior of the population and their decision-making regarding the starting time of the evacuation.
Laurine A. de Wolf, Peter J. Robinson, W. J. Wouter Botzen, Toon Haer, Jantsje M. Mol, and Jeffrey Czajkowski
Nat. Hazards Earth Syst. Sci., 24, 1303–1318, https://doi.org/10.5194/nhess-24-1303-2024, https://doi.org/10.5194/nhess-24-1303-2024, 2024
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An understanding of flood risk perceptions may aid in improving flood risk communication. We conducted a survey among 871 coastal residents in Florida who were threatened to be flooded by Hurricane Dorian. Part of the original sample was resurveyed after Dorian failed to make landfall to investigate changes in risk perception. We find a strong influence of previous flood experience and social norms on flood risk perceptions. Furthermore, flood risk perceptions declined after the near-miss event.
Louise Cavalcante, David W. Walker, Sarra Kchouk, Germano Ribeiro Neto, Taís Maria Nunes Carvalho, Mariana Madruga de Brito, Wieke Pot, Art Dewulf, and Pieter van Oel
EGUsphere, https://doi.org/10.5194/egusphere-2024-650, https://doi.org/10.5194/egusphere-2024-650, 2024
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The research aimed to understand the role of society in mitigating drought impacts through policy responses in the context of northeast Brazil. Results revealed that socio-environmental-economic impacts of drought are less frequently reported, while hydrological impacts of drought were the most reported. It emphasized that public policies addressing the impacts of drought need to focus not only on increasing water availability, but also on strengthening the local economy.
Christian Geiß, Jana Maier, Emily So, Elisabeth Schoepfer, Sven Harig, Juan Camilo Gómez Zapata, and Yue Zhu
Nat. Hazards Earth Syst. Sci., 24, 1051–1064, https://doi.org/10.5194/nhess-24-1051-2024, https://doi.org/10.5194/nhess-24-1051-2024, 2024
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We establish a model of future geospatial population distributions to quantify the number of people living in earthquake-prone and tsunami-prone areas of Lima and Callao, Peru, for the year 2035. Areas of high earthquake intensity will experience a population growth of almost 30 %. The population in the tsunami inundation area is estimated to grow by more than 60 %. Uncovering those relations can help urban planners and policymakers to develop effective risk mitigation strategies.
Chiara Scaini, Alberto Tamaro, Baurzhan Adilkhan, Satbek Sarzhanov, Vakhitkhan Ismailov, Ruslan Umaraliev, Mustafo Safarov, Vladimir Belikov, Japar Karayev, and Ettore Faga
Nat. Hazards Earth Syst. Sci., 24, 929–945, https://doi.org/10.5194/nhess-24-929-2024, https://doi.org/10.5194/nhess-24-929-2024, 2024
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Central Asia is highly exposed to multiple hazards, including earthquakes, floods and landslides, for which risk reduction strategies are currently under development. We provide a regional-scale database of assets at risk, including population and residential buildings, based on existing information and recent data collected for each Central Asian country. The population and number of buildings are also estimated for the year 2080 to support the definition of disaster risk reduction strategies.
Tianyang Yu, Banghua Lu, Hui Jiang, and Zhi Liu
Nat. Hazards Earth Syst. Sci., 24, 803–822, https://doi.org/10.5194/nhess-24-803-2024, https://doi.org/10.5194/nhess-24-803-2024, 2024
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A basic database for seismic risk assessment of 720 urban water supply systems in mainland China is established. The parameters of the seismic risk curves of 720 cities are calculated. The seismic fragility curves of various facilities in the water supply system are given based on the logarithmic normal distribution model. The expected seismic loss and the expected loss rate index of 720 urban water supply systems in mainland China in the medium and long term are given.
Connor Darlington, Jonathan Raikes, Daniel Henstra, Jason Thistlethwaite, and Emma K. Raven
Nat. Hazards Earth Syst. Sci., 24, 699–714, https://doi.org/10.5194/nhess-24-699-2024, https://doi.org/10.5194/nhess-24-699-2024, 2024
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The impacts of climate change on local floods require precise maps that clearly demarcate changes to flood exposure; however, most maps lack important considerations that reduce their utility in policy and decision-making. This article presents a new approach to identifying current and projected flood exposure using a 5 m model. The results highlight advancements in the mapping of flood exposure with implications for flood risk management.
Chiara Arrighi and Alessio Domeneghetti
Nat. Hazards Earth Syst. Sci., 24, 673–679, https://doi.org/10.5194/nhess-24-673-2024, https://doi.org/10.5194/nhess-24-673-2024, 2024
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In this communication, we reflect on environmental flood impacts by analysing the reported environmental consequences of the 2023 Emilia-Romagna floods. The most frequently reported damage involves water resources and water-related ecosystems. Indirect effects in time and space, intrinsic recovery capacity, cascade impacts on socio-economic systems, and the lack of established monitoring activities appear to be the most challenging aspects for future research.
Chiara Scaini, Alberto Tamaro, Baurzhan Adilkhan, Satbek Sarzhanov, Zukhritdin Ergashev, Ruslan Umaraliev, Mustafo Safarov, Vladimir Belikov, Japar Karayev, and Ettore Fagà
Nat. Hazards Earth Syst. Sci., 24, 355–373, https://doi.org/10.5194/nhess-24-355-2024, https://doi.org/10.5194/nhess-24-355-2024, 2024
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Central Asia is prone to multiple hazards such as floods, landslides and earthquakes, which can affect a wide range of assets at risk. We develop the first regionally consistent database of assets at risk for non-residential buildings, transportation and croplands in Central Asia. The database combines global and regional data sources and country-based information and supports the development of regional-scale disaster risk reduction strategies for the Central Asia region.
Mersedeh Kooshki Forooshani, Marc van den Homberg, Kyriaki Kalimeri, Andreas Kaltenbrunner, Yelena Mejova, Leonardo Milano, Pauline Ndirangu, Daniela Paolotti, Aklilu Teklesadik, and Monica L. Turner
Nat. Hazards Earth Syst. Sci., 24, 309–329, https://doi.org/10.5194/nhess-24-309-2024, https://doi.org/10.5194/nhess-24-309-2024, 2024
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We improve an existing impact forecasting model for the Philippines by transforming the target variable (percentage of damaged houses) to a fine grid, using only features which are globally available. We show that our two-stage model conserves the performance of the original and even has the potential to introduce savings in anticipatory action resources. Such model generalizability is important in increasing the applicability of such tools around the world.
Lisa Dillenardt and Annegret H. Thieken
EGUsphere, https://doi.org/10.5194/egusphere-2024-162, https://doi.org/10.5194/egusphere-2024-162, 2024
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Using survey data, we analysed the influence of different flood types on whether households implement adaptive measures. We found that communication and management strategies need to involve municipalities and should be tailored to the locally relevant flood type.
Jia Xu, Makoto Takahashi, and Weifu Li
Nat. Hazards Earth Syst. Sci., 24, 179–197, https://doi.org/10.5194/nhess-24-179-2024, https://doi.org/10.5194/nhess-24-179-2024, 2024
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Through the development of micro-individual social vulnerability indicators and cluster analysis, this study assessed the level of social vulnerability of 599 residents from 11 communities in the Hongshan District of Wuhan. The findings reveal three levels of social vulnerability: high, medium, and low. Quantitative assessments offer specific comparisons between distinct units, and the results indicate that different types of communities have significant differences in social vulnerability.
Tommaso Piseddu, Mathilda Englund, and Karina Barquet
Nat. Hazards Earth Syst. Sci., 24, 145–161, https://doi.org/10.5194/nhess-24-145-2024, https://doi.org/10.5194/nhess-24-145-2024, 2024
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Contributions to social capital, risk awareness, and preparedness constitute the parameters to test applications in disaster risk management. We propose an evaluation of four of these: mobile positioning data, social media crowdsourcing, drones, and satellite imaging. The analysis grants the opportunity to investigate how different methods to evaluate surveys' results may influence final preferences. We find that the different assumptions on which these methods rely deliver diverging results.
Yuting Zhang, Kai Liu, Xiaoyong Ni, Ming Wang, Jianchun Zheng, Mengting Liu, and Dapeng Yu
Nat. Hazards Earth Syst. Sci., 24, 63–77, https://doi.org/10.5194/nhess-24-63-2024, https://doi.org/10.5194/nhess-24-63-2024, 2024
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This article is aimed at developing a method to quantify the influence of inclement weather on the accessibility of emergency medical services (EMSs) in Beijing, China, and identifying the vulnerable areas that could not get timely EMSs under inclement weather. We found that inclement weather could reduce the accessibility of EMSs by up to 40%. Furthermore, towns with lower baseline EMSs accessibility are more vulnerable when inclement weather occurs.
Cited articles
Alexander, D. E.: The L'Aquila Earthquake of 6 April 2009 and Italian Government Policy on Disaster Response, Journal of Natural Resources Policy Research, 2, 325–342, https://doi.org/10.1080/19390459.2010.511450, 2010. a, b
Alexander, D. E.: An evaluation of medium-term recovery processes after the 6 April 2009 earthquake in L'Aquila, Central Italy, Environmental Hazards, 12, 60–73, https://doi.org/10.1080/17477891.2012.689250, 2013. a
Ali, R. A., Mannakkara, S., and Wilkinson, S.: Factors affecting successful transition between post-disaster recovery phases: a case study of 2010 floods in Sindh, Pakistan, International Journal of Disaster Resilience in the Built Environment, 11, 597–614, https://doi.org/10.1108/IJDRBE-03-2020-0016, 2020. a, b
Alifa, S. and Nugroho, F.: The role of local community enterprise towards economic recovery of disaster-affected community in Indonesia, Pertanika Journal of Social Sciences and Humanities, 27, 2333–2349, 2019. a
Almoghathawi, Y. and Barker, K.: Component importance measures for interdependent infrastructure network resilience, Comput. Ind. Eng., 133, 153–164, https://doi.org/10.1016/j.cie.2019.05.001, 2019. a
Arenas, A., Missal, R., Mellucci, C., Murshed, Z., and Vatsa, K.: A Guidance Note: National Post-Disaster Recovery Planning and Coordination, https://www.preventionweb.net/publication/guidance-note-national-post-disaster-recovery-planning-and-coordination (last access: 24 October 2023), 2016. a, b, c
Argyroudis, S. A., Mitoulis, S. A., Hofer, L., Zanini, M. A., Tubaldi, E., and Frangopol, D. M.: Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets, Sci. Total Environ., 714, 136854, https://doi.org/10.1016/j.scitotenv.2020.136854, 2020. a, b
Aroquipa, H. and Hurtado, A.: Seismic resilience assessment of buildings: A simplified methodological approach through conventional seismic risk assessment, Int. J. Disast. Risk Re., 77, 103047, https://doi.org/10.1016/j.ijdrr.2022.103047, 2022. a
Australian Institute for Disaster Resilience: Australian Emergency Management Thesaurus, Tech. rep., Australian Institute for Disaster Resilience, https://knowledge.aidr.org.au/media/1957/manual-4-australian-emergency-management-thesaurus.pdf (last access: 24 October 2023), 1998. a
Bahmani, H. and Zhang, W.: Comprehensive Success Evaluation Framework for Socio-Natural Disaster Recovery Projects, Buildings, 11, 647, https://doi.org/10.3390/buildings11120647, 2021. a, b, c, d
Barakat, S. and Zyck, S. A.: Housing Reconstruction as Socio-economic Recovery and State Building: Evidence from Southern Lebanon, Housing Stud., 26, 133–154, https://doi.org/10.1080/02673037.2010.512750, 2011. a
Berke, P., Cooper, J., Aminto, M., Grabich, S., and Horney, J.: Adaptive Planning for Disaster Recovery and Resiliency: An Evaluation of 87 Local Recovery Plans in Eight States, J. Am. Plann. Assoc., 80, 310–323, https://doi.org/10.1080/01944363.2014.976585, 2014. a
Berke, P. R., Song, Y., and Stevens, M.: Integrating Hazard Mitigation into New Urban and Conventional Developments, J. Plan. Educ. Res., 28, 441–455, https://doi.org/10.1177/0739456X09331550, 2009. a
Blackburn, S.: What Does Transformation Look Like? Post-Disaster Politics and the Case for Progressive Rehabilitation, Sustainability, 10, 2317, https://doi.org/10.3390/su10072317, 2018. a
Blagojević, N., Didier, M., and Stojadinović, B.: Quantifying component importance for disaster resilience of communities with interdependent civil infrastructure systems, Reliab. Eng. Syst. Safe, 228, 108747, https://doi.org/10.1016/j.ress.2022.108747, 2022.
Boaz, A., Ashby, D., and Young, K.: Systematic reviews: what have they got to offer evidence based policy and practice?, ESRC UK Centre for Evidence Based Policy and Practice London https://emilkirkegaard.dk/en/wp-content/uploads/Should-I-do-a-systematic-review.pdf, (last access: 24 October 2023), 2002. a
Bolin, R. and Stanford, L.: The Northridge Earthquake: Community-based Approaches to Unmet Recovery Needs, Disasters, 22, 21–38, https://doi.org/10.1111/1467-7717.00073, 1998. a
Bolin, R. C. and Bolton, P. A.: Race, religion, and ethnicity in disaster recovery, Institute of Behavioral Science, University of Colorado, https://digitalcommons.usf.edu/fmhi_pub/88 (last access: 12 January 2024), 1986. a
Bosher, L., Chmutina, K., and van Niekerk, D.: Stop going around in circles: towards a reconceptualisation of disaster risk management phases, Disaster Prev. Manag., 30, 525–537, https://doi.org/10.1108/DPM-03-2021-0071, 2021. a
Bozza, A., Asprone, D., and Manfredi, G.: Developing an integrated framework to quantify resilience of urban systems against disasters, Nat. Hazards, 78, 1729–1748, https://doi.org/10.1007/s11069-015-1798-3, 2015. a
Bozza, A., Asprone, D., and Manfredi, G.: A methodological framework assessing disaster resilience of city ecosystems to enhance resource use efficiency, International Journal of Urban Sustainable Development, 9, 136–150, https://doi.org/10.1080/19463138.2016.1244538, 2017.
Bristow, D. N.: How Spatial and Functional Dependencies between Operations and Infrastructure Leads to Resilient Recovery, J. Infrastruct. Syst., 25, 04019011, https://doi.org/10.1061/(ASCE)IS.1943-555X.0000490, 2019.
Brugmann, J.: Financing the resilient city, Environ. Urban., 24, 215–232, https://doi.org/10.1177/0956247812437130, 2012. a
Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O'Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. A., and von Winterfeldt, D.: A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities, Earthq. Spectra, 19, 733–752, https://doi.org/10.1193/1.1623497, 2003. a, b
Cavallaro, M., Asprone, D., Latora, V., Manfredi, G., and Nicosia, V.: Assessment of Urban Ecosystem Resilience through Hybrid Social–Physical Complex Networks, Comput.-Aided Civ. Inf., 29, 608–625, https://doi.org/10.1111/mice.12080, 2014.
Cerè, G., Rezgui, Y., and Zhao, W.: Critical review of existing built environment resilience frameworks: Directions for future research, Int. J. Disast. Risk Re., 25, 173–189, https://doi.org/10.1016/j.ijdrr.2017.09.018, 2017. a
Cha, E. J. and He, X.: Post-disaster Recovery Planning of Interdependent Infrastructure Systems: A Game Theory-Based Approach, in: 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, 26–30 May 2019, https://doi.org/10.22725/ICASP13.091, 2019.
Chandrasekhar, D.: Digging deeper: participation and non-participation in post-disaster community recovery, Community Development, 43, 614–629, https://doi.org/10.1080/15575330.2012.730538, 2012. a, b
Chandrasekhar, D., Zhang, Y., and Xiao, Y.: Nontraditional Participation in Disaster Recovery Planning: Cases From China, India, and the United States, J. Am. Plann. Assoc., 80, 373–384, https://doi.org/10.1080/01944363.2014.989399, 2014. a
Chang, S. E.: Modeling how cities recover from disasters, in: International Conference on Urban Disaster Reduction, Kobe, Japan, January 2005, 18–20, 2005. a
Chang, S. E.: Urban disaster recovery: a measurement framework and its application to the 1995 Kobe earthquake, Disasters, 34, 303–327, https://doi.org/10.1111/j.1467-7717.2009.01130.x, 2010. a
Charles, S. H., Chang-Richards, A., and Yiu, T. W.: What do post-disaster reconstruction project success indicators look like? End-user’s perspectives, International Journal of Disaster Resilience in the Built Environment, 13, 31–50, https://doi.org/10.1108/IJDRBE-11-2020-0112, 2021. a
Charny, J. and Martin, S.: Sri Lanka: Tsunami Survivors Yearn for Permanent Housing and Employment, Refugees International, https://www.refworld.org/docid/47a6eec78.html (last access: 24 October 2023), 2005. a
Chen, K.-T., Chen, W. J., Malilay, J., and Twu, S.-J.: The Public Health Response to the Chi-Chi Earthquake in Taiwan, 1999, Public Health Rep., 118, 493–499, 2016. a
Cheng, S., Ganapati, E., and Ganapati, S.: Measuring disaster recovery: bouncing back or reaching the counterfactual state?, Disasters, 39, 427–446, https://doi.org/10.1111/disa.12112, 2015. a
Cheng, Y., Elsayed, E. A., and Chen, X.: Random Multi Hazard Resilience Modeling of Engineered Systems and Critical Infrastructure, Reliab. Eng. Syst. Safe, 209, 107453, https://doi.org/10.1016/j.ress.2021.107453, 2021. a, b
Chhibber, A. and Laajaj, R.: Natural disasters and economic development impact, response and preparedness, Global Development Network, https://www.researchgate.net/publication/265198864_Natural_Disasters_and_Economic_Development_Impact_Response_and_Preparedness (last access: 24 October 2023), 2007. a
Clinton, W. J.: Lessons learned from tsunami recovery: Key propositions for building back better, New York: Office of the UN Secretary-General's Special Envoy for Tsunami Recovery, https://www.preventionweb.net/files/2054_VL108301.pdf (last access: 24 October 2023), 2006. a
Coaffee, J.: Risk, resilience, and environmentally sustainable cities, Energ. Policy, 36, 4633–4638, https://doi.org/10.1016/j.enpol.2008.09.048, 2008. a
Coetzee, C. and Van, N. D.: Tracking the evolution of the disaster management cycle: a general system theory approach: original research, Jamba: Journal of Disaster Risk Studies, 4, 1–9, https://doi.org/10.4102/jamba.v4i1.54, 2012. a
Comerio, M. C.: Disaster Recovery and Community Renewal: Housing Approaches, Cityscape, 16, 51–68, 2014. a
Contreras, D.: Fuzzy Boundaries Between Post-Disaster Phases: The Case of L'Aquila, Italy, Int. J. Disast. Risk Sc., 7, 277–292, https://doi.org/10.1007/s13753-016-0095-4, 2016. a
Contreras, D., Blaschke, T., Kienberger, S., and Zeil, P.: Spatial connectivity as a recovery process indicator: The L'Aquila earthquake, Technol. Forecast. Soc., 80, 1782–1803, https://doi.org/10.1016/j.techfore.2012.12.001, 2013. a, b
Contreras, D., Blaschke, T., Kienberger, S., and Zeil, P.: Myths and realities about the recovery of L'Aquila after the earthquake, Int. J. Disast. Risk Re., 8, 125–142, https://doi.org/10.1016/j.ijdrr.2014.02.001, 2014. a, b
Contreras, D., Blaschke, T., and Hodgson, M. E.: Lack of spatial resilience in a recovery process: Case L'Aquila, Italy, Technol. Forecast. Soc., 121, 76–88, https://doi.org/10.1016/j.techfore.2016.12.010, 2017. a
CRED: 2021 Disasters in numbers, Centre for Research on the Epidemiology of Disaster (CRED), https://reliefweb.int/report/world/2021-disasters-numbers (last access: 5 March 2023), 2022. a
Crosti, C., Duthinh, D., and Simiu, E.: Risk Consistency and Synergy in Multihazard Design, J. Struct. Eng., 137, 844–849, https://doi.org/10.1061/(ASCE)ST.1943-541X.0000335, 2011. a
Curt, C.: Multirisk: What trends in recent works? – A bibliometric analysis, Sci. Total Environ., 763, 142951, https://doi.org/10.1016/j.scitotenv.2020.142951, 2021. a
Cutter, S. L., Emrich, C. T., Mitchell, J. T., Boruff, B. J., Gall, M., Schmidtlein, M. C., Burton, C. G., and Melton, G.: The Long Road Home: Race, Class, and Recovery from Hurricane Katrina, Environment: Science and Policy for Sustainable Development, 48, 8–20, https://doi.org/10.3200/ENVT.48.2.8-20, 2006. a
Cutter, S. L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., and Webb, J.: A place-based model for understanding community resilience to natural disasters, Global Environ. Chang., 18, 598–606, https://doi.org/10.1016/j.gloenvcha.2008.07.013, 2008. a
da Silva, J., Kernaghan, S., and Luque, A.: A systems approach to meeting the challenges of urban climate change, International Journal of Urban Sustainable Development, 4, 125–145, https://doi.org/10.1080/19463138.2012.718279, 2012. a
Daly, P., Barenstein, J. D., Hollenbach, P., and Ninglekhu, S.: Post-disaster housing reconstruction in urban areas in Nepal, International Institute for Environment and Development (IIED), London, https://www.iied.org/sites/default/files/pdfs/migrate/10836IIED.pdf (last access: 24 October 2023), 2017. a, b
David R., G., Adam, R., Elliott, M., Keith, P., and Carol, T. W.: Estimating the value of foresight: aggregate analysis of natural hazard mitigation benefits and costs, J. Environ. Plann. Man., 52, 739–756, https://doi.org/10.1080/09640560903083715, 2009. a
Davidson, C. H., Johnson, C., Lizarralde, G., Dikmen, N., and Sliwinski, A.: Truths and myths about community participation in post-disaster housing projects, Habitat Int., 31, 100–115, https://doi.org/10.1016/j.habitatint.2006.08.003, 2007. a
Davis, I.: Learning from Disaster Recovery: Guidance for Decision Makers: Executive Summary, International Recovery Platform, https://www.undrr.org/publication/learning-disaster-recovery-guidance-decision-makers-executive-summary (last access: 24 October 2023), 2007. a, b
Davoudi, S., Shaw, K., Haider, L. J., Quinlan, A. E., Peterson, G. D., Wilkinson, C., Fünfgeld, H., McEvoy, D., Porter, L., and Davoudi, S.: Resilience: A Bridging Concept or a Dead End? “Reframing” Resilience: Challenges for Planning Theory and Practice Interacting Traps: Resilience Assessment of a Pasture Management System in Northern Afghanistan Urban Resilience: What Does it Mean in Planning Practice? Resilience as a Useful Concept for Climate Change Adaptation? The Politics of Resilience for Planning: A Cautionary Note, Planning Theory & Practice, 13, 299–333, https://doi.org/10.1080/14649357.2012.677124, 2012. a
De Angeli, S., Malamud, B. D., Rossi, L., Taylor, F. E., Trasforini, E., and Rudari, R.: A multi-hazard framework for spatial-temporal impact analysis, Int. J. Disast. Risk Re., 73, 102829, https://doi.org/10.1016/j.ijdrr.2022.102829, 2022. a, b, c, d
de Ruiter, M. C., Couasnon, A., van den Homberg, M. J. C., Daniell, J. E., Gill, J. C., and Ward, P. J.: Why We Can No Longer Ignore Consecutive Disasters, Earth's Future, 8, e2019EF001425, https://doi.org/10.1029/2019EF001425, 2020. a, b, c
de Ruiter, M. C., de Bruijn, J. A., Englhardt, J., Daniell, J. E., de Moel, H., and Ward, P. J.: The Asynergies of Structural Disaster Risk Reduction Measures: Comparing Floods and Earthquakes, Earth's Future, 9, e2020EF001531, https://doi.org/10.1029/2020EF001531, 2021. a
Deen, S.: Pakistan 2010 floods. Policy gaps in disaster preparedness and response, Int. J. Disast. Risk Re., 12, 341–349, https://doi.org/10.1016/j.ijdrr.2015.03.007, 2015. a
Degg, M. R. and Chester, D. K.: Seismic and volcanic hazards in Peru: changing attitudes to disaster mitigation, Geogr. J., 171, 125–145, 2005. a
Delilah Roque, A., Pijawka, D., and Wutich, A.: The Role of Social Capital in Resiliency: Disaster Recovery in Puerto Rico, Risk, Hazards & Crisis in Public Policy, 11, 204–235, https://doi.org/10.1002/rhc3.12187, 2020. a, b
Der Sarkissian, R., Abdallah, C., Zaninetti, J.-M., and Najem, S.: Modelling intra-dependencies to assess road network resilience to natural hazards, Nat. Hazards, 103, 121–137, https://doi.org/10.1007/s11069-020-03962-5, 2020. a, b
Der Sarkissian, R., Dabaj, A., Diab, Y., and Vuillet, M.: Evaluating the Implementation of the “Build-Back-Better” Concept for Critical Infrastructure Systems: Lessons from Saint-Martin’s Island Following Hurricane Irma, Sustainability, 13, 3133, https://doi.org/10.3390/su13063133, 2021. a
Der Sarkissian, R., Cariolet, J.-M., Diab, Y., and Vuillet, M.: Investigating the importance of critical infrastructures' interdependencies during recovery; lessons from Hurricane Irma in Saint-Martin's island, Int. J. Disast. Risk Re., 67, 102675, https://doi.org/10.1016/j.ijdrr.2021.102675, 2022. a
Desouza, K. C. and Flanery, T. H.: Designing, planning, and managing resilient cities: A conceptual framework, Cities, 35, 89–99, https://doi.org/10.1016/j.cities.2013.06.003, 2013. a
Dong, S., Malecha, M., Farahmand, H., Mostafavi, A., Berke, P. R., and Woodruff, S. C.: Integrated infrastructure-plan analysis for resilience enhancement of post-hazards access to critical facilities, Cities, 117, 103318, https://doi.org/10.1016/j.cities.2021.103318, 2021. a
Du, L. and Peeta, S.: A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions, Networks and Spatial Economics, 14, 271–295, https://doi.org/10.1007/s11067-013-9219-1, 2014.
Dudenhoeffer, D. D., Permann, M. R., and Manic, M.: CIMS: A Framework for Infrastructure Interdependency Modeling and Analysis, in: Proceedings of the 2006 Winter Simulation Conference, 478–485, 3–6 December 2006, Monterey, CA, USA, https://doi.org/10.1109/WSC.2006.323119, 2006. a
Dunford, M. and Li, L.: Earthquake reconstruction in Wenchuan: Assessing the state overall plan and addressing the “forgotten phase”, Appl. Geogr., 31, 998–1009, https://doi.org/10.1016/j.apgeog.2011.01.001, 2011. a, b, c
Durham, K.: Treating the risks in Cairns, Nat. Hazards, 30, 251–261, https://doi.org/10.1023/A:1026174602731, 2003. a
Dwyer, C. and Horney, J.: Validating Indicators of Disaster Recovery with Qualitative Research, PLoS Currents, 6, ecurrents.dis.ec60 859ff436 919e096d51ef7d50 736f, https://doi.org/10.1371/currents.dis.ec60859ff436919e096d51ef7d50736f, 2014. a
Esteban, M., Onuki, M., Ikeda, I., and Akiyama, T.: Chapter 29 – Reconstruction Following the 2011 Tohoku Earthquake Tsunami: Case Study of Otsuchi Town in Iwate Prefecture, Japan, in: Handbook of Coastal Disaster Mitigation for Engineers and Planners, edited by: Esteban, M., Takagi, H., and Shibayama, T., 615–631, Butterworth-Heinemann, https://doi.org/10.1016/B978-0-12-801060-0.00029-0, 2015. a
Fang, Y. and Zio, E.: Game-Theoretic Decision Making for the Resilience of Interdependent Infrastructures Exposed to Disruptions, in: Critical Infrastructure Security and Resilience: Theories, Methods, Tools and Technologies, edited by: Gritzalis, D., Theocharidou, M., and Stergiopoulos, G., Advanced Sciences and Technologies for Security Applications, 97–114, Springer International Publishing, https://doi.org/10.1007/978-3-030-00024-0_6, 2019a.
Fang, Y.-P. and Zio, E.: An adaptive robust framework for the optimization of the resilience of interdependent infrastructures under natural hazards, Eur. J. Oper. Res., 276, 1119–1136, https://doi.org/10.1016/j.ejor.2019.01.052, 2019b.
Fang, Y.-P., Pedroni, N., and Zio, E.: Resilience-Based Component Importance Measures for Critical Infrastructure Network Systems, IEEE T. Reliab., 65, 502–512, https://doi.org/10.1109/TR.2016.2521761, 2016. a
Fernandez, G. and Ahmed, I.: “Build back better” approach to disaster recovery: Research trends since 2006, Progress in Disaster Science, 1, 100003, https://doi.org/10.1016/j.pdisas.2019.100003, 2019. a, b, c
Folke, C.: Resilience: The emergence of a perspective for social–ecological systems analyses, Global Environ. Chang., 16, 253–267, https://doi.org/10.1016/j.gloenvcha.2006.04.002, 2006. a
Forino, G.: Disaster recovery: narrating the resilience process in the reconstruction of L’Aquila (Italy), Geogr. TIDSSKR, 115, 1–13, https://doi.org/10.1080/00167223.2014.973056, 2015. a
Freeman, P. K.: Allocation of post-disaster reconstruction financing to housing, Build. Res. Inf., 32, 427–437, https://doi.org/10.1080/0961321042000221016, 2004. a
Fussell, E.: The Long-Term Recovery of New Orleans’ Population After Hurricane Katrina, Am. Behav. Sci., 59, 1231–1245, https://doi.org/10.1177/0002764215591181, 2015. a
Gaillard, J.-C. and Mercer, J.: From knowledge to action: Bridging gaps in disaster risk reduction, Prog. Hum. Geog., 37, 93–114, https://doi.org/10.1177/0309132512446717, 2013. a
Ganapati, N. E. and Mukherji, A.: Out of Sync: World Bank Funding for Housing Recovery, Postdisaster Planning, and Participation, Nat. Hazards Rev., 15, 58–73, https://doi.org/10.1061/(ASCE)NH.1527-6996.0000120, 2014. a
Garnett, J. D. and Moore, M.: Enhancing Disaster Recovery: Lessons from Exemplary International Disaster Management Practices, J. Homel. Secur. Emerg., 7, 40, https://doi.org/10.2202/1547-7355.1711, 2010. a
Cremen, G., Galasso, C., McCloskey, J., Barcena, A., Creed, M., Filippi, M. E., Gentile, R., Jenkins, L. T., Kalaycioglu, M., Mentese, E. Y., Muthusamy, M., Tarbali, K., and Trogrlić, R. Š.: A state-of-the-art decision-support environment for risk-sensitive and pro-poor urban planning and design in Tomorrow's cities, Int. J. Disast., 85, 103400, https://doi.org/10.1016/j.ijdrr.2022.103400, 2023 a
Gentile, R., Galasso, C., Idris, Y., Rusydy, I., and Meilianda, E.: From rapid visual survey to multi-hazard risk prioritisation and numerical fragility of school buildings, Nat. Hazards Earth Syst. Sci., 19, 1365–1386, https://doi.org/10.5194/nhess-19-1365-2019, 2019. a, b
GFDRR: Post-Disaster Needs Assessments, Volume A. Guidelines, European Commission, United Nations Development Group, and Global Facility for Disaster Reduction and Recovery, https://www.gfdrr.org/en/publication/post-disaster-needs-assessments-guidelines-volume-2013 (last access: 24 October 2023), 2013. a, b
Ghannad, P., Lee, Y.-C., Friedland, C. J., Choi, J. O., and Yang, E.: Multiobjective Optimization of Postdisaster Reconstruction Processes for Ensuring Long-Term Socioeconomic Benefits, J. Manage. Eng., 36, 04020038, https://doi.org/10.1061/(ASCE)ME.1943-5479.0000799, 2020. a
Ghorbani-Renani, N., González, A. D., Barker, K., and Morshedlou, N.: Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience, Reliab. Eng. Syst. Safe, 199, 106907, https://doi.org/10.1016/j.ress.2020.106907, 2020. a
Gill, J. C. and Malamud, B. D.: Reviewing and visualizing the interactions of natural hazards, Rev. Geophys., 52, 680–722, https://doi.org/10.1002/2013RG000445, 2014. a
Gill, J. C. and Malamud, B. D.: Hazard interactions and interaction networks (cascades) within multi-hazard methodologies, Earth Syst. Dynam., 7, 659–679, https://doi.org/10.5194/esd-7-659-2016, 2016. a
Goldschmidt, K. H. and Kumar, S.: Reducing the cost of humanitarian operations through disaster preparation and preparedness, Ann. Oper. Res., 283, 1139–1152, 2019. a
Grant, M. J. and Booth, A.: A typology of reviews: an analysis of 14 review types and associated methodologies, Health Information & Libraries Journal, 26, 91–108, https://doi.org/10.1111/j.1471-1842.2009.00848.x, 2009. a
Guidotti, R., Gardoni, P., and Rosenheim, N.: Integration of physical infrastructure and social systems in communities’ reliability and resilience analysis, Reliab. Eng. Syst. Safe, 185, 476–492, https://doi.org/10.1016/j.ress.2019.01.008, 2019.
Haas, J., Kates, R., Bowden, M., and Amaral, D.: Reconstruction Following Disaster, Environmental Studies Series, MIT Press, ISBN 9780262080941, 1977. a
He, L.: We need land first: Identifying local needs for sustainable recovery after the 2015 Gorkha earthquake, Nepal, WIDER Working Paper Series wp-2018-62, World Institute for Development Economic Research (UNU-WIDER), Helsinki, Finland, https://doi.org/10.35188/UNU-WIDER/2018/504-6, 2018. a
He, L.: Identifying local needs for post-disaster recovery in Nepal, World Dev., 118, 52–62, https://doi.org/10.1016/j.worlddev.2019.02.005, 2019. a, b
He, L., Aitchison, J. C., Hussey, K., Wei, Y., and Lo, A.: Accumulation of vulnerabilities in the aftermath of the 2015 Nepal earthquake: Household displacement, livelihood changes and recovery challenges, Int. J. Disast. Risk Re., 31, 68–75, https://doi.org/10.1016/j.ijdrr.2018.04.017, 2018. a
He, L., Aitchison, J. C., Hussey, K., and Chen, Y.: Building new houses or long-term recovery? A combination of quantitative and qualitative evidence from earthquake-displaced households in Sichuan, China, Habitat Int., 83, 135–145, https://doi.org/10.1016/j.habitatint.2018.12.002, 2019. a, b
He, X. and Cha, E. J.: DIN II: incorporation of multi-level interdependencies and uncertainties for infrastructure system recovery modeling, Struct. Infrastruct. E., 17, 1566–1581, https://doi.org/10.1080/15732479.2020.1817104, 2021. a
Heo, B.-Y. and Heo, W.-H.: Economic Analysis of Disaster Management Investment Effectiveness in Korea, Sustainability, 11, 3011, https://doi.org/10.3390/su11113011, 2019. a
Hinzpeter, K. and Sandholz, S.: Squaring the circle? Integrating environment, infrastructure and risk reduction in Post Disaster Needs Assessments, Int. J. Disast. Risk Re., 32, 113–124, https://doi.org/10.1016/j.ijdrr.2018.05.016, 2018. a, b
Hochrainer-Stigler, S., Šakić Trogrlić, R., Reiter, K., Ward, P. J., de Ruiter, M. C., Duncan, M. J., Torresan, S., Ciurean, R., Mysiak, J., Stuparu, D., and Gottardo, S.: Toward a framework for systemic multi-hazard and multi-risk assessment and management, iScience, 26, 106736, https://doi.org/10.1016/j.isci.2023.106736, 2023. a, b
Holling, C. S.: Resilience and Stability of Ecological Systems, Annual Review of Ecology and Systematics, 4, 1–23, https://doi.org/10.1146/annurev.es.04.110173.000245, 1973. a
Gunderson, L. H. and Holling, C. S.: Panarchy: understanding transformations in human and natural systems, Island Press, Washington, DC, 507 pp., ISBN 1559638575, 2002. a
Holton, G. E. L.: Disasters and Democracy: The Politics of Extreme Natural Events, Electronic Green Journal, 1, 13, https://doi.org/10.5070/G311310409, 2000. a
Honjo, Y.: Implementation of the Kobe City Recovery Plan, Japan Social Innovation Journal, 1, 1–11, https://doi.org/10.12668/jsij.1.1, 2011. a
Horney, J., Nguyen, M., Salvesen, D., Tomasco, O., and Berke, P.: Engaging the public in planning for disaster recovery, Int. J. Disast. Risk Re., 17, 33–37, https://doi.org/10.1016/j.ijdrr.2016.03.011, 2016. a
Ingram, J. C., Franco, G., Rumbaitis-del Rio, C., and Khazai, B.: Post-disaster recovery dilemmas: challenges in balancing short-term and long-term needs for vulnerability reduction, Environ. Sci. Policy, 9, 607–613, https://doi.org/10.1016/j.envsci.2006.07.006, 2006. a, b
Ismail, D., Majid, T. A., Roosli, R., and Ab Samah, N.: Project management success for post-disaster reconstruction projects: International NGOs perspectives, Proc. Econ. Financ., 18, 120–127, https://doi.org/10.1016/S2212-5671(14)00921-6, 2014. a
Iuchi, K.: Planning resettlement after disasters, J. Am. Plann. Assoc., 80, 413–425, https://doi.org/10.1080/01944363.2014.978353, 2014. a
Iuchi, K., Maly, E., and Johnson, L.: Three Years After a Mega-disaster: Recovery Policies, Programs and Implementation After the Great East Japan Earthquake, in: Post-Tsunami Hazard: Reconstruction and Restoration, edited by: Santiago-Fandiño, V., Kontar, Y., and Kaneda, Y., Advances in Natural and Technological Hazards Research, 29–46, Springer International Publishing, https://doi.org/10.1007/978-3-319-10202-3_3, 2015. a
Jenkins, L. T., Creed, M. J., Tarbali, K., Muthusamy, M., Šakić Trogrlić, R., Phillips, J. C., Watson, C. S., Sinclair, H. D., Galasso, C., and McCloskey, J.: Physics-based simulations of multiple natural hazards for risk-sensitive planning and decision making in expanding urban regions, Int. J. Disast. Risk Re., 84, 103338, https://doi.org/10.1016/j.ijdrr.2022.103338, 2023. a
Kates, R. W. and Pijawka, D.: From rubble to monument: the pace of reconstruction, in: Reconstruction Following Disaster, edited by: Haas, J., Kates, R., Bowden, M., and Amaral, D., 1–23, MIT Press, Cambridge, MA, 1977. a
Kates, R. W., Colten, C. E., Laska, S., and Leatherman, S. P.: Reconstruction of New Orleans after Hurricane Katrina: A research perspective, P. Natl. Acad. Sci. USA, 103, 14653–14660, https://doi.org/10.1073/pnas.0605726103, 2006. a
Kawasaki, A. and Rhyner, J.: Investing in Disaster Risk Reduction for Resilience: Roles of Science, Technology, and Education, Journal of Disaster Research, 13, 1181–1186, https://doi.org/10.20965/jdr.2018.p1181, 2018. a
Kennedy, J., Ashmore, J., Babister, E., and Kelman, I.: The Meaning of “Build Back Better”: Evidence From Post-Tsunami Aceh and Sri Lanka, J. Conting. Crisis Man., 16, 24–36, https://doi.org/10.1111/j.1468-5973.2008.00529.x, 2008. a, b, c
Kim, K. and Olshansky, R. B.: The Theory and Practice of Building Back Better, J. Am. Plann. Assoc., 80, 289–292, https://doi.org/10.1080/01944363.2014.988597, 2014. a
Klein, R. J., Nicholls, R. J., and Thomalla, F.: Resilience to natural hazards: How useful is this concept?, Global Environmental Change Part B: Environmental Hazards, 5, 35–45, https://doi.org/10.1016/j.hazards.2004.02.001, 2003. a
Kousky, C., Ritchie, L., Tierney, K., and Lingle, B.: Return on investment analysis and its applicability to community disaster preparedness activities: Calculating costs and returns, Int. J. Disast. Risk Re, 41, 101296, https://doi.org/10.1016/j.ijdrr.2019.101296, 2019. a
Kurosaki, T.: Household-Level Recovery after Floods in a Tribal and Conflict-Ridden Society, World Dev., 94, 51–63, https://doi.org/10.1016/j.worlddev.2016.12.039, 2017. a, b
Labadie, J. R.: Auditing of post‐disaster recovery and reconstruction activities, Disaster Prev. Manag., 17, 575–586, https://doi.org/10.1108/09653560810918612, 2008. a
Leichenko, R.: Climate change and urban resilience, Curr. Opin. Env. Sust., 3, 164–168, https://doi.org/10.1016/j.cosust.2010.12.014, 2011. a
Levine, J. N., Esnard, A.-M., and Sapat, A.: Population Displacement and Housing Dilemmas Due to Catastrophic Disasters, J. Plan. Lit., 22, 3–15, https://doi.org/10.1177/0885412207302277, 2007. a
Li, Y., Ahuja, A., and Padgett, J. E.: Review of Methods to Assess, Design for, and Mitigate Multiple Hazards, J. Perform. Constr. Fac., 26, 104–117, https://doi.org/10.1061/(ASCE)CF.1943-5509.0000279, 2012. a
Liu, N., Zhang, J., Lin, W., Cheng, W., and Chen, Z.: Draining Tangjiashan Barrier Lake after Wenchuan Earthquake and the flood propagation after the dam break, Sci. China Ser. E, 52, 801–809, https://doi.org/10.1007/s11431-009-0118-0, 2009. a
Liu, W., Song, Z., Ouyang, M., and Li, J.: Recovery-based seismic resilience enhancement strategies of water distribution networks, Reliab. Eng. Syst. Safe., 203, 107088, https://doi.org/10.1016/j.ress.2020.107088, 2020.
Liu, X., Ferrario, E., and Zio, E.: Resilience Analysis Framework for Interconnected Critical Infrastructures, ASCE-ASME J. Risk and Uncert. in Engrg. Sys. Part B Mech. Engrg., 3, RISK-15-1115, https://doi.org/10.1115/1.4035728, 2017. a
Liu, X., Fang, Y.-P., and Zio, E.: A Hierarchical Resilience Enhancement Framework for Interdependent Critical Infrastructures, Reliab. Eng. Syst. Safe., 215, 107868, https://doi.org/10.1016/j.ress.2021.107868, 2021.
Lyons, M.: Building Back Better: The Large-Scale Impact of Small-Scale Approaches to Reconstruction, World Dev., 37, 385–398, https://doi.org/10.1016/j.worlddev.2008.01.006, 2009. a
MacRae, G. and Hodgkin, D.: Beyond the 2006 Yogyakarta Earthquake, in: Rebuilding Asia Following Natural Disasters: Approaches to Reconstruction in the Asia-Pacific Region, 261–283, Cambridge University Press, https://doi.org/10.1017/CBO9781139683548.011, 2016. a
Malilay, J., Flanders, W. D., and Brogan, D.: A modified cluster-sampling method for post-disaster rapid assessment of needs., B. World Health Organ., 74, 399–405, 1996. a
Mannella, A., Di Ludovico, M., Sabino, A., Prota, A., Dolce, M., and Manfredi, G.: Analysis of the Population Assistance and Returning Home in the Reconstruction Process of the 2009 L’Aquila Earthquake, Sustainability, 9, 1395, https://doi.org/10.3390/su9081395, 2017. a
Manyena, B., Machingura, F., and O'Keefe, P.: Disaster Resilience Integrated Framework for Transformation (DRIFT): A new approach to theorising and operationalising resilience, World Dev., 123, 104587, https://doi.org/10.1016/j.worlddev.2019.06.011, 2019. a
Marshall, M. I. and Schrank, H. L.: Small business disaster recovery: a research framework, Nat. Hazards, 72, 597–616, https://doi.org/10.1007/s11069-013-1025-z, 2014. a
Marzocchi, W., Di Ruocco, A., and Mastellone, M. L.: Principles of multi-risk assessment: interaction amongst natural and man-induced risks, European Commission, ISBN 978-92-79-07963-4, 2009. a
Marzocchi, W., Garcia-Aristizabal, A., Gasparini, P., Mastellone, M. L., and Di Ruocco, A.: Basic principles of multi-risk assessment: a case study in Italy, Nat. Hazards, 62, 551–573, https://doi.org/10.1007/s11069-012-0092-x, 2012. a
Masiero, G. and Santarossa, M.: Natural disasters and electoral outcomes, Eur. J. Polit. Econ., 67, 101983, https://doi.org/10.1016/j.ejpoleco.2020.101983, 2021. a
McEntire, D. A., Fuller, C., Johnston, C. W., and Weber, R.: A Comparison of Disaster Paradigms: The Search for a Holistic Policy Guide, Public Admin. Rev., 62, 267–281, https://doi.org/10.1111/1540-6210.00178, 2002. a, b
Meerow, S., Newell, J. P., and Stults, M.: Defining urban resilience: A review, Landscape Urban Plan., 147, 38–49, https://doi.org/10.1016/j.landurbplan.2015.11.011, 2016. a, b
Mileti, D.: Disasters by Design: A Reassessment of Nat. Hazards in the United States, The National Academies Press, Washington, DC, ISBN 978-0-309-26173-9, https://doi.org/10.17226/5782, 1999. a, b
Miri, M., Raziei, T., Zand, M., and Kousari, M. R.: Synoptic aspects of two flash flood-inducing heavy rainfalls in southern Iran during 2019–2020, Nat. Hazards, 115, 2655–2672, https://doi.org/10.1007/s11069-022-05658-4, 2023. a
Mitsova, D., Escaleras, M., Sapat, A., Esnard, A.-M., and Lamadrid, A. J.: The Effects of Infrastructure Service Disruptions and Socio-Economic Vulnerability on Hurricane Recovery, Sustainability, 11, 516, https://doi.org/10.3390/su11020516, 2019. a
Mudassir, G.: Social-Based Physical Reconstruction Planning in Case of Natural Disaster: A Machine Learning Approach, in: Research Challenges in Information Science, edited by: Dalpiaz, F., Zdravkovic, J., and Loucopoulos, P., Lecture Notes in Business Information Processing, 604–612, Springer International Publishing, https://doi.org/10.1007/978-3-030-50316-1_44, 2020.
Muskat, B., Nakanishi, H., and Blackman, D.: Integrating tourism into disaster recovery management: the case of the Great East Japan Earthquake and Tsunami 2011, CABI Series in Tourism Management Research, 97–115, https://www.cabidigitallibrary.org/doi/abs/10.1079/9781780643250.0097 (last access: 10 October 2023), 2015. a
Mutch, C.: The role of schools in disaster preparedness, response and recovery: what can we learn from the literature?, Pastoral Care in Education, 32, 5–22, https://doi.org/10.1080/02643944.2014.880123, 2014. a
Nakanishi, H. and Black, J.: Implicit and explicit knowledge in flood evacuations with a case study of Takamatsu, Japan, Int. J. Disast. Risk Re., 28, 788–797, https://doi.org/10.1016/j.ijdrr.2018.02.008, 2018. a, b, c, d
Naserieh, S., Ghofrani, H., Shoja-Taheri, J., Dezvareh, M., and Mirzaei Alavijeh, H.: Strong Ground-Motion Characteristics Observed in the November 12, 2017, Mw7.3 Sarpol-e Zahab, Iran Earthquake, J. Earthq. Eng., 26, 3488–3505, https://doi.org/10.1080/13632469.2020.1806950, 2022. a
Nelson, D. R., Adger, W. N., and Brown, K.: Adaptation to Environmental Change: Contributions of a Resilience Framework, Annu. Rev. Env. Resour., 32, 395–419, https://doi.org/10.1146/annurev.energy.32.051807.090348, 2007. a
Oliver-Smith, A.: Post-Disaster Housing Reconstruction and Social Inequality: A Challenge to Policy and Practice, Disasters, 14, 7–19, https://doi.org/10.1111/j.1467-7717.1990.tb00968.x, 1990. a
Olshansky, R. B.: Planning after hurricane Katrina, J. Am. Plann. Assoc., 72, 147–153, https://doi.org/10.1080/01944360608976735, 2006. a
Omarzadeh, D., Karimzadeh, S., Matsuoka, M., and Feizizadeh, B.: Earthquake Aftermath from Very High-Resolution WorldView-2 Image and Semi-Automated Object-Based Image Analysis (Case Study: Kermanshah, Sarpol-e Zahab, Iran), Remote Sens., 13, 4272, https://doi.org/10.3390/rs13214272, 2021. a
Ouyang, M.: Review on modeling and simulation of interdependent critical infrastructure systems, Reliab. Eng. Syst. Safe, 121, 43–60, https://doi.org/10.1016/j.ress.2013.06.040, 2014. a
Ouyang, M., Dueñas-Osorio, L., and Min, X.: A three-stage resilience analysis framework for urban infrastructure systems, Struct. Saf., 36–37, 23–31, https://doi.org/10.1016/j.strusafe.2011.12.004, 2012.
Ouyang, M., Liu, C., and Xu, M.: Value of resilience-based solutions on critical infrastructure protection: Comparing with robustness-based solutions, Reliab. Eng. Syst. Safe, 190, 106506, https://doi.org/10.1016/j.ress.2019.106506, 2019.
Pant, R., Barker, K., and Zobel, C. W.: Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors, Reliab. Eng. Syst. Safe, 125, 92–102, https://doi.org/10.1016/j.ress.2013.09.007, 2014. a
Parker, R. S.: Hazards of Nature, Risks to Development, The World Bank, https://doi.org/10.1596/978-0-8213-6650-9, 2006. a
Peacock, W., Morrow, B. H., and Gladwin, H.: Hurricane Andrew and the reshaping of Miami: Ethnicity, gender, and the socio-political ecology of disasters, Routledge, London, 1st edn., https://doi.org/10.4324/9780203351628, 1997. a
Perce, K. H.: Disaster recovery: lessons learned from an occupational health and human resources perspective, AAOHN journal: official journal of the American Association of Occupational Health Nurses, 55, 235–240, https://doi.org/10.1177/216507990705500603, 2007. a
Platt, S. and So, E.: Speed or deliberation: a comparison of post-disaster recovery in Japan, Turkey, and Chile, Disasters, 41, 696–727, https://doi.org/10.1111/disa.12219, 2017. a
Quarantelli, E. L.: The Disaster Recovery Process: What We Know And Do Not Know From Research, in: International Forum on Civil Protection, 20 March 1999, Foligno, Italy, https://api.semanticscholar.org/CorpusID:128100676 (last access: 10 October 2023), 1999. a
Raju, E. and Becker, P.: Multi-organisational coordination for disaster recovery: The story of post-tsunami Tamil Nadu, India, Int. J. Disast. Risk Re., 4, 82–91, https://doi.org/10.1016/j.ijdrr.2013.02.004, 2013. a, b
Rinaldi, S., Peerenboom, J., and Kelly, T.: Identifying, understanding, and analyzing critical infrastructure interdependencies, IEEE Contr. Syst. Mag., 21, 11–25, https://doi.org/10.1109/37.969131, 2001. a
Rind, D.: Complexity and Climate, Science, 284, 105–107, https://doi.org/10.1126/science.284.5411.105, 1999. a
Ritchie, H. and Roser, M.: Urbanization, Our World in Data, https://ourworldindata.org/urbanization (last access: 24 October 2023), 2018. a
Rodríguez, H., Donner, W., and Trainor, J. E. (Eds.): Handbook of Disaster Research, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-319-63254-4, 2018. a
Rosato, V., Pietro, A. D., Kotzanikolaou, P., Stergiopoulos, G., and Smedile, G.: Integrating Resilience in Time-based Dependency Analysis: A Large-Scale Case Study for Urban Critical Infrastructures, in: Issues on Risk Analysis for Critical Infrastructure Protection, edited by: Rosato, V. and Pietro, A. D., chap. 5, IntechOpen, Rijeka, https://doi.org/10.5772/intechopen.97809, 2021.
Rosenheim, N., Guidotti, R., Gardoni, P., and Peacock, W. G.: Integration of detailed household and housing unit characteristic data with critical infrastructure for post-hazard resilience modeling, Sustainable and Resilient Infrastructure, 6, 385–401, https://doi.org/10.1080/23789689.2019.1681821, 2021.
Rotimi, J. O., Wilkinson, S., Zuo, K., and Myburgh, D.: Legislation for effective post‐disaster reconstruction, Int. J. Strateg. Prop. M., 13, 143–152, https://doi.org/10.3846/1648-715X.2009.13.143-152, 2009. a
Rubin, C. B.: Long Term Recovery from Disasters – The Neglected Component of Emergency Management, J. Homel. Secur. Emerg., 6, 46, https://doi.org/10.2202/1547-7355.1616, 2009. a, b
Rubin, C. B. and Barbee, D. G.: Disaster Recovery and Hazard Mitigation: Bridging the Intergovernmental Gap, Public Admin. Rev., 45, 57–63, https://doi.org/10.2307/3134998, 1985. a, b
Runkle, J. D., Brock-Martin, A., Karmaus, W., and Svendsen, E. R.: Secondary Surge Capacity: A Framework for Understanding Long-Term Access to Primary Care for Medically Vulnerable Populations in Disaster Recovery, Am. J. Public Health, 102, e24–e32, https://doi.org/10.2105/AJPH.2012.301027, 2012. a
Rus, K., Kilar, V., and Koren, D.: Resilience assessment of complex urban systems to natural disasters: A new literature review, Int. J. Disast. Risk Re., 31, 311–330, https://doi.org/10.1016/j.ijdrr.2018.05.015, 2018. a, b
Ryan, R., Wortley, L., and She, E.: Evaluations of post-disaster recovery: A review of practice material, Evidence Base, 4, 1–33, https://doi.org/10.21307/eb-2016-001, 2016. a
Rykiel Jr., E. J.: Towards a definition of ecological disturbance, Aust. J. Ecol., 10, 361–365, https://doi.org/10.1111/j.1442-9993.1985.tb00897.x, 1985. a
Sadiqi, Z., Trigunarsyah, B., and Coffey, V.: A framework for community participation in post-disaster housing reconstruction projects: A case of Afghanistan, Int. J. Proj. Manag., 35, 900–912, https://doi.org/10.1016/j.ijproman.2016.11.008, 2017. a
Schlumberger, J., Stuparu, D., Ciurean, R., Duncan, M., Mysiak, J., Khazai, B., Dochiu, C., and Claassen, J.: D1.3 – Report on policies, policy-making processes, and governance for multi-hazard, multi-risk management, https://www.myriadproject.eu/wp-content/uploads/2023/04/D1.3_Review-of-policy-and-governance_v3.pdf, project deliverable MYRIAD-EU (last access: 24 October 2023), 2022. a
Sevieri, G., Galasso, C., D'Ayala, D., De Jesus, R., Oreta, A., Grio, M. E. D. A., and Ibabao, R.: A multi-hazard risk prioritisation framework for cultural heritage assets, Nat. Hazards Earth Syst. Sci., 20, 1391–1414, https://doi.org/10.5194/nhess-20-1391-2020, 2020. a
Shaw, R., Gupta, M., and Sarma, A.: Community recovery and its sustainability: Lessons from Gujarat earthquake of India, The Australian Journal of Emergency Management, 18, 28–34, 2003. a
Smith, G., Martin, A., and Wenger, D. E.: Disaster Recovery in an Era of Climate Change: The Unrealized Promise of Institutional Resilience, in: Handbook of Disaster Research, edited by: Rodríguez, H., Donner, W., and Trainor, J. E., Handbooks of Sociology and Social Research, 595–619, Springer International Publishing, https://doi.org/10.1007/978-3-319-63254-4_28, 2018. a
Smith, G. P. and Wenger, D.: Sustainable Disaster Recovery: Operationalizing An Existing Agenda, in: Handbook of Disaster Research, edited by: Rodríguez, H., Quarantelli, E. L., and Dynes, R. R., Handbooks of Sociology and Social Research, 234–257, Springer, https://doi.org/10.1007/978-0-387-32353-4_14, 2007. a, b, c, d, e
Snyder, H.: Literature review as a research methodology: An overview and guidelines, J. Bus. Res., 104, 333–339, https://doi.org/10.1016/j.jbusres.2019.07.039, 2019. a
Sobhaninia, S. and Buckman, S. T.: Revisiting and adapting the Kates-Pijawka disaster recovery model: A reconfigured emphasis on anticipation, equity, and resilience, Int. J. Disast. Risk Re., 69, 102738, https://doi.org/10.1016/j.ijdrr.2021.102738, 2022. a, b, c, d
Soltani-Sobh, A., Heaslip, K., Scarlatos, P., and Kaisar, E.: Reliability based pre-positioning of recovery centers for resilient transportation infrastructure, Int. J. Disast. Risk Re., 19, 324–333, https://doi.org/10.1016/j.ijdrr.2016.09.004, 2016. a
Sovacool, B. K.: Don’t let disaster recovery perpetuate injustice, Nature, 549, 433–433, https://doi.org/10.1038/549433a, 2017. a
Staupe-Delgado, R.: Overcoming Barriers to Proactive Response in Slow-onset Disasters. Contributing Paper to GAR 2019, https://www.preventionweb.net/publications/view/66508 (last access: 24 October 2023), 2019. a
Su, Y. and Le Dé, L.: Whose views matter in post-disaster recovery? A case study of “build back better” in Tacloban City after Typhoon Haiyan, Int. J. Disast. Risk Re., 51, 101786, https://doi.org/10.1016/j.ijdrr.2020.101786, 2020. a
Sullivan, M.: Integrated Recovery Management: A New Way of Looking at a Delicate Process, The Australian Journal of Emergency Management, 18, 4–27, 2003. a
Talbot, J., Poleacovschi, C., Hamideh, S., and Santos-Rivera, C.: Informality in Postdisaster Reconstruction: The Role of Social Capital in Reconstruction Management in Post–Hurricane Maria Puerto Rico, J. Manage. Eng., 36, 04020074, https://doi.org/10.1061/(ASCE)ME.1943-5479.0000833, 2020. a
Tanner, T., Mitchell, T., Polack, E., and Guenther, B.: Urban Governance for Adaptation: Assessing Climate Change Resilience in Ten Asian Cities, IDS Working Papers, 2009, 01–47, https://doi.org/10.1111/j.2040-0209.2009.00315_2.x, 2009. a
Tatham, P. and Houghton, L.: The wicked problem of humanitarian logistics and disaster relief aid, Journal of Humanitarian Logistics and Supply Chain Management, 1, 15–31, https://doi.org/10.1108/20426741111122394, 2011. a
Terzi, S., De Angeli, S., Miozzo, D., Massucchielli, L. S., Szarzynski, J., Carturan, F., and Boni, G.: Learning from the COVID-19 pandemic in Italy to advance multi-hazard disaster risk management, Progress in Disaster Science, 16, 100268, https://doi.org/10.1016/j.pdisas.2022.100268, 2022. a, b
Thomalla, F., Lebel, L., Boyland, M., Marks, D., Kimkong, H., Tan, S. B., and Nugroho, A.: Long-term recovery narratives following major disasters in Southeast Asia, Reg. Environ. Change, 18, 1211–1222, https://doi.org/10.1007/s10113-017-1260-z, 2018. a
Tierney, K. and Oliver-Smith, A.: Social Dimensions of Disaster Recovery, International Journal of Mass Emergencies & Disasters, 30, 123–146, https://doi.org/10.1177/028072701203000210, 2012. a, b
Tilloy, A., Malamud, B. D., Winter, H., and Joly-Laugel, A.: A review of quantification methodologies for multi-hazard interrelationships, Earth-Sci. Rev., 196, 102881, https://doi.org/10.1016/j.earscirev.2019.102881, 2019. a
Twigg, J.: Disaster risk reduction, Overseas Development Institute, Humanitarian Policy Group London, https://odihpn.org/wp-content/uploads/2011/06/GPR-9-web-string-1.pdf (last access: 8 October 2023), 2015. a
UNDRR: International Recovery Platform, https://recovery.preventionweb.net/international-recovery-platform (last access: 25 September 2023), 2022. a
Vale, L. J. and Campanella, T. J.: The Resilient City: How Modern Cities Recover from Disaster, Oxford University Press, https://doi.org/10.1093/oso/9780195175844.001.0001, 2005. a
Šakić Trogrlić, R., Rijke, J., Dolman, N., and Zevenbergen, C.: Rebuild by Design in Hoboken: A Design Competition as a Means for Achieving Flood Resilience of Urban Areas through the Implementation of Green Infrastructure, Water, 10, 553, https://doi.org/10.3390/w10050553, 2018. a
Šakić Trogrlić, R., Duncan, M., Wright, G., van den Homberg, M., Adeloye, A., Mwale, F., and McQuistan, C.: External stakeholders’ attitudes towards and engagement with local knowledge in disaster risk reduction: are we only paying lip service?, Int. J. Disast. Risk Re., 58, 102196, https://doi.org/10.1016/j.ijdrr.2021.102196, 2021. a
Walker, B., Holling, C. S., Carpenter, S. R., and Kinzig, A.: Resilience, adaptability and transformability in social–ecological systems, Ecol. Soc., 9, 5, 2004. a
Ward, P. J., Daniell, J., Duncan, M., Dunne, A., Hananel, C., Hochrainer-Stigler, S., Tijssen, A., Torresan, S., Ciurean, R., Gill, J. C., Sillmann, J., Couasnon, A., Koks, E., Padrón-Fumero, N., Tatman, S., Tronstad Lund, M., Adesiyun, A., Aerts, J. C. J. H., Alabaster, A., Bulder, B., Campillo Torres, C., Critto, A., Hernández-Martín, R., Machado, M., Mysiak, J., Orth, R., Palomino Antolín, I., Petrescu, E.-C., Reichstein, M., Tiggeloven, T., Van Loon, A. F., Vuong Pham, H., and de Ruiter, M. C.: Invited perspectives: A research agenda towards disaster risk management pathways in multi-(hazard-)risk assessment, Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, 2022. a, b
Wilkinson, C.: Social-ecological resilience: Insights and issues for planning theory, Planning Theory, 11, 148–169, https://doi.org/10.1177/1473095211426274, 2012. a
Wong, G., Greenhalgh, T., Westhorp, G., Buckingham, J., and Pawson, R.: RAMESES publication standards: meta-narrative reviews, BMC Med., 11, 20, https://doi.org/10.1186/1741-7015-11-20, 2013. a
World Bank Group: Sierra Leone Rapid Damage and Loss Assessment of August 14th, 2017 Landslides and Floods in the Western Area, World Bank, https://doi.org/10.1596/28836, 2017. a
World Bank Group, United Nations, and European Union: Malawi Drought 2015–2016: Post-Disaster Needs Assessment, World Bank, https://doi.org/10.1596/25781, 2016. a
Xu, Z., Ramirez-Marquez, J. E., Liu, Y., and Xiahou, T.: A new resilience-based component importance measure for multi-state networks, Reliability Engineering & System Safety, 193, 106591, https://doi.org/10.1016/j.ress.2019.106591, 2020.
Yadollahie, M.: The Flood in Iran: A Consequence of the Global Warming?, The International Journal of Occupational and Environmental Medicine, 10, 54–56, https://doi.org/10.15171/ijoem.2019.1681, 2019. a
Yamaguchi, R., Sato, M., and Ueta, K.: Measuring Regional Wealth and Assessing Sustainable Development: An Application to a Disaster-Torn Region in Japan, Soc. Indic. Res., 129, 365–389, https://doi.org/10.1007/s11205-015-1106-3, 2016. a
Yu, J.-Z. and Baroud, H.: Modeling Uncertain and Dynamic Interdependencies of Infrastructure Systems Using Stochastic Block Models, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6, 020906, https://doi.org/10.1115/1.4046472, 2020.
Zamanifar, M. and Hartmann, T.: Optimization-based decision-making models for disaster recovery and reconstruction planning of transportation networks, Nat. Hazards, 104, 1–25, https://doi.org/10.1007/s11069-020-04192-5, 2020. a, b, c
Zhang, J., Zhang, M., and Li, G.: Multi-stage composition of urban resilience and the influence of pre-disaster urban functionality on urban resilience, Nat. Hazards, 107, 447–473, https://doi.org/10.1007/s11069-021-04590-3, 2021. a, b, c
Zhang, Q.: Disaster response and recovery: Aid and social change, Annals of Anthropological Practice, 40, 86–97, https://doi.org/10.1111/napa.12090, 2016. a
Zhang, W. and Wang, N.: Resilience-based risk mitigation for road networks, Struct. Saf., 62, 57–65, https://doi.org/10.1016/j.strusafe.2016.06.003, 2016. a
Özerdem, A. and Rufini, G.: L'Aquila's reconstruction challenges: has Italy learned from its previous earthquake disasters?, Disasters, 37, 119–143, https://doi.org/10.1111/j.1467-7717.2012.01296.x, 2013. a
Short summary
This paper critically reviews disaster recovery literature from a multi-risk perspective. Identified key challenges encompass the lack of approaches integrating physical reconstruction and socio-economic recovery, the neglect of multi-risk interactions, the limited exploration of recovery from a pre-disaster planning perspective, and the low consideration of disaster recovery as a non-linear process in which communities need change over time.
This paper critically reviews disaster recovery literature from a multi-risk perspective....
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