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Editorial

Risk Assessment and Sustainable Disaster Management

1
Department of Informatics Engineering, Universitas Papua, Manokwari 98314, Indonesia
2
Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney, Ultimo, NSW 2007, Australia
3
School of Computing, Faculty of Engineering, University Teknologi Malaysia, Johor Bahru 81310, Malaysia
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 5254; https://doi.org/10.3390/su15065254
Submission received: 8 March 2023 / Accepted: 13 March 2023 / Published: 16 March 2023
(This article belongs to the Special Issue Risk Assessment and Sustainable Disaster Management)

1. Introduction

A risk assessment is a process of identifying potential risks and hazards, evaluating the likelihood and impact of these risks, and developing strategies to manage these risks across all disaster management (DM) phases: prevention, preparedness, response, and recovery (PPRR) [1]. In the context of DM, risk assessments involve evaluating the potential risks and hazards that are associated with a particular disaster scenario, both man-made and natural, such as the likelihood and impact of an earthquake, hurricane, flood, or nuclear disaster [2]. By considering these risks, DM authorities can develop proactive strategies to mitigate the impact of disasters and improve their ability to prepare, respond to, and recover from imminent emergencies, as well as during and in the aftermath of the event [3]. All these activities aim to ensure an effective and sustained DM across the phases. This is essentially called developing resilience [4], which refers to the capacity to either (1) recover quickly from unexpected stress or (2) adjust one’s behaviour in response to changing circumstances. The degree to which affected communities possess the required resources and the capacity to handle those resources effectively during emergency circumstances is the primary factor that determines their level of resilience [5].
However, orchestrating all the necessary resources and activities for effective and timely DM is extremely challenging. While all stakeholders are often required to comprehend the status of an ongoing situation, they are also demanded to have a broad consensus of what is needed and should be conducted to achieve the main goal in each DM activity [6]. In other words, while assessing all risks to ensure that effective and sustained DM is important, it is also crucial to provide empirical knowledge throughout the process concomitant with know-what, know-how, know-where, know-who, know-when, and know-why in all DM activities [7]. The provided knowledge needs to be manifested across all DM phases: prevention, preparedness, response, and recovery (PPRR).
In this editorial piece, we examine these surrounding issues in light of recent events. Of all the submitted papers, only fourteen full-length and outstanding articles were accepted and included in this Special Issue (SI). In the following sections, we also provide an overview of these papers and a synopsis of their contributions.

2. Reviewing of the Content

2.1. Urgency of knowledge in Disaster Management

It is impossible to overstate how important knowledge is in the field of DM. Disasters can strike suddenly and profoundly impact individuals and communities, causing widespread destruction, displacement, and loss of life. In order to respond effectively to disasters and minimise harm, DM stakeholders must have access to accurate and up-to-date knowledge about the risks and hazards associated with a particular disaster scenario [8]. This knowledge must be structured in a way that allows for rapid and effective decision-making and must be accessible at all stages of the DM cycle, from prevention, preparedness, and response to recovery. This is aimed at pursuing the overarching goal of resiliency. The availability and accessibility of knowledge in disaster management are therefore critical for improving the effectiveness of disaster response and recovery efforts and reducing the harm caused by disasters [9].
The first four papers by Bronfman et al., Chasanah & Sakakibara, Ilabaca et al., and Oktari et al. in this Special Issue deal with this issue (Contributions 1–4). They emphasise the concerns of the urgency of knowledge across all four phases of DM regardless of the disaster types. The paper by Oktari et al. (Contribution 4), for instance, examines the impact of severe climate-related disasters on vulnerable populations in Indonesia and the need for adaptive measures to protect their health. The authors identify action areas for health emergency and disaster risk management in policy documents in Indonesia and potential gaps that require further study. The study proposes recommendations to support mobilising and accelerating health adaptation actions towards climate-related disasters in the country. In a similar vein, while the paper by Chasanah and Sakakibara (Contribution 2) emphasises equipping the stakeholders with social capital knowledge in volcano eruption disasters, the papers by Bronfman et al. and Ilabaca et al. (Contributions 1 and 3), respectively, argue that providing the best practice knowledge for managing humanitarian aid distribution for the earthquake and Tsunami disasters, and casualties in the case of mass-injury disasters for the earthquake disaster, respectively, are also crucial. Both studies approach simulation as the technique that can generate such knowledge with Chile as the context in both cases. They legitimise the urgency of knowledge for an effective DM.

2.2. Disaster Management Knowledge Assessment

The knowledge that is ready to use is crucial to ensure sustainable DM. However, validating DM knowledge out of context is challenging. DM knowledge needs to embody empirical elements for various points on the DM timeline, including the goals to be achieved, roles to be played, applicable constraints, and the activities to be managed. More importantly, it should be coupled with a mechanism that can effectively identify and induce the knowledge elements to be reused and shared. As such, it is important to ensure that there is always a learning mechanism for the best lesson to be learned in case of a similar disaster across all PPRR phases. Given the devastating impacts in cases of a disaster, these precautionary measures should be rigorously taken into account. These efforts are even stimulated by embracing simulations for both natural (contributions 5 and 6) and man-made disasters (contributions 7 and 8) to thoroughly assess their potential risks and impacts and, therefore, the measures required to mitigate them. All these are aimed at ensuring sustainable DM.
The papers by Daskal et al., Royo et al., and Rahman et al. (Contributions 9–11) in this context assess individuals’ social-emotional behaviours towards pre- and post-disasters. For instance, while Rahman et al. (Contribution 11) discuss university students’ self-rated status, knowledge, attitudes, and practices regarding lightning in Bangladesh, Daskal et al. (Contribution 9) focus on social-emotional preparedness for earthquakes and the need for a robust social-emotional preparedness program (SEPP) to help the population quickly recover and return to full functioning in the face of uncertainty in Israel. Finally, Royo et al. (Contribution 10) emphasise the emotional barriers faced by pubescent girls returning to school after event-driven disasters, such as an earthquake followed by a tsunami in Central Sulawesi Province, Indonesia, with concerns for water, sanitation, and hygiene (WASH) issues. These instances emphasise the need to acquire representative knowledge to lessen the disaster impact. Particularly, they highlight the necessity for customisable knowledge instead of a one-size-fits-all approach, as well as effective measures to build resiliency across all DM cycles.
The paper by Dedring et al. (Contribution 5) develops an empirical model for simulating and evaluating the failure of tailings dams using risk assessment functionalities. The model is then validated against the tailings dam failures (TDF) in Brumadinho, Minas Gerais State, Brazil. Although this approach produced promising results, further investigation and the improvement of the model are needed to address uncertainties and improve its accuracy, particularly the use of the OpenStreetMap-based part for the basis of the risk assessment. The paper by Hu et al. (Contribution 8) explores the use of satellite imagery and advanced techniques such as SBAS-InSAR and PS-InSAR, wavelet period analysis, and grey correlation analysis to assess the risk of geological disasters and the correlation between surface deformation and climate environments in Nanchang City, China. The study successfully shows a large-scale subsidence trend in the central urban area of Nanchang and an uplift trend in the agroecological areas in the southeast. The results of the study have important implications for sustainable urban development and disaster management.
The paper by Chen et al. (Contribution 6) focuses on developing a periodic assessment system for urban safety and security considering multiple hazards based on WebGIS on the Southeast Coast of China. The system was then tested on a typical urban area to demonstrate its effectiveness for conducting periodic assessments and supporting single-hazard and multi-hazard analysis and decision-making. Although the results demonstrate that the system can promote the sustainable construction of a safe and smart city, the assessment data mostly relies on manual input, and there is no real-time automatic update of data available. This hinders the real-time decision-making processes that are crucial to those who are on the ground. The paper by Chandra et al. (Contribution 7) aims to help organisations prepare for cyber disasters. It harnesses Endsley’s situational awareness model and a tabletop exercise to determine risk priority and assess a team’s preparedness for dealing with a cyber disaster. The results once again demonstrate that the availability of DM knowledge to be reused in the first place is the most significant factor that could influence a better decision-making process. Equipping the stakeholders with relevant DM knowledge can help organisations achieve resiliency.

2.3. Efficient DM knowledge Use for Sharing and Reusing

Given the devastating impact caused by disasters, it has been acknowledged that learning from best practices is the most efficient way to pursue DM resilience. In this context, the lessons learned aim to ensure others reuse it for similar DMs. In other words, sharing and reusing knowledge can lead to better decision-making, more effective response strategies, and, ultimately, more sustainable DM.
The paper by Song and Park (Contribution 12) demonstrates how prior knowledge contributed to alleviating agriculture drainage issues in the Daegu Metropolitan City of South Korea. Their study develops a reduction facility to decrease the number of debris entering agricultural drainage and evaluates its performance in capturing debris under different flow rates and types of reduction facilities. In the end, their research allowed knowledge to be reused to reduce the number of debris entering agricultural drainage. This research contributes to the sustainable management of agricultural drainage and helps to mitigate the impact of debris on crop cultivation.
Paper 13 by Ramli et al. (Contribution 13) finally attempts to integrate the efforts of disaster risk reduction by guiding decision-makers to properly evaluate and analyse risks in the pre-disaster cycle of a framework, the disaster risk assessment framework (IDRAF). They validated this framework with a real case study from Malaysia. They showed that this framework could effectively measure disaster risks at the local level or national level by assessing the potential disaster impacts in detail and accurately. Essentially, this endeavour echoes the previous works in DM that contribute to composing complete DM knowledge into a format that could be easily reused and shared for a similar disaster. The most notable one, for instance, can be found here [2] as this study does not only provide DM knowledge elements for pre- or post-ones.
Finally, the paper by Inan et al. (Contribution 14) formalises the urgency of efficient knowledge sharing and reusing in DM activities by showing a COVID-19 case study in Indonesia. The author embraces the disaster management knowledge analysis framework (DMKAF) as a template [6] to develop an Indonesia COVID-19 disaster management plan (DISPLAN) and formally formulate the sharing, reusing, and a better decision-making system for DM activities related to the COVID-19 pandemic in Indonesia.

3. Concluding Remarks

In conclusion, continuous risk assessments are an essential principle for sustainable DM. Only by identifying and analysing potential hazards, vulnerabilities, and exposures can it become possible to develop effective strategies for disaster prevention, preparedness, response, and recovery. Moreover, sustainable DM requires the efficient use of knowledge through sharing and reusing. By incorporating the lessons learned from past disasters, stakeholders can improve DM practices and increase their ability to reduce disaster risks and enhance resilience. Ultimately, the integration of risk assessments and sustainable DM practices could lead to more effective and efficient DM, protecting lives, livelihoods, and the environment. It is, therefore, imperative for policymakers, researchers, practitioners, and communities to prioritise these practices in their disaster risk reduction and management efforts. In addition, we also would like to take this opportunity to extend our gratitude to every anonymous referee for the diligent effort that they have put into reviewing the submissions and offering helpful criticism, as well as the authors for contributing their work to this Special Issue to disseminate the most recent results of their study.

List of Contributions

  • Bronfman, A.; Beneventti G, D.; Alvarez, P.P.; Reid, S.; Paredes-Belmar, G. The Casualty Stabilization–Transportation Problem in a Large-Scale Disaster. Sustainability 2022, 14, 621.
  • Chasanah, F.; Sakakibara, H. Implication of Mutual Assistance Evacuation Model to Reduce the Volcanic Risk for Vulnerable Society: Insight from Mount Merapi, Indonesia. Sustainability 2022, 14, 8110.
  • Ilabaca, A.; Paredes-Belmar, G.; Alvarez, P.P. Optimization of Humanitarian Aid Distribution in Case of an Earthquake and Tsunami in the City of Iquique, Chile. Sustainability 2022, 14, 819.
  • Oktari, R.S.; Dwirahmadi, F.; Gan, C.C.; Darundiyah, K.; Nugroho, P.C.; Wibowo, A.; Chu, C. Indonesia’s Climate-Related Disasters and Health Adaptation Policy in the Build-up to Cop26 and Beyond. Sustainability 2022, 14, 1006.
  • Dedring, T.; Graw, V.; Thygesen, K.; Rienow, A. Validation of an Empirical Model with Risk Assessment Functionalities to Simulate and Evaluate the Tailings Dam Failure in Brumadinho. Sustainability 2022, 14, 6681.
  • Chen, X.; Chen, G.; Yang, Q.; Li, J.; Yuan, Z.; Jiang, S. A Periodic Assessment System for Urban Safety and Security Considering Multiple Hazards Based on Webgis. Sustainability 2021, 13, 13993.
  • Chandra, N.A.; Ratna, A.A.; Ramli, K. Development and Simulation of Cyberdisaster Situation Awareness Models. Sustainability 2022, 14, 1133.
  • Hu, B.; Chen, B.; Na, J.; Yao, J.; Zhang, Z.; Du, X. Urban Surface Deformation Management: Assessing Dangerous Subsidence Areas through Regional Surface Deformation, Natural Factors, and Human Activities. Sustainability 2022, 14, 10487.
  • Daskal, S.; Ben-Eliyahu, A.; Levy, G.; Ben-Haim, Y.; Avny, R. Earthquake Vulnerability Reduction by Building a Robust Social-Emotional Preparedness Program. Sustainability 2022, 14, 5763.
  • Royo, M.G.; Parrott, E.; Pacheco, E.-M.; Ahmed, I.; Meilianda, E.; Kumala, I.; Parikh, P. A Structured Review of Emotional Barriers to Wash Provision for Schoolgirls Post-Disaster. Sustainability 2022, 14, 2471.
  • Rahman, M.M.; Nabila, I.A.; Sakib, M.S.; Silvia, N.J.; Galib, M.A.; Shobuj, I.A.; Abdo, H.G. Status and Individual View toward Lightning among University Students of Bangladesh. Sustainability 2022, 14, 9341.
  • Song, Y.; Park, M. A Study on the Development of Reduction Facilities’ Management Standards for Agricultural Drainage for Disaster Reduction. Sustainability 2021, 13, 9595.
  • Ramli, M.W.A.; Alias, N.E.; Mohd Yusof, H.; Yusop, Z.; Taib, S.M. Development of a Local, Integrated Disaster Risk Assessment Framework for Malaysia. Sustainability 2021, 13, 10792.
  • Inan, D.I.; Beydoun, G.; Othman, S.H.; Pradhan, B.; Opper, S. Developing Reusable COVID-19 Disaster Management Plans Using Agent-Based Analysis. Sustainability 2022, 14, 6981.

Author Contributions

Writing—original draft preparation, D.I.I.; writing—review and editing, G.B. and S.H.O. All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

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MDPI and ACS Style

Inan, D.I.; Beydoun, G.; Othman, S.H. Risk Assessment and Sustainable Disaster Management. Sustainability 2023, 15, 5254. https://doi.org/10.3390/su15065254

AMA Style

Inan DI, Beydoun G, Othman SH. Risk Assessment and Sustainable Disaster Management. Sustainability. 2023; 15(6):5254. https://doi.org/10.3390/su15065254

Chicago/Turabian Style

Inan, Dedi I., Ghassan Beydoun, and Siti Hajar Othman. 2023. "Risk Assessment and Sustainable Disaster Management" Sustainability 15, no. 6: 5254. https://doi.org/10.3390/su15065254

APA Style

Inan, D. I., Beydoun, G., & Othman, S. H. (2023). Risk Assessment and Sustainable Disaster Management. Sustainability, 15(6), 5254. https://doi.org/10.3390/su15065254

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