Disaster Risk Management and Resilience

Topic Information

Dear Colleagues,

As the global population grows and natural disasters occur more frequently, the risks faced by communities worldwide continue to escalate. To mitigate the devastating impacts of these hazards, efforts have increasingly shifted towards designing, constructing, and retrofitting buildings as well as infrastructure that are not only more robust individually but also better integrated collectively. Emphasizing faster recovery, regional functionality, and the interdependence of systems is critical to achieving resilience at the community level. Achieving this goal is no small task, particularly when it must also align with broader societal priorities such as sustainability and the reduction in environmental and resource footprints. The interplay between these objectives presents both challenges and opportunities for innovation.

The aim of this topic series, “Disaster Risk Management and Resilience”, is to bring together expertise from structural, geotechnical, and hydraulic engineering, along with advanced approaches to sustainable resilience and risk modeling for natural hazards. We invite high-quality, original research articles that present cutting-edge techniques and methods at the intersection of sustainability, resilience, risk analysis, and disaster management. Topics of interest include, but are not limited to, structures and infrastructure subjected to a variety of natural hazards, such as earthquakes, fires, floods, windstorms, hurricanes, and the effects of aging. We welcome both theoretical and applied research of a high technical standard from diverse disciplines. The goal is to foster cross-disciplinary awareness and the application of innovative techniques as well as methods. Submissions may include original research articles as well as review papers that focus on sustainability and demonstrate potential for practical impacts. Topics of interest include, but are not limited to, the following:

• Risk and resilience of buildings and lifeline infrastructure systems.
• Social and economic considerations in the design of resilient systems.
• Retrofit solutions and energy efficiency upgrades.
• Sustainable and resilient buildings and infrastructural networks.
• Functional recovery design and planning for the built environment.
• Uncertainty quantification in the assessment of structures.
• Compound natural hazards towards risk mitigation.
• Artificial intelligence to tackle risk and resilience problems.

We look forward to receiving your contributions.

Dr. Mohammad Amin Hariri-Ardebili
Dr. Sissy Nikolaou
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Buildings buildings	3.1	4.4	2011	14.9 Days	CHF 2600	Submit
Climate climate	3.2	5.7	2013	21.6 Days	CHF 1800	Submit
Fire fire	2.7	3.9	2018	16.5 Days	CHF 2400	Submit
Sustainability sustainability	3.3	7.7	2009	19.3 Days	CHF 2400	Submit
Water water	3.0	6.0	2009	19.1 Days	CHF 2600	Submit
Infrastructures infrastructures	2.9	6.0	2016	15.7 Days	CHF 1800	Submit

Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.

MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:

1. Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
2. Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
3. Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
4. Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
5. Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (3 papers)

Order results

Content type Publication Date

Result details

Normal Extended Compact

Journals

All Buildings Climate Fire Sustainability Water Infrastructures

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

Error

Oops... you haven't selected anything for export.

Ok

clear

21 pages, 4515 KiB  

Open AccessArticle

Deep Learning- and Multi-Point Analysis-Based Systematic Deformation Warning for Arch Dams

by Tao Zhou, Xiubo Niu, Ning Ma, Futing Sun and Shilin Gong

Infrastructures 2025, 10(7), 170; https://doi.org/10.3390/infrastructures10070170 - 3 Jul 2025

Viewed by 239

Abstract

Deformation is a direct manifestation of structural changes that occur during the operation of arch dams, and the development of reliable deformation early warning indicators allows for their timely study. Considering that an arch dam is a systematic overall structure, it is necessary [...] Read more.

Deformation is a direct manifestation of structural changes that occur during the operation of arch dams, and the development of reliable deformation early warning indicators allows for their timely study. Considering that an arch dam is a systematic overall structure, it is necessary to systematically analyze the formulation of deformation early warning indicators and general early warning methods for this dam type. To this end, this study innovatively proposes a systematic early warning method for arch dams based on deep learning and a multi-measurement point analysis strategy. Firstly, the causal model (HST) is utilized to extract the environmental factors as convolutional neural network (CNN) array samples, and the absolute deformation residual sequences of multiple points are obtained by HST-MultiCNN. Secondly, combining this with principal component analysis, a systematic deformation residual index with multiple points is established. Then, the kernel function is used to simulate the distribution of the abovementioned indicators, and is combined with the idea of small probability to formulate the overall warning indicator. Finally, the Re-CNN strategy is used to train the mapping relationship between the multi-objective residuals and the system indicators, and the mapping relationship outlined above is then used to obtain the system indicators corresponding to real-time prediction values, which in turn determine the overall deformation state of arch dams. Analysis shows that the RMSE of the deformation output of the proposed monitoring method uses a value between 0.2284 and 0.2942, with satisfactory accuracy, and the overall deformation warning accuracy reaches 100%, which is significantly better than the comparison method, and effectively solves the primary defect of the traditional single-point analysis—failure to reflect the overall deformation condition. Full article

(This article belongs to the Topic Disaster Risk Management and Resilience)

►▼ Show Figures

Figure 1

22 pages, 5827 KiB  

Open AccessArticle

Multi-Factor Earthquake Disaster Prediction for Urban Buried Water Supply Pipelines Amid Seismic Wave Propagation

by Lifang Qi, Baitao Sun and Nan Wang

Water 2025, 17(13), 1900; https://doi.org/10.3390/w17131900 - 26 Jun 2025

Viewed by 305

Abstract

Urban water supply pipelines play a critical role in ensuring the continuous delivery of water, and their failure during earthquakes can result in significant societal disruptions. This study proposes a seismic damage prediction method for urban buried water supply pipelines affected by seismic [...] Read more.

Urban water supply pipelines play a critical role in ensuring the continuous delivery of water, and their failure during earthquakes can result in significant societal disruptions. This study proposes a seismic damage prediction method for urban buried water supply pipelines affected by seismic wave propagation, grounded in empirical data from past earthquake events. The method integrates key influencing factors, including pipeline material, diameter, joint type, age, and soil corrosivity. To enhance its practical applicability and address the challenge of quantifying soil corrosivity, a simplified classification approach is introduced. The proposed model is validated using observed pipeline damage data from the 2008 Wenchuan earthquake, with predicted results showing relatively good agreement with actual failure patterns, thereby demonstrating the model’s reliability for seismic risk assessment. Furthermore, the model is applied to assess potential earthquake-induced damage to buried pipelines in the city center of Ganzhou, and the corresponding results are presented. The findings support earthquake risk mitigation and the protection of urban infrastructure, while also providing valuable guidance for the replacement of aging pipelines and the enhancement of urban disaster resilience. Full article

(This article belongs to the Topic Disaster Risk Management and Resilience)

►▼ Show Figures

Figure 1

19 pages, 16814 KiB  

Open AccessArticle

Research on Vertical Bearing Characteristics of Single Pile in Complex Interactive Karst Area

by Xinquan Wang, Chen Liu, Haibo Hu, Yongle Tian, Haitao Chen and Jun Hong

Buildings 2025, 15(9), 1530; https://doi.org/10.3390/buildings15091530 - 2 May 2025

Viewed by 502

Abstract

This study investigates the vertical bearing characteristics of single-pile foundations in complex karst areas, focusing on the influence of underlying cavities, eccentric cavities, and beaded cavities. Using both indoor model tests and numerical simulations with ABAQUS/CAE 2020, the load–settlement behavior, pile axial force, [...] Read more.

This study investigates the vertical bearing characteristics of single-pile foundations in complex karst areas, focusing on the influence of underlying cavities, eccentric cavities, and beaded cavities. Using both indoor model tests and numerical simulations with ABAQUS/CAE 2020, the load–settlement behavior, pile axial force, and side friction distribution under these conditions are explored. The results reveal that the presence of eccentric cavities (eccentricity 2.5 d) significantly enhances the ultimate bearing capacity by 53% compared to concentric cavities. In contrast, beaded cavities reduce the bearing capacity by 12% due to increased pile instability and larger settlements. The study also examines the effects of backfilling on the bearing characteristics, finding that backfilling underlying cavities increases the ultimate bearing capacity by 111.8% and prevents shear failure of the cavity roof. Backfilling beaded cavities improves stability by reducing top settlement and increasing the ultimate bearing capacity by 4.5%. The novelty of this research lies in the comprehensive consideration of both eccentric and beaded cavities, which are often overlooked in existing studies. These findings provide valuable insights for the design of pile foundations in karst regions, offering practical guidance on how to mitigate the adverse effects of cavities and optimize foundation stability. Full article

(This article belongs to the Topic Disaster Risk Management and Resilience)

►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less

Select all

Export citation of selected articles as:

Plain Text BibTeX BibTeX (without abstracts) Endnote Endnote (without abstracts) Tab-delimited RIS

 

Error

Oops... you haven't selected anything for export.

Ok

clear

Displaying articles 1-3