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Special Issue "Advances in Hazard, Risk and Disaster Management"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: 6 September 2019.

Special Issue Editor

Guest Editor
Prof. Dr. Jason K. Levy

Disaster Preparedness and Emergency Management, University of Hawaii, Kapolei, HI 96707, USA
Website | E-Mail
Interests: disaster risk governance; sustainable hazard mitigation; emergency management decision making; natural–technologic (na–tech) crises; health-related emergencies; fluvial and marine disasters; global climate change

Special Issue Information

Dear Colleagues,

Geohazards (geologic hazards) are a growing menace to public health. There are a wide variety of geological or hydrological processes that pose a critical threat to health facilities and other health-related critical infrastructure, as well as to human health and the property of citizens. Every year, severe natural events damage critical infrastructure and cause injuries and even deaths. Potentially hazardous geo-processes include volcanic eruptions, earthquakes, landslides, mudflows, sinkholes, snow avalanches, flooding, and tsunamis.

While human activities can exacerbate geologic risks, there are new set of tools in the big data era that that can help to reduce the impact of geohazards. For example, there are machine learning tools, statistical approaches that capitalize on the ubiquity of health data sets, as well as advances in remote sensing, global position systems and GIS. These solutions also provide new opportunities for the analysis and management of geohazards, human health and disaster risks.

Prof. Jason K. Levy
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • earthquakes
  • human health
  • statisics
  • GIS
  • geohazards

Published Papers (6 papers)

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Research

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Open AccessArticle
The Solidification of Lead-Zinc Smelting Slag through Bentonite Supported Alkali-Activated Slag Cementitious Material
Int. J. Environ. Res. Public Health 2019, 16(7), 1121; https://doi.org/10.3390/ijerph16071121
Received: 14 February 2019 / Revised: 21 March 2019 / Accepted: 22 March 2019 / Published: 28 March 2019
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Abstract
The proper disposal of Lead-Zinc Smelting Slag (LZSS) having toxic metals is a great challenge for a sustainable environment. In the present study, this challenge was overcome by its solidification/stabilization through alkali-activated cementitious material i.e., Blast Furnace Slag (BFS). The different parameters (water [...] Read more.
The proper disposal of Lead-Zinc Smelting Slag (LZSS) having toxic metals is a great challenge for a sustainable environment. In the present study, this challenge was overcome by its solidification/stabilization through alkali-activated cementitious material i.e., Blast Furnace Slag (BFS). The different parameters (water glass modulus, liquid-solid ratio and curing temperature) regarding strength development were optimized through single factor and orthogonal experiments. The LZSS was solidified in samples that had the highest compressive strength (after factor optimization) synthesized with (AASB) and without (AAS) bentonite as an adsorbent material. The results indicated that the highest compressive strength (AAS = 92.89MPa and AASB = 94.57MPa) was observed in samples which were prepared by using a water glass modulus of 1.4, liquid-solid ratio of 0.26 and a curing temperature of 25 °C. The leaching concentrations of Pb and Zn in both methods (sulfuric and nitric acid, and TCLP) had not exceeded the toxicity limits up to 70% addition of LZSS due to a higher compressive strength (>60 MPa) of AAS and AASB samples. While, leaching concentrations in AASB samples were lower than AAS. Conclusively, it was found that the solidification effect depends upon the composition of binder material, type of leaching extractant, nature and concentration of heavy metals in waste. The XRD, FTIR and SEM analyses confirmed that the solidification mechanism was carried out by both physical encapsulation and chemical fixation (dissolved into a crystal structure). Additionally, bentonite as an auxiliary additive significantly improved the solidification/stabilization of LZSS in AASB by enhancing the chemical adsorption capacity of heavy metals. Full article
(This article belongs to the Special Issue Advances in Hazard, Risk and Disaster Management)
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Open AccessArticle
Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China
Int. J. Environ. Res. Public Health 2019, 16(3), 368; https://doi.org/10.3390/ijerph16030368
Received: 11 December 2018 / Revised: 25 January 2019 / Accepted: 27 January 2019 / Published: 28 January 2019
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Abstract
The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to [...] Read more.
The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to produce high-quality landslide susceptibility maps for Lishui City in Zhejiang Province, China. Landslide-related factors were extracted from topographic maps, geological maps, and satellite images. Twelve factors were selected as independent variables using correlation coefficient analysis and the neighborhood rough set (NRS) method. In total, 288 soil landslides were mapped using field surveys, historical records, and satellite images. The landslides were randomly divided into two datasets: 70% of all landslides were selected as the original training dataset and 30% were used for validation. Then, SMOTE was employed to generate datasets with sizes ranging from two to thirty times that of the training dataset to establish and compare the four machine learning methods for landslide susceptibility mapping. In addition, we used slope units to subdivide the terrain to determine the landslide susceptibility. Finally, the landslide susceptibility maps were validated using statistical indexes and the area under the curve (AUC). The results indicated that the performances of the four machine learning methods showed different levels of improvement as the sample sizes increased. The RF model exhibited a more substantial improvement (AUC improved by 24.12%) than did the ANN (18.94%), SVM (17.77%), and LR (3.00%) models. Furthermore, the ANN model achieved the highest predictive ability (AUC = 0.98), followed by the RF (AUC = 0.96), SVM (AUC = 0.94), and LR (AUC = 0.79) models. This approach significantly improves the performance of machine learning techniques for landslide susceptibility mapping, thereby providing a better tool for reducing the impacts of landslide disasters. Full article
(This article belongs to the Special Issue Advances in Hazard, Risk and Disaster Management)
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Open AccessArticle
Flood Risk Evaluation in Urban Spaces: The Study Case of Tormes River (Salamanca, Spain)
Int. J. Environ. Res. Public Health 2019, 16(1), 5; https://doi.org/10.3390/ijerph16010005
Received: 10 November 2018 / Revised: 17 December 2018 / Accepted: 18 December 2018 / Published: 20 December 2018
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Abstract
The expansion of cities towards flood zones, and the increasingly frequent episodes of torrential rains arising from global warming, mean that the population is becoming more exposed to floods. Due to this, a correct assessment of flood events is of great help in [...] Read more.
The expansion of cities towards flood zones, and the increasingly frequent episodes of torrential rains arising from global warming, mean that the population is becoming more exposed to floods. Due to this, a correct assessment of flood events is of great help in the development of preventive actions, planning and resource management, or interventions. For this reason, in this work we aim to establish guidelines to assess the hazard, exposure, and vulnerability of the population and its properties to flood events, using Hec-Ras for the simulation of the flood and ArcGis and GeoHecRas to treat geographic information and prepare the cartography. The study was focused on the Tormes River in Salamanca (Spain). We studied three return periods with different probabilities of occurrence and intensity, corresponding to 5, 100, and 500 years. The flow corresponding to each episode was calculated, along with the extension, speed, and depth that would be achieved in each case. Then, the probability of occurrence was delimited, as well as the magnitude, allowing us to obtain different hazard maps. In addition, the areas of greatest hazard to people and property were established for each event. Regarding the exposure, the areas and land use, infrastructure, and buildings that would be flooded in each case were identified, quantifying the extension or length of the affected properties at the different levels of hazard in each case. Additionally, the vulnerability of the different buildings and exposed infrastructure was studied. Finally, the flood risk was estimated by combining these three components. Full article
(This article belongs to the Special Issue Advances in Hazard, Risk and Disaster Management)
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Open AccessArticle
Hands-On Experience of Crowdsourcing for Flood Risks. An Android Mobile Application Tested in Frederikssund, Denmark
Int. J. Environ. Res. Public Health 2018, 15(9), 1926; https://doi.org/10.3390/ijerph15091926
Received: 8 August 2018 / Revised: 31 August 2018 / Accepted: 1 September 2018 / Published: 4 September 2018
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Abstract
There is evidence that the toll of death and destruction caused by natural hazards is rising. This is often ascribed to the impact of climate change that resulted in an increased frequency of extreme meteorological events. As a consequence, it is realistic to [...] Read more.
There is evidence that the toll of death and destruction caused by natural hazards is rising. This is often ascribed to the impact of climate change that resulted in an increased frequency of extreme meteorological events. As a consequence, it is realistic to expect that the casualties and damages caused by floods will increase in the near future. Advanced weather forecast is a fundamental tool to predict the occurrence of floods and structural mitigation measures are crucial for flood protection. However, these strategies should be associate with tools to promote and increase natural-disaster awareness and nonstructural mitigation measures in the exposed population. To bridge this gap, we coupled innovative, ICT-based technologies with crowdsourcing. The idea is to exploit geospatial data gathered by citizens and volunteers with their own devices such as mobile phones to provide authorities with relevant information in case of flood emergencies. This paper describes the design and testing of an Android application named MAppERS (Mobile Applications for Emergency Response and Support), thought to enhance active participation and response of the population in territorial and flood-risk mitigation in Frederikssund, Denmark. The results of the piloting fully validate MAppERS as an effective tool to support the decision-making process during a crisis and to improve the awareness of the community and their disaster resilience. Full article
(This article belongs to the Special Issue Advances in Hazard, Risk and Disaster Management)
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Review

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Open AccessReview
Emergency Logistics in a Large-Scale Disaster Context: Achievements and Challenges
Int. J. Environ. Res. Public Health 2019, 16(5), 779; https://doi.org/10.3390/ijerph16050779
Received: 12 November 2018 / Revised: 2 February 2019 / Accepted: 19 February 2019 / Published: 4 March 2019
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Abstract
There is growing research interest in emergency logistics within the operations research (OR) community. Different from normal business operations, emergency response for large scale disasters is very complex and there are many challenges to deal with. Research on emergency logistics is still in [...] Read more.
There is growing research interest in emergency logistics within the operations research (OR) community. Different from normal business operations, emergency response for large scale disasters is very complex and there are many challenges to deal with. Research on emergency logistics is still in its infancy stage. Understanding the challenges and new research directions is very important. In this paper, we present a literature review of emergency logistics in the context of large-scale disasters. The main contributions of our study include three aspects: First, we identify key characteristics of large-scale disasters and assess their challenges to emergency logistics. Second, we analyze and summarize the current literature on how to deal with these challenges. Finally, we discuss existing gaps in the relevant research and suggest future research directions. Full article
(This article belongs to the Special Issue Advances in Hazard, Risk and Disaster Management)

Other

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Open AccessTechnical Note
Erosion Failure of a Soil Slope by Heavy Rain: Laboratory Investigation and Modified GA Model of Soil Slope Failure
Int. J. Environ. Res. Public Health 2019, 16(6), 1075; https://doi.org/10.3390/ijerph16061075
Received: 15 February 2019 / Revised: 20 March 2019 / Accepted: 22 March 2019 / Published: 26 March 2019
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Abstract
Rainfall has been identified as one of the main causes for slope failures in areas where high annual rainfall is experienced. The slope angle is important for its stability during rainfall. This paper aimed to determine the impact of the angle of soil [...] Read more.
Rainfall has been identified as one of the main causes for slope failures in areas where high annual rainfall is experienced. The slope angle is important for its stability during rainfall. This paper aimed to determine the impact of the angle of soil slope on the migration of wetting front in rainfall. The results proved that under the same rainfall condition, more runoff was generated with the increase of slope angle, which resulted in more serious erosion of the soil and the ascent of wetting front. A modified Green-Ampt (GA) model of wetting front was also proposed considering the seepage in the saturated zone and the slope angle. These findings will provide insights into the rainfall-induced failure of soil slopes in terms of angle. Full article
(This article belongs to the Special Issue Advances in Hazard, Risk and Disaster Management)
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