Springer Science and Business Media LLC

Decision and policy makers in disaster management are compelled to look at alternative measures during the COVID-19 pandemic. They require integrated measures to both reduce the spread of COVID-19 and response to disasters. The measures to mitigate damage of disaster amid COVID-19 can become expensive and inefficient compared to single disaster responses, resulting in delays. Hence, a balance is crucial to successfully manage co-occurring disasters, and new holistic approaches are necessary to produce efficient responses during the COVID-19 outbreak.

The Great Sumatra Tsunami on 26 December 2004 generated large amounts of debris and waste throughout the affected coastal region in the Indian Ocean. In Banda Aceh—Indonesia, the tsunami flows were observed carrying a thick muddy sludge that mixed with all kinds of debris from the destroyed buildings, bridges and culverts, vehicles, fallen trees, and other flotsam. This waste and debris was mostly deposited inland, but traveled both onshore and offshore. Numerical dispersal modeling is carried out to simulate the transport of debris and waste produced by the tsunamis during the event. The model solves the Lagrangian form of the transport/dispersion equations using novel particle tracking techniques. Model results show that understanding the pathway and distribution of the suspended materials and flotsam caused by tsunamis is important for a proper hazards mitigation plan and waste management action, and to minimize serious long-term adverse environmental and natural resources consequences.

The main purpose of this paper is to present the damage features of masonry structures and engineering seismology studies after the 19–22 November 2021 Köprüköy earthquakes (Mw 5.1 and Mw 4.7). The masonry structures damaged near the epicenter have been examined. Damages have been detected that such as vertical cracks in the walls of the masonry structures, out-of-plane bending of the walls, splits in the joints of the walls, and separation of the floors from the elements such as walls and roofs. The fact that the structures in the region do not receive an engineering service and that they are constructed without complying with the relevant earthquake regulations are thought to cause such damage. The damage in Topçu village of Köprüköy district in Erzurum is more than in other settlements. Microtremor measurements have been applied in Topçu Village to investigate dynamic soil features. The soil amplification factor and soil predominant period have been obtained ~ 6.8 and ~ 1.3 s for the first measurement and ~ 9.4 and ~ 1.3 s for second location, respectively. Also, Vs30, bedrock depth, vulnerability index, and shear strain parameters have been calculated using some empirical relations. High bedrock depth and low Vs30 values are obtained for both measurements. The vulnerability index and shear strain values also indicate that the vulnerability of the soil is high. In order to remain in the safe zone for structures in a possible future earthquake, it has been suggested that it should comply with the earthquake-soil-structure relationship and should be designed in accordance with the earthquake regulation standard.

Land-use planners have a critical role to play in building vibrant, sustainable and hazard resilient communities in New Zealand. The policy and legal setting for natural hazards planning provides a solid foundation for good practice. But there are many examples of ‘bad practice’ that result in unnecessary risks and, in some cases, exposure to repeat events and potentially devastating impacts. Much, therefore, remains to be done to improve hazards planning policy and practice in New Zealand. This article explores the questions: What role does land-use planning play in managing hazard risks in New Zealand; and what needs to be done to reduce hazard risks and build community resilience? The article starts by describing the milieu within which natural hazards planning takes place. It goes onto outline the stakeholders and institutional and legal setting for natural hazards planning in New Zealand, including barriers to realising the potential of natural hazards planning. This synthesis reveals a number of ‘burning issues’, including the need to: (a) Improve understanding about the nature of hazards; (b) Prioritise risk avoidance (reduction) measures; (c) Provide national guidance for communities exposed to repeat events and address the relocation issue and (d) Mainstream climate change adaptation. Each ‘burning issue’ is discussed, and priority actions are recommended to realise the potential of land-use planning to reduce natural hazard risks and build community resilience in New Zealand. Ultimately, the challenge is to develop a cooperative hazards governance approach that is founded on coordinated policies, laws and institutions, cooperative professional practice and collaborative communities.

Consideration of within-earthquake ground-motion correlation is essential for the estimation of seismic hazards, damage, and loss for spatially distributed systems. In many seismically active regions, the strong motion data of real engineering significance are completely unavailable or very scarce. The absence of necessary data does not allow developing regional empirical correlation models, and the models obtained for other regions should be used with correspondent sensitivity analysis. The level of within-earthquake correlation may vary in broad range; therefore, development of correspondent criteria for selection from available models is important. In this paper, we analyzed the performance of a system of critical elements of electric power network (substations) depending on variations in within-earthquake correlation. The performance is described as probability of different levels of non-functionality, i.e., percentage of area suffering power outage, and probability of expected number of customers without power. We have shown that the proper choice of the within-earthquake correlation model is critical in comprehensive estimations of functionality of substations in electrical power system. Skipping the ground-motion variability and within-earthquake correlation may lead to unreliable results. Relevance of geology-based within-earthquake correlation models has been demonstrated, and a scheme, which allows reducing uncertainty in the choice of realistic correlation, has been proposed.

On the flanks of the dormant Miravalles volcano, systematic fieldwork and radiocarbon dating of buried humus-rich soils (paleosols) and wood fragments, augmented by mineralogical and geochemical analysis, reveal extensive and previously undocumented Holocene activity. Phase 1 consisted of a ~ 6300 BCE (8.3 ka) volcanic debris avalanche and thick lapilli blast and fallout deposit that appear coeval. Hiatus 1 marks 2600 years of inactivity followed by Phase 2 lapilli interbedded with two lahars below a basaltic lava flow that dates to 3400 BCE (5.3 ka). Hiatus 2 lasted 1800 years from 3300 to 1500 BCE (5.3 ka to 3.5 ka), after which a very active Phase 3 ensued from 1600 BCE to 1500 CE (3.5 to 0.5 ka) with ≥ four lapilli eruptions, ≥ 4 lahars, ≥ 6 layers of ash and pumice, and small andesitic lava flows. The most recent evidence for eruption is a 1070 CE lapilli overlain by poorly-sorted gravels that may represent distal lahar sediments. Evidence indicates the occurrence of at least two, if not three, destructive lahars on the west flank of Miravalles in the past 500 years. The floodplain sedimentary record indicates much more activity of Miravalles volcano over the past 3500 years (since ~ 1500 BCE) than previously known, with a minimum of 24 events in that span. Overbank floodplain deposits are likely to contain the most compete record of recent activity in active and dormant volcanoes, and in the absence of dateable vegetation fragments, radiocarbon dating of paleosol A-horizons is very useful, with a precision of ~ 5 to 10% for a given age, e.g., 1200 ybp ± 60 to 120 y.

Landslide susceptibility maps provide crucial information that helps local authorities, public institutions, and land-use planners make the correct decisions when they are managing landslide-prone areas. In recent years, machine-learning techniques have become very popular for producing landslide susceptibility maps. This study aims to compare the performance of these machine learning models with the traditional statistical methods used to produce landslide susceptibility maps. The landslide susceptibility for Ardanuc, Turkey was evaluated using three models: logistic regression (LR), support vector machine (SVM), and random forest (RF). Ten parameters that are effective in landslide occurrence are used in this study. The accuracy and prediction capabilities of the models were assessed using both the receiver operating characteristic (ROC) curve and area under the curve (AUC) methods. According to the AUC method, the success rate of the LR, SVM, and RF models was 83.1%, 93.2%, and 98.3%, respectively. Further, the prediction rates were calculated as 82.9% (LR), 92.8% (SVM), and 97.7% (RF). According to the verification results, RF and SVM models outperformed the traditional LR model in terms of success and prediction rate. The RF model, however, performed better than the SVM model in terms of success and prediction rates. The landslide susceptibility maps produced as a result of this study can guide city planners, local administrators, and public institutions related to disaster management to prevent and reduce landslide hazards.

High Conservation Value Forests or botanical parks are critical forested areas that need to be appropriately managed and protected against fire, as they contain large concentrations of biodiversity-which includes endangered or threatened species–which are very sensitive to fire outbreaks. Thus, early detection and rapid responses are so important in combating and containing fire in these areas. As such, a lot of innovative methods are used for the containment and combating of fire. This paper proposes a stand-alone program called FireLocator created by LabVIEW that can detect in real-time the geolocation and behavior of fires by superposition of detection areas through state-of-the-art multispectral infrared detectors using wireless transmitters and mathematical modeling algorithms at a very early stage with maximum spatial resolution. In this context, four alternative models for the optimum positions of detectors in pilot control area are analyzed with Analytic Hierarchy Process (AHP) method. Experimental results demonstrated that preferred alternative model for FireLocator program has the highest percentage with 38.22% based on the AHP algorithm that validates the model used in this study. Moreover, FireLocator outperformed other fire monitoring systems and provided high spatial resolution (up to 3 m) which assisted in determining fire behavior and the geolocation of the fire in a minimum pilot area of ~ 3598.9 square meters.

Climate change-induced disasters show the highest risk for agriculture and livelihoods in rural areas of developing countries. Due to changing rainfall pattern, the arid and semiarid region of Pakistan faces frequent droughts. Farming communities affected by drought disasters are causing serious threats to livelihood, global food crises, environmental migration, and sustainable development. The existing study was designed to quantify two key components through (1) analysis of agrometeorological data (1981–2017) with exploratory data analysis and Mann–Kendall trend analysis; (2) extensive field survey (200 households). The multivariate probit model has been run to detect determinants of coping and adaptive strategies by farmers. Our results showed that the farmers supposed that temperature and rainfall were highly fluctuating in recent years equally. Farmers adopted different coping and adaptive measures that include crop diversification, input adjustment, water management, asset depletion, income diversification, and migration to sustain their livelihood during stress periods. The agrometeorological data analysis revealed that the agricultural vulnerability to drought risks increased significantly, and the survey results projected that 64.7% of the population is exposed to drought directly or indirectly. Sen’s slope quantification resulted in (0.025 °C) rise in temperature, (− 2.936 mm) decline in rainfall year−1. Modeling future scenarios resulted in an increase in temperature up to 0.7 °C, 1.2 °C, and a decrease in precipitation up to 161.48 mm, 103.5 mm in 2040 and 2060. The study evaluated a huge gap in the provision of drought risk resilience services, crop insurance, and climate-smart training practices to build capacities among farmers to cope with the impacts of extreme weather conditions. Our research might provide the groundwork to upgrade actions to drought prevention and early warning in water scarcity areas.