Natural Hazards Research最新文献

In this study, flood susceptibility mapping was carried out for Chemoga watershed upper Abay River basin, Ethiopia. The main objective of this study is to identify the flood susceptibility areas using Frequency ratio and Information Values models. Based on Google Earth imagery and filed survey, about 168 flooding locations were identified and classified randomly into training flood locations datasets 70% (118) and the remaining 30% (50) of flooding locations datasets were used for validation purpose. Identified 12, flood conditioning factors such as slope, elevation, aspect, curvature, TWI, NDVI, distance from road, distance from river, soil texture, lithology, land use and rainfall were integrated with training flood locations datasets to determine the weights of each flood location conditioning factor and factor classes using both frequency ratio and information value models. The flood susceptibility maps were produced by overlay the weights of all the flood conditioning factors using raster calculator of the spatial analyst tool in ArcGIS 10.4. The final flood susceptibility maps were reclassified as very low, low, moderate, high and very high susceptibility classes both FR and IV models. This susceptibility maps were validated using flood location area under the curve (AUC). The results of AUC accuracy models showed that the success rates of the FR and IV models were 82.90% and 82.10%, while the prediction rates were 80.70% and 80.00% respectively. Past flood events are compared with the flood vulnerable database to validate the modeled output in the present study. This type of study will be very useful to the local government for future planning and decision on flood mitigation plans.

It has been more than three decades of disaster risk reduction education in the United Nations; however, no study has been conducted to explore its current intellectual landscape. That being so, the present study aimed to determine the existing research trends and gaps in disaster risk reduction education, including opportunities and challenges. The paper reports bibliometric research on disaster risk reduction education using publications extracted from the Scopus database. With 452 publications so far (as of writing), results revealed that although the trends in the number of publications per year are generally increasing, there is a considerably limited number of scholars, institutions, and countries that are involved in disaster risk reduction education research; not to mention its limited diversity. This may be because disaster risk reduction is an emerging field. Nevertheless, it may be necessary to invest in building the capacity and encouraging more scholars and institutions to conduct research along with various aspects/phases of disaster risk reduction, involving different stakeholders and vulnerable groups of people, using a variety of research designs in needs assessment and evaluation studies, as well as the assessment on the effectiveness of related strategies. The study contributes to the discourse on disaster risk reduction, specifically disaster risk reduction education. It attempted to establish the current disaster risk reduction education research landscape that led to determining existing trends and gaps. Consequently, findings informed the reflection on opportunities and challenges in disaster risk reduction education research.

This study analyzes the visibility characteristics in Beijing from 2015 to 2020 using the 10-min average horizonal visibility hourly data from 20 national meteorological stations (NMSs). We examine the visibility trends on different time and space scales, including year, month, day. Our findings reveal that the visibility of the Beijing area shows a noticeable change trend year by year. Overall, the number of days with high visibility (visibility ≥10 ​km) has increased, and the number of hours with low visibility (visibility < 1 ​km) has decreased. Low visibility in Beijing mainly occurs during winter, whereas high visibility occurs throughout the year. On a daily scale, low visibility mainly occurs around 6 a.m. and 8 p.m. Furthermore, the spatial distribution of high and low visibility in Beijing correlates with the topographic boundary between plains and mountains. We observed that mountainous areas have more days with increased visibility and fewer hours with low visibility, while plain areas have fewer days with high visibility and more hours with high visibility. These findings have implications for understanding the environmental hazards caused by poor visibility in Beijing, such as impaired air quality, increased traffic accidents, and reduced human mobility. By identifying the temporal and spatial patterns of visibility, this study provides valuable information that can be used to improve hazard mitigation strategies and promote public safety.

Prediction of streamflow is a crucial tool in planning and managing water resources and preventing floods. Due to the recent drought in Urmia Lake, predicting streamflow has become necessary for its rehabilitation. Therefore, selecting the best-optimized model for research is of particular importance. In this study, we modeled and predicted the inlet flow of Urmia Lake from 2019 to 2049, using the inlet flow statistics of ten stations from 1989 to 2019. The two employed software packages demonstrated good correlation with values ranging between 0.7 and 0.92. The neural network method outperformed R software by predicting the future with less MSE error. Unlike R software, the neural network considers the future prediction variable in addition to observational streamflow, making it possible to examine the possibility of flood in case of noticeable increase or decrease in the stations and account for uncertainties such as climate change. The Tapik station showed the highest correlation rate of 0.86 in R software, while Bandeurmiye station had the highest correlation of 0.92 in the neural network, which was performed by selected predictor variables under RCP 2.6 scenario. The neural network forecasting graph results indicate an increasing trend of streamflow in Tapik, Babarood, and Mako stations located in the northwest of the basin in the next 30 years. Babarood station is expected to have the highest streamflow increase of about 15 cubic meters per second in 30 years.

A qualitative study on impact of pre-disaster public awareness activities on public readiness was conducted in the North and South Pagai Islands after the 25 October 2010 Mentawai earthquake. Parameters of readiness are public response to tsunami and the number of casualties. The results show that public awareness activities that commenced from 2004 have effectively increased people's awareness of tsunamis as indicated by their knowledge of tsunami signals. Yet apart from failure of the official warning system to alert the public in remote areas, the response of people to the natural tsunami signals has been made on the basis of misperceptions of strong earthquake signals and tsunami lead-time. Tsunami lead-time of the Pagai Islands had been perceived as long as that of Sumatra or Java Islands and strong earthquakes have been perceived as merely strong ground shaking. These misperceptions came from invalid materials of public education and invalid translation of scientific information, and were confirmed by people's experiences in the 12 September 2007 Bengkulu earthquake. Hence, despite mitigation by relocating houses to the high ground that has saved many lives in Malakopa and Asahan, there is no evidence on the positive relation of pre-disaster awareness intervention with the reduction in loss of lives in the study sites. In order to not give invalid information on tsunami awareness in the future, instead of using a generic formula of regional tsunamis, public education on tsunami should use a specific formula based on local characteristics. Moreover, sensing earthquakes that may trigger tsunamis through the duration of ground shaking may be more effective than that of the strength of ground shaking. Because sensing time duration is difficult, particularly for communities that are not used to using modern timers, it is necessary to develop simple means of sensing time duration.