scholarly journals ANALYSIS OF DEBRIS FLOW DISASTER DUE TO HEAVY RAIN BY X-BAND MP RADAR DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 125-132 ◽  
Author(s):  
M. Nishio ◽  
M. Mori
Keyword(s):  
Debris Flow ◽  
Meteorological Data ◽  
Mesh Size ◽  
Heavy Rain ◽  
Japan Meteorological Agency ◽  
Disaster Prevention ◽  
X Band ◽  
Accumulated Rainfall ◽  
Debris Flow Disaster ◽  
Hiroshima City

On August 20 of 2014, Hiroshima City (Japan) was struck by local heavy rain from an autumnal rain front. The resultant debris flow disaster claimed 75 victims and destroyed many buildings. From 1:30 am to 4:30 am on August 20, the accumulated rainfall in Hiroshima City exceeded 200 mm. Serious damage occurred in the Asakita and Asaminami wards of Hiroshima City. As a disaster prevention measure, local heavy rain (localized torrential rains) is usually observed by the Automated Meteorological Data Acquisition System (AMeDAS) operated by the Japan Meteorological Agency (JMA) and by the C-band radar operated by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan, with spatial resolutions of 2.5 km and 1 km, respectively. The new X-band MP radar system enables more detailed rainfall observations than the C-band radar. In fact, this radar can observe local rainfall throughout Japan in near-real time over a minimum mesh size of 250 m. A fine-scale accumulated rainfall monitoring system is crucial for disaster prevention, and potential disasters can be alerted by the hazard levels of the accumulated rainfall.

scholarly journals ANALYSIS OF DEBRIS FLOW DISASTER DUE TO HEAVY RAIN BY X-BAND MP RADAR DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 125-132
Author(s):  
M. Nishio ◽  
M. Mori
Keyword(s):  
Debris Flow ◽  
Meteorological Data ◽  
Mesh Size ◽  
Heavy Rain ◽  
Japan Meteorological Agency ◽  
Disaster Prevention ◽  
X Band ◽  
Accumulated Rainfall ◽  
Debris Flow Disaster ◽  
Hiroshima City

On August 20 of 2014, Hiroshima City (Japan) was struck by local heavy rain from an autumnal rain front. The resultant debris flow disaster claimed 75 victims and destroyed many buildings. From 1:30 am to 4:30 am on August 20, the accumulated rainfall in Hiroshima City exceeded 200 mm. Serious damage occurred in the Asakita and Asaminami wards of Hiroshima City. As a disaster prevention measure, local heavy rain (localized torrential rains) is usually observed by the Automated Meteorological Data Acquisition System (AMeDAS) operated by the Japan Meteorological Agency (JMA) and by the C-band radar operated by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan, with spatial resolutions of 2.5 km and 1 km, respectively. The new X-band MP radar system enables more detailed rainfall observations than the C-band radar. In fact, this radar can observe local rainfall throughout Japan in near-real time over a minimum mesh size of 250 m. A fine-scale accumulated rainfall monitoring system is crucial for disaster prevention, and potential disasters can be alerted by the hazard levels of the accumulated rainfall.

Deposition Prediction of Debris Flow Alluvial Fan Based on Experimental Study

2012 ◽  
Vol 518-523 ◽  
pp. 4819-4822
Author(s):  
Jin Feng Liu ◽  
Shun Yang ◽  
Guo Qiang Ou
Keyword(s):  
Experimental Study ◽  
Debris Flow ◽  
Statistical Method ◽  
Laboratory Experiments ◽  
Empirical Models ◽  
Alluvial Fan ◽  
Disaster Prevention ◽  
Average Accuracy ◽  
Hazardous Area ◽  
Debris Flow Disaster

The deposition prediction of debris flow hazardous area is very important for organizing and implementing debris flow disaster prevention and reduction. This paper selected the data base from laboratory experiments and applied the multiple regression statistical method to establish a series of empirical calculation models for delimiting the debris flow hazardous areas on the alluvial fan. The empirical models for predicting the maximum deposition length (Lc), the maximum deposition width (Bmax) and the maximum deposition thichness (Z0) under the condition of different debris flow volumes (V), densities (rm) and slopes of accumulation area (θd) were establised. And the verification results indicated that the established models can predict the debris flow hazards area with the average accuracy of 86%.

scholarly journals Rainfall Information System Based on Weather Radar for Debris Flow Disaster Mitigation

2018 ◽  
Vol 7 (4.44) ◽  
pp. 165 ◽  
Author(s):  
Ratih Indri Hapsari ◽  
Gerard Aponno ◽  
Rosa Andrie Asmara ◽  
Satoru Oishi
Keyword(s):  
Information System ◽  
Debris Flow ◽  
Weather Radar ◽  
Active Volcano ◽  
Radar Data ◽  
Disaster Mitigation ◽  
Web Based ◽  
X Band ◽  
Secondary Hazards ◽  
Debris Flow Disaster

Rainfall-triggered debris flow has caused multiple impacts to the environment. It. is regarded as the most severe secondary hazards of volcanic eruption. However, limited access to the active volcano slope restricts the ground rain measurement as well as the direct delivery of risk information. In this study, an integrated information system is proposed for volcanic-related disaster mitigation under the framework of X-Plore/X-band Polarimetric Radar for Prevention of Water Disaster. In the first part, the acquisition and processing of high-resolution X-band dual polarimetric weather/X-MP radar data in real-time scheme for demonstrating the disaster-prone region are described. The second part presents the design of rainfall resource database and extensive maps coverage of predicted hazard information in GIS web-based platform accessible both using internet and offline. The proposed platform would be useful for communicating the disaster risk prediction based on weather radar in operational setting.  

scholarly journals Naïve Bayes Classifier for Debris Flow Disaster Mitigation in Mount Merapi Volcanic Rivers, Indonesia, Using X-band Polarimetric Radar

2020 ◽  
Vol 11 (6) ◽  
pp. 776-789
Author(s):  
Ratih Indri Hapsari ◽  
Bima Ahida Indaka Sugna ◽  
Dandung Novianto ◽  
Rosa Andrie Asmara ◽  
Satoru Oishi
Keyword(s):  
Debris Flow ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Disaster Mitigation ◽  
Naive Bayes Classifier ◽  
Bayes Classifier ◽  
Naïve Bayes Classifier ◽  
X Band ◽  
System Verification ◽  
Debris Flow Disaster

AbstractDebris flow triggered by rainfall that accompanies a volcanic eruption is a serious secondary impact of a volcanic disaster. The probability of debris flow events can be estimated based on the prior information of rainfall from historical and geomorphological data that are presumed to relate to debris flow occurrence. In this study, a debris flow disaster warning system was developed by applying the Naïve Bayes Classifier (NBC). The spatial likelihood of the hazard is evaluated at a small subbasin scale by including high-resolution rainfall measurements from X-band polarimetric weather radar, a topographic factor, and soil type as predictors. The study was conducted in the Gendol River Basin of Mount Merapi, one of the most active volcanoes in Indonesia. Rainfall and debris flow occurrence data were collected for the upper Gendol River from October 2016 to February 2018 and divided into calibration and validation datasets. The NBC was used to estimate the status of debris flow incidences displayed in the susceptibility map that is based on the posterior probability from the predictors. The system verification was performed by quantitative dichotomous quality indices along with a contingency table. Using the validation datasets, the advantage of the NBC for estimating debris flow occurrence is confirmed. This work contributes to existing knowledge on estimating debris flow susceptibility through the data mining approach. Despite the existence of predictive uncertainty, the presented system could contribute to the improvement of debris flow countermeasures in volcanic regions.

Disaster prevention education through learning about past heavy rainfall and debris flow damage

2020 ◽  
Author(s):  
Banshoya Shogo
Keyword(s):  
High School Students ◽  
Debris Flow ◽  
Heavy Rainfall ◽  
Heavy Rain ◽  
Aerial Photographs ◽  
Disaster Prevention ◽  
School Students ◽  
Prevention Education ◽  
The Past

<p>This study is an introduction to disaster prevention education for high school students, which aims to raise disaster prevention awareness by learning about disasters that occurred in the past. We live in Hiroshima, Japan. There are many fan-shaped regions in this area, and when heavy rain falls due to the rainy season or typhoons, it is easy for debris flow disasters to occur. The most recent damage was caused by a heavy rain in July 2018. On July 7, 2018, 250 to 300 mm of rain fell in one day. As a result, debris flow damage occurred, greatly affecting the students’ life. Debris flow damage is said to occur repeatedly in the same place. Therefore, I think that learning from the past damage will help students learn about future disaster prevention. </p><p>My students have studied the following 1 and 2 since April 2019. And we worked with graduate student and a professor at Hiroshima University.</p><p>1: Case study of debris flow damage caused by a typhoon (Makurazaki-typhoon) that occurred in 1945.</p><p>A huge typhoon occurred in September 1945, causing heavy rainfall and a debris flow disaster. Then our area was very confused. (Because, just after the war, only one month had passed since the atomic bomb was dropped). Therefore, details of the debris flow damage caused by the typhoon are not known.</p><p>So, we analyzed the aerial photographs taken after the disaster and clarified the extent of the damage. We examined the Kirikushi district in Etajima City, Hiroshima Prefecture, Japan as a case area.</p><p> </p><p>2: Case study of debris flow damage through fieldwork.</p><p>We went to the area we studied in 1. We talked with people who were once affected by debris flow damage in 1945.<span>  </span>As a result, we were able to clarify the situation immediately after the occurrence of debris flow.<span>  </span>And we also asked about the debris flow damage in 2018 and compared the two damages.</p>

Risk Assessment of the Debris Flow Gully in Tibet Southeast

2015 ◽  
Vol 724 ◽  
pp. 347-352
Author(s):  
Jiang Xu ◽  
Qiang He ◽  
Pei Qing Wang ◽  
Lu Lu ◽  
Dong Dong Chen
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Disaster Prevention ◽  
Correlation Ratio ◽  
Human Engineering ◽  
The Core ◽  
Core Content ◽  
Debris Flow Disaster

Risk assessment of debris flow is the core content and decision-making basis for debris flow disaster forecasting and the disaster prevention work. It is a comprehensive analysis for the geological, climate, rainfall, historical disaster activities and human engineering activities in some certain areas which may be in danger conditions, so as to determine the occurrence probability of debris flow. In this study, risk assessment model of the debris flow gully in Tibet southeast area is established. According to the correlation ratio of risk assessment indexes and the debris flow occurrence, the assessment indexes can be divided into three levels and defined with some certain values according to the correlation of debris flow occurrence. Finally, the risk assessment of debris flow gully in Tibet southeast area is conducted, and model outputs achieve a good result.

scholarly journals Adaptive Construction of the Virtual Debris Flow Disaster Environments Driven by Multilevel Visualization Task

2019 ◽  
Vol 8 (5) ◽  
pp. 209 ◽  
Author(s):  
Yunhao Zhang ◽  
Jun Zhu ◽  
Weilian Li ◽  
Qing Zhu ◽  
Ya Hu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Emergency Response ◽  
Dynamic Scheduling ◽  
Single Type ◽  
Prototype System ◽  
Disaster Prevention ◽  
On Demand ◽  
Task Requirements ◽  
Debris Flow Disaster

The construction of a virtual debris flow disaster environment is of great significance in debris flow disaster prevention, risk assessment, accurate simulation, and disaster emergency response. However, existing research on virtual disaster environments mainly focus on the specific visualization task requirements of single-type users, and the multilevel visualization task requirements of multitype users are generally not met. In this paper, an adaptive construction method for virtual debris flow disaster environments driven by multilevel visualization task is proposed based on the characteristics of users with different professional knowledge backgrounds and requirements in disaster emergency response scenarios. The on-demand construction of virtual debris flow disaster environments and the corresponding diverse organization and dynamic scheduling technologies are discussed in detail. Finally, the Qipan Gully debris flow disaster is selected for experimental analysis, and a prototype system is developed. The experimental results show that the proposed method can adaptively construct virtual debris flow disaster environments according to the multilevel visualization task requirements of multitype users in debris flow disaster emergency response scenarios. This approach can provide efficient rendering of disaster scenes and appropriate disaster information to multitype users who are involved in debris flow disaster emergency response scenarios.

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