Case study of debris flow disaster scenario caused by torrential rain on Kiyomizu-dera, Kyoto, Japan - using Hyper KANAKO system

2016 ◽  
Vol 13 (2) ◽  
pp. 193-202 ◽  
Author(s):  
Kana Nakatani ◽  
Satoshi Hayami ◽  
Yoshifumi Satofuka ◽  
Takahisa Mizuyama
Keyword(s):  
Debris Flow ◽  
Torrential Rain ◽  
Disaster Scenario ◽  
Debris Flow Disaster

LEARNING TO ROLL WITH THE ONE-TWO PUNCH OF FIRE AND DEBRIS FLOW: LESSONS LEARNED FROM THE JANUARY 2018 DEBRIS-FLOW DISASTER IN MONTECITO, CA

2018 ◽  
Author(s):  
Jason W. Kean ◽  
◽  
Dennis M. Staley ◽  
Jeremy T. Lancaster ◽  
Francis K. Rengers ◽  
...  
Keyword(s):  
Debris Flow ◽  
Lessons Learned ◽  
The One ◽  
Debris Flow Disaster

Susceptibility Assessments and Validations of Debris-Flow Events in Meizoseismal Areas: Case Study in China’s Longxi River Watershed

2020 ◽  
Vol 21 (1) ◽  
pp. 05019005 ◽  
Author(s):  
Saier Wu ◽  
Jian Chen ◽  
Chong Xu ◽  
Wendy Zhou ◽  
Leihua Yao ◽  
...  
Keyword(s):  
Debris Flow ◽  
River Watershed

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%.

The Debris Flow Disaster Faster-Than-Early Forecast System (DFS) with Multi-Sensors Integrated Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 975-979
Author(s):  
Rong Zhao ◽  
Cai Hong Li ◽  
Yun Jian Tan ◽  
Jun Shi ◽  
Fu Qiang Mu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Debris Flow ◽  
Real Time ◽  
Debris Flows ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Forecast System ◽  
Debris Flow Disaster

This paper presents a Debris Flow Disaster Faster-than-early Forecast System (DFS) with wireless sensor networks. Debris flows carrying saturated solid materials in water flowing downslope often cause severe damage to the lives and properties in their path. Faster-than-early or faster-than-real-time forecasts are imperative to save lives and reduce damage. This paper presents a novel multi-sensor networks for monitoring debris flows. The main idea is to let these sensors drift with the debris flow, to collect flow information as they move along, and to transmit the collected data to base stations in real time. The Raw data are sent to the cloud processing center from the base station. And the processed data and the video of the debris flow are display on the remote PC. The design of the system address many challenging issues, including cost, deployment efforts, and fast reaction.

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