scholarly journals iCRESTRIGRS: A coupled modeling system for cascading flood-landslide disaster forecasting

2016 ◽  
Author(s):  
Ke Zhang ◽  
Xianwu Xue ◽  
Yang Hong ◽  
Jonathan J. Gourley ◽  
Ning Lu ◽  
...  
Keyword(s):  
Slope Stability ◽  
Early Warning ◽  
Early Warning System ◽  
Flash Flood ◽  
Significant Risk ◽  
Warning System ◽  
Prototype System ◽  
Coupled Modeling ◽  
Hazard Management ◽  
Landslide Disaster

Abstract. Severe storm-triggered floods and landslides are two major natural hazards in the U.S., causing property losses of $6 billion and approximately 110–160 fatalities per year nationwide. Moreover, floods and landslides often occur in a cascading manner, posing significant risk and leading to losses that are significantly greater than the sum of the losses from the individual hazards. It is pertinent to couple hydrological and geotechnical modelling processes toward an integrated flood-landslide cascading disaster early warning system for improved disaster preparedness and hazard management. In this study, we developed the iCRESTRIGRS model, a coupled flash flood and landslide disaster early warning system, by integrating the Coupled Routing and Excess STorage (CREST) model with the physically based Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) landslide model. The iCRESTRIGRS system is evaluated in four river basins in western North Carolina that experienced a large number of floods, landslides and debris flows, triggered by heavy rainfall from Hurricane Ivan during September 16–18, 2004. The modelled hourly hydrographs at four USGS gauge stations show generally good agreement with the observations during the entire storm period. In terms of landslide prediction in this case study, the coupled model has a global accuracy of 89.5 % and a true positive rate of 50.6 %. More importantly, it shows an improved predictive capability for landslides relative to the stand-alone TRIGRS model. This study highlights the important physical connection between rainfall, hydrological processes and slope stability, and provides a useful prototype system for operational forecasting of flood and landslide.

scholarly journals iCRESTRIGRS: a coupled modeling system for cascading flood–landslide disaster forecasting

2016 ◽  
Vol 20 (12) ◽  
pp. 5035-5048 ◽  
Author(s):  
Ke Zhang ◽  
Xianwu Xue ◽  
Yang Hong ◽  
Jonathan J. Gourley ◽  
Ning Lu ◽  
...  
Keyword(s):  
Slope Stability ◽  
Disaster Preparedness ◽  
Flash Flood ◽  
Significant Risk ◽  
Coupled Model ◽  
True Positive Rate ◽  
Prototype Model ◽  
Coupled Modeling ◽  
Hazard Management ◽  
Hurricane Ivan

Abstract. Severe storm-triggered floods and landslides are two major natural hazards in the US, causing property losses of USD 6 billion and approximately 110–160 fatalities per year nationwide. Moreover, floods and landslides often occur in a cascading manner, posing significant risk and leading to losses that are significantly greater than the sum of the losses from the hazards when acting separately. It is pertinent to couple hydrological and geotechnical modeling processes to an integrated flood–landslide cascading disaster modeling system for improved disaster preparedness and hazard management. In this study, we developed the iCRESTRIGRS model, a coupled flash flood and landslide initiation modeling system, by integrating the Coupled Routing and Excess STorage (CREST) model with the physically based Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) landslide model. The iCRESTRIGRS system is evaluated in four river basins in western North Carolina that experienced a large number of floods, landslides and debris flows triggered by heavy rainfall from Hurricane Ivan during 16–18 September 2004. The modeled hourly hydrographs at four USGS gauge stations show generally good agreement with the observations during the entire storm period. In terms of landslide prediction in this case study, the coupled model has a global accuracy of 98.9 % and a true positive rate of 56.4 %. More importantly, it shows an improved predictive capability for landslides relative to the stand-alone TRIGRS model. This study highlights the important physical connection between rainfall, hydrological processes and slope stability, and provides a useful prototype model system for operational forecasting of flood and landslide.

scholarly journals A review of advances in China’s flash flood early-warning system

2018 ◽  
Vol 92 (2) ◽  
pp. 619-634 ◽  
Author(s):  
Changjun Liu ◽  
Liang Guo ◽  
Lei Ye ◽  
Shunfu Zhang ◽  
Yanzeng Zhao ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Flash Flood ◽  
Warning System

scholarly journals RISIKO KAWASAN LONGSOR DALAM UPAYA MITIGASI BENCANA MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS

Pondasi ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 67
Author(s):  
Fakhryza Nabila Hamida ◽  
Hasti Widyasamratri
Keyword(s):  
Land Use ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Disaster Risk ◽  
Risk Mapping ◽  
Disaster Mitigation ◽  
Accurate Information ◽  
Loss Of Life ◽  
Landslide Disaster

ABSTRACTIndonesia is an area prone to landslides. The occurrence of this landslide disaster can cause a large impact such as damage and loss both material and non-material. The availability of complete and accurate information in controlling land use in landslide prone areas in the development of an area becomes very important in minimizing the loss of life and losses, both physical, social and economic. This information must be disseminated to the community as an early warning system in disaster mitigation efforts. Identification of the characteristics of landslide prone areas requires a risk mapping of landslide prone areas in efforts to mitigate disasters can be done using Geographic Information Systems (GIS). The results in this study indicate the need to identify disaster risk in detail because basically, an area threatened by disaster does not necessarily mean that each community has the same level of disaster risk. Mapping can be done by clustering or by identifying each building in a vulnerable area based on the level of risk of landslides. Keywords: risk analysis, landslides, disaster mitigation, GIS ABSTRAKIndonesia merupakan wilayah yang rawan terhadap bencana longsor. Terjadinya bencana longsor ini dapat menyebabkan dampak yang besar seperti kerusakan dan kerugian baik materiil maupun non materiil. Tersedianya informasi yang lengkap dan akurat dalam pengendalian pemanfaatan lahan di kawasan rawan bencana longsor dalam pengembangan suatu wilayah menjadi hal yang sangat penting dalam meminimalisir adanya korban jiwa dan kerugian-kerugian baik fisik, sosial maupun ekonomi. Informasi tersebut harus disebarkan kepada masyarakat sebagai sistem peringatan dini dalam upaya mitigasi bencana. Identifikasi karakteristik daerah rawan longsor diperlukan sebuah pemetaan risiko kawasan rawan longsor dalam upaya mitigasi bencana dapat dilakukan menggunakan Sistem Informasi Geografis (SIG). Hasil dalam penelitian ini menunjukkan perlunya identifikasi risiko bencana secara detail karena pada dasarnya, suatu kawasan yang terancam bencana belum tentu tiap masyarakatnya mempunyai tingkat risiko bencana yang sama. Pemetaan dapat dilakukan dengan pengklusteran maupun dengan identifikasi setiap bangunan dalam kawasan rawan berdasarkan tingkat risiko terhadap bencana tanah longsor.Kata Kunci: analisis risiko, tanah longsor, mitigasi bencana, GIS

scholarly journals A Flash Flood Early Warning System for Rural Kenya: A Pilot Study

2018 ◽  
Vol 7 (4.38) ◽  
pp. 1310
Author(s):  
Prof. Dr. Ir Vinesh Thiruchelvam ◽  
Mbau Stella Nyambura
Keyword(s):  
Climate Change ◽  
Early Warning ◽  
Rural Areas ◽  
Early Warning System ◽  
Flash Flood ◽  
Warning System ◽  
Flash Floods ◽  
Short Term ◽  
Moderation Effect ◽  
Early Warnings

The cost of climate change has increased phenomenally in recent years. Therefore, understanding climate change and its impacts, that are likely to get worse and worse into the future, gives us the ability to predict scenarios and plan for them. Flash floods, which are a common result of climate change, follow increased precipitation which then increases risk and associated vulnerability due to the unpredictable rainfall patterns. Developing countries suffer grave consequences in the event that weather disasters strike because they have the least adaptive capacity. At the equator where the hot days are hotter and winds carrying rainfall move faster, Kenya’s Tana River County is noted for its vulnerability towards flash floods. Additionally, this county and others that are classified as rural areas in Kenya do not receive short term early warnings for floods. This county was therefore selected as the study area for its vulnerability. The aim of the study is therefore to propose a flash flood early warning system framework that delivers short term early warnings. Using questionnaires, information about the existing warning system will be collected and analyzed using SPSS. The results will be used to interpret the relationships between variables of the study, with a particular interest in the moderation effect in order to confirm that the existing system can be modified; that is, if the moderation effect is confirmed.       

scholarly journals Advanced Tools for Flood Management: An Early Warning System for Arid and Semiarid Regions

2021 ◽  
pp. 209-223
Author(s):  
Ekkehard Holzbecher ◽  
Ahmed Hadidi ◽  
Nicolette Volp ◽  
Jeroen de Koning ◽  
Humaid Al Badi ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Flash Flood ◽  
Warning System ◽  
Integrated Water Resources Management ◽  
Early Warning Systems ◽  
Flood Management ◽  
Special Focus ◽  
Semiarid Regions ◽  
Smart Technologies

AbstractTechnologies concerning integrated water resources management, in general, and flood management, in particular, have recently undergone rapid developments. New smart technologies have been implemented in every relevant sector and include hydrological sensors, remote sensing, sensor networks, data integration, hydrodynamic simulation and visualization, decision support and early warning systems as well as the dissemination of information to decision-makers and the public. After providing a rough review of current developments, we demonstrate the operation of an advanced system with a special focus on an early warning system. Two case studies are covered in this chapter: one specific urban case located in the city of Parrametta in Australia in an area that shows similar flood characteristics to those found in arid or semiarid regions and one case regarding the countrywide Flash Flood Guidance System in Oman (OmanFFGS).

scholarly journals A Flash Flood Early Warning System for Rural Kenya: A Pilot Study

2018 ◽  
Vol 7 (4.38) ◽  
pp. 810
Author(s):  
Prof. Dr. Ir Vinesh Thiruchelvam ◽  
Mbau Stella Nyambura
Keyword(s):  
Climate Change ◽  
Early Warning ◽  
Rural Areas ◽  
Early Warning System ◽  
Flash Flood ◽  
Warning System ◽  
Flash Floods ◽  
Short Term ◽  
Moderation Effect ◽  
Early Warnings

The cost of climate change has increased phenomenally in recent years. Therefore, understanding climate change and its impacts, that are likely to get worse and worse into the future, gives us the ability to predict scenarios and plan for them. Flash floods, which are a common result of climate change, follow increased precipitation which then increases risk and associated vulnerability due to the unpredictable rainfall patterns. Developing countries suffer grave consequences in the event that weather disasters strike because they have the least adaptive capacity. At the equator where the hot days are hotter and winds carrying rainfall move faster, Kenya’s Tana River County is noted for its vulnerability towards flash floods. Additionally, this county and others that are classified as rural areas in Kenya do not receive short term early warnings for floods. This county was therefore selected as the study area for its vulnerability. The aim of the study is therefore to propose a flash flood early warning system framework that delivers short term early warnings. Using questionnaires, information about the existing warning system will be collected and analyzed using SPSS. The results will be used to interpret the relationships between variables of the study, with a particular interest in the moderation effect in order to confirm that the existing system can be modified; that is, if the moderation effect is confirmed.   

The Open Colliery Slope Mechanics Stability Analysis and Forecasting Methods Reasearching

2012 ◽  
Vol 157-158 ◽  
pp. 743-746
Author(s):  
Hai Bo Jiang ◽  
Chang Sheng Ji ◽  
Ying Qiu Shu ◽  
Jiang Li
Keyword(s):  
Stability Analysis ◽  
Slope Stability ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Slope Stability Analysis ◽  
Forecasting Methods

The slope, out-dump ,inner-dump and work-slope, is the important part in the open colliery. Slope should bring the huge loss without effective forecast during the work. Many methods have been used in the slope stability analysis to escape the slope. Dffective landslide forecast can improve the early warning system of landslides and mitigate the landslide disasters. In this paper, the methods used in the analysis have been list and forecast reasearch should be discuss. The better method could be get from integrate the multi-method.

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