An integrated flood risk assessment model for property insurance industry in Taiwan

2011 ◽  
Vol 58 (3) ◽  
pp. 1295-1309 ◽  
Author(s):  
Wen-Ko Hsu ◽  
Pei-Chiung Huang ◽  
Ching-Cheng Chang ◽  
Cheng-Wu Chen ◽  
Dung-Moung Hung ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Insurance Industry ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Flood Risk Assessment ◽  
Property Insurance

scholarly journals An Integrated Flood Risk Assessment Model for Cities Located in the Transitional Zone between Taihang Mountains and North China Plain: A Case Study in Shijiazhuang, Hebei, China

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 104 ◽  
Author(s):  
Qiang Liu ◽  
Hongmao Yang ◽  
Min Liu ◽  
Rui Sun ◽  
Junhai Zhang
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
North China Plain ◽  
North China ◽  
Transitional Zone ◽  
Assessment Model ◽  
Analysis Tool ◽  
Risk Assessment Model ◽  
Flood Risk Assessment ◽  
Risk Map

Cities located in the transitional zone between Taihang Mountains and North China plain run high flood risk in recent years, especially urban waterlogging risk. In this paper, we take Shijiazhuang, which is located in this transitional zone, as the study area and proposed a new flood risk assessment model for this specific geographical environment. Flood risk assessment indicator factors are established by using the digital elevation model (DEM), along with land cover, economic, population, and precipitation data. A min-max normalization method is used to normalize the indices. An analytic hierarchy process (AHP) method is used to determine the weight of each normalized index and the geographic information system (GIS) spatial analysis tool is adopted for calculating the risk map of flood disaster in Shijiazhuang. This risk map is consistent with the reports released by Hebei Provincial Water Conservancy Bureau and can provide reference for flood risk management.

Development of Flood Risk Assessment Model

2012 ◽  
Vol 12 (5) ◽  
pp. 75-81 ◽  
Author(s):  
Jin Gul Joo ◽  
Jung Ho Lee ◽  
Moo Jong Park
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Flood Risk Assessment

scholarly journals A Flood Risk Assessment Model for Companies and Criteria for Governmental Decision-Making to Minimize Hazards

2017 ◽  
Vol 9 (11) ◽  
pp. 2005 ◽  
Author(s):  
Jieun Ryu ◽  
Eun Joo Yoon ◽  
Chan Park ◽  
Dong Kun Lee ◽  
Seong Woo Jeon
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Flood Risk ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Flood Risk Assessment

scholarly journals A Case Study of Flood Risk Evaluation Based on Emergy Theory and Cloud Model in Anyang Region, China

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 420
Author(s):  
Zening Wu ◽  
Yuhai Cui ◽  
Yuan Guo
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Control ◽  
Flood Hazard ◽  
Cloud Model ◽  
Flood Disaster ◽  
Assessment System ◽  
Assessment Model ◽  
Flood Risk Assessment ◽  
Emergy Theory

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.

Identification of hotspots of flood risk in High Mountain Asia region based on geomorphology and climate data

2021 ◽  
Author(s):  
Mariam Khanam ◽  
Giulia Sofia ◽  
Efthymios I. Nikolopoulos ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Extreme Rainfall ◽  
Drainage Density ◽  
Assessment Model ◽  
High Mountain ◽  
Flood Risk Assessment ◽  
Climate Data ◽  
Floodplain Delineation ◽  
Flood Prone Areas

<p>High Mountain Asia (HMA) has the most complex terrain with active hydrologic and geomorphologic processes. Climate change has expedited glacial melt and altered monsoon rain intensity. This has increased flood vulnerability across the region. There have been a few initiatives to measure the vulnerability locally. However, to identify hotspots of flood risk across the region, investigation of the entire HMA region is necessary. Unfortunately, in ungauged basins, the use of traditional floodplain mapping techniques is prevented by the lack of the extensive data required. The present work aims to provide a remote sensing-based flood-risk assessment model that maps and quantifies susceptibility in flood-prone areas. We developed a procedure for floodplain delineation based on high-resolution terrain data and a geomorphic classifier, coupled with satellite-derived extreme rainfall quantiles, and records of past flood events. For this work, we used the unique 8-meter Digital Elevation Models (DEMs) for HMA that are available at the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC). The geomorphic classifier is based on the Hydraulic Scaling Function automatically derived from the DEM, which is used to normalize topography according to the ratio between the local elevations along the drainage network and the riverbanks.  We assess the flood risk hot spots for a specific year based on the spatial distribution of flood losses, drainage density, flood-prone areas, and rainfall. This local flood-risk assessment framework, gradually applied across the entire HMA domain, will increase the awareness of flood risk, towards improved measures for flood risk reduction.</p>

Global Flood Model: Revolutionising Flood Catastrophe Modelling

2020 ◽  
Author(s):  
Paul Dunning ◽  
Kirsty Styles ◽  
Daniel Evans ◽  
Stephen Hutchings
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Hazard ◽  
Insurance Industry ◽  
Flood Risk Assessment ◽  
Catastrophe Model ◽  
Geographical Regions ◽  
Flood Model ◽  
Catastrophe Modelling ◽  
Catastrophe Models

<p>Catastrophe models are well established tools, traditionally used by the re/insurance industry to assess the financial risk to insured property (“exposure”) associated with natural perils. Catastrophe modelling is challenging, particularly for flood perils over large geographical scales, for a number of reasons. To adequately capture the fine spatial variability of flood depth, a flood catastrophe model must be of high spatial resolution. To validly compare estimates of risk obtained from catastrophe models for different geographical regions, those models must be built from geographically consistent data. To compare estimates of risk between any given collection of geographical regions globally, global coverage is required.</p><p>Traditional catastrophe models struggle to meet these requirements; compromises are made, often for performance reasons.  In addition, traditional models are typically static datasets, built in a discrete process prior to their use in exposure risk assessment. Scientific assumptions are therefore deeply embedded; there is little scope for the end user to adjust the model based on their own scientific knowledge.</p><p>This research presents a new and better approach to catastrophe modelling that addresses these challenges and, in doing so, has allowed creation of the world’s first global flood catastrophe model.</p><p>JBA’s Global Flood Model is facilitated by a technological breakthrough in the form of JBA’s <strong>FLY</strong> Technology. The innovations encoded in <strong>FLY</strong> have enabled JBA to create a model capable of consistent global probabilistic flood risk assessment, operating at 30m resolution and supported by a catalogue of 15 million distinct flood events (both river and surface water). <strong>FLY </strong>brings a model to life dynamically, from raw flood hazard data, simultaneously addressing the user configurability and performance challenges.</p><p>Global Flood Model and <strong>FLY</strong> Technology will be of interest to those involved in financial, economic or humanitarian risk assessment, particularly in and between countries and regions not covered by flood catastrophe models to date. The detail of how they work will be covered here, and their power in facilitating consistent global flood risk assessment will be demonstrated.</p>

Sign in / Sign up

Export Citation Format

Share Document