scholarly journals Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China

2019 ◽  
Vol 11 (4) ◽  
pp. 971 ◽  
Author(s):  
Jidong Wu ◽  
Mengqi Ye ◽  
Xu Wang ◽  
Elco Koks
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Population Density ◽  
Flood Risk ◽  
Statistical Data ◽  
Risk Assessments ◽  
Flood Hazards ◽  
Grid Data ◽  
Flood Exposure ◽  
Asset Value

Exposure is an integral part of any natural disaster risk assessment, and damage to buildings is one of the most important consequence of flood disasters. As such, estimates of the building stock and the values at risk can assist in flood risk management, including determining the damage extent and severity. Unfortunately, little information about building asset value, and especially its spatial distributions, is readily available in most countries. This is certainly true in China, given that the statistical data on building floor area (BFA) is collected by administrative entities (i.e. census level). To bridge the gap between census-level BFA data and geo-coded building asset value data, this article introduces a method for building asset value mapping, using Shanghai as an example. This method consists of a census-level BFA disaggregation (downscaling) by means of a building footprint map extracted from high-resolution remote sensing data, combined with LandScan population density grid data and a financial appraisal of building asset values. Validation with statistical data and field survey data confirms that the method can produce good results, but largely constrained by the resolution of the population density grid used. However, compared with other models with no disaggregation in flood exposure assessment that involves Shanghai, the building asset value mapping method used in this study has a comparative advantage, and it will provide a quick way to produce a building asset value map for regional flood risk assessments. We argue that a sound flood risk assessment should be based on a high-resolution—individual building-based—building asset value map because of the high spatial heterogeneity of flood hazards.

scholarly journals Building Asset Value Mapping in Support of Flood Risk Assessment: A Case Study of Shanghai, China

2017 ◽  
Author(s):  
Jidong Wu ◽  
Xu Wang ◽  
Elco Koks
Keyword(s):  
Risk Assessment ◽  
Natural Disaster ◽  
Flood Risk ◽  
Statistical Data ◽  
Disaster Risk ◽  
Flood Risk Assessment ◽  
Building Stock ◽  
Floor Area ◽  
Asset Value ◽  
Natural Disaster Risk

Abstract. Exposure is an integral part of any natural disaster risk assessment. As one of the consequences of natural disasters, damage to buildings is one of the most important concerns. As such, estimates of the building stock and the values at risk can assist natural disaster risk management, including determining the damage extent and severity. Unfortunately, only little information about building asset value is readily available in most countries (especially its spatial distributions) including in China, given that the statistical data on building floor area (BFA) is collected by administrative unities in China. In order to bridge the gap between aggregated census statistical buildings floor-area data to geo-coded building asset value data, this article introduces a methodology for a city-scale building asset value mapping using Shanghai as an example. It consists of a census BFA disaggregation (downscaling) by means of a building footprint map extracted from high-resolution remote sensing data and LandScan population density data, and a financial appraisal of building asset values. A validation with statistical data confirms the feasibility of the modelled building storey. The example of the use of the developed building asset value map in exposure assessment of a flood scenario of Shanghai demonstrated that the dataset offers immense analytical flexibility for flood risk assessment. The method used in this paper is transferable to be applied in other cities of China for building asset value mapping.

scholarly journals Flood Risk Assessment of Communities to Flood Hazards in Central Niger Delta, Nigeria

2021 ◽  
Vol 4 (1) ◽  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Disaster Preparedness ◽  
Niger Delta ◽  
Sampling Technique ◽  
Flood Hazards ◽  
River Channels ◽  
Social Infrastructure ◽  
Entire Study ◽  
Flood Exposure

The study examined the risk assessment of communities in the Central Niger Delta, Nigeria with a view to employing analytical hierarchical ranking process technique. The study considered the landuse, elevation, soil texture and proximity to active river channels as factors determining flood vulnerability (FV) while factors such as accessibility, social infrastructure, water supply, agriculture, commercial activities and disaster preparedness of communities were used for flood exposure (FE) using purposive sampling technique. Both FV and FE were combined together using UNION Module of ArcGIS 10.5 to produce flood risk map of the Central Niger Delta. Descriptive statistics using frequency and percentages were used for the data analysis. Findings revealed that 20.25%, 51.66% and 28.09% of the entire study area were lowly vulnerable, moderately vulnerable and highly vulnerable to flood. Similarly, 0.3%, 45.7% and 54.8% were lowly exposed, moderately exposed and highly exposed to flood. However, 14.3%, 28.3% and 57.4% of the study area had low flood risk, moderate flood risk and high flood risk respectively. The study concluded that majority of the area in the Central Niger Delta is risky to flood. It is recommended among others that channelization and dredging of River Niger Creeks in the study area are important in order for the river to accommodate more volume of water whenever there is excessive rainfall.

scholarly journals A framework for global river flood risk assessments

2013 ◽  
Vol 17 (5) ◽  
pp. 1871-1892 ◽  
Author(s):  
H. C. Winsemius ◽  
L. P. H. Van Beek ◽  
B. Jongman ◽  
P. J. Ward ◽  
A. Bouwman
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Hydrological Model ◽  
Flood Hazard ◽  
Probability Distributions ◽  
Flood Routing ◽  
Risk Assessments ◽  
First Case ◽  
Impact Models ◽  
Damage Estimates

Abstract. There is an increasing need for strategic global assessments of flood risks in current and future conditions. In this paper, we propose a framework for global flood risk assessment for river floods, which can be applied in current conditions, as well as in future conditions due to climate and socio-economic changes. The framework's goal is to establish flood hazard and impact estimates at a high enough resolution to allow for their combination into a risk estimate, which can be used for strategic global flood risk assessments. The framework estimates hazard at a resolution of ~ 1 km2 using global forcing datasets of the current (or in scenario mode, future) climate, a global hydrological model, a global flood-routing model, and more importantly, an inundation downscaling routine. The second component of the framework combines hazard with flood impact models at the same resolution (e.g. damage, affected GDP, and affected population) to establish indicators for flood risk (e.g. annual expected damage, affected GDP, and affected population). The framework has been applied using the global hydrological model PCR-GLOBWB, which includes an optional global flood routing model DynRout, combined with scenarios from the Integrated Model to Assess the Global Environment (IMAGE). We performed downscaling of the hazard probability distributions to 1 km2 resolution with a new downscaling algorithm, applied on Bangladesh as a first case study application area. We demonstrate the risk assessment approach in Bangladesh based on GDP per capita data, population, and land use maps for 2010 and 2050. Validation of the hazard estimates has been performed using the Dartmouth Flood Observatory database. This was done by comparing a high return period flood with the maximum observed extent, as well as by comparing a time series of a single event with Dartmouth imagery of the event. Validation of modelled damage estimates was performed using observed damage estimates from the EM-DAT database and World Bank sources. We discuss and show sensitivities of the estimated risks with regard to the use of different climate input sets, decisions made in the downscaling algorithm, and different approaches to establish impact models.

scholarly journals Flood Risk Assessment and Quantification at the Community and Property Level in the State of Iowa

2021 ◽  
Author(s):  
Enes Yildirim ◽  
Ibrahim Demir
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Spatial Scales ◽  
The United States ◽  
Flood Risk Assessment ◽  
Study Region ◽  
Study Results ◽  
Flood Maps

Flood risk assessment contributes to identifying at-risk communities and supports mitigation decisions to maximize benefits from the investments. Large-scale risk assessments generate invaluable inputs for prioritizing regions for the distribution of limited resources. High-resolution flood maps and accurate parcel information are critical for flood risk analysis to generate reliable outcomes for planning, preparedness, and decision-making applications. Large-scale damage assessment studies in the United States often utilize the National Structure Inventory (NSI) or HAZUS default dataset, which results in inaccurate risk estimates due to the low geospatial accuracy of these datasets. On the other hand, some studies utilize higher resolution datasets, however they are limited to focus on small scales, for example, a city or a Hydrological United Code (HUC)-12 watershed. In this study, we collected extensive detailed flood maps and parcel datasets for many communities in Iowa to carry out a large-scale flood risk assessment. High-resolution flood maps and the most recent parcel information are collected to ensure the accuracy of risk products. The results indicate that the Eastern Iowa communities are prone to a higher risk of direct flood losses. Our model estimates nearly $10 million in average annualized losses, particularly in large communities in the study region. The study highlights that existing risk products based on FEMA's flood risk output underestimate the flood loss, specifically in highly populated urban communities such as Bettendorf, Cedar Falls, Davenport, Dubuque, and Waterloo. Additionally, we propose a flood risk score methodology for two spatial scales (e.g., HUC-12 watershed, property) to prioritize regions and properties for mitigation purposes. Lastly, the watershed-scale study results are shared through a web-based platform to inform the decision-makers and the public.

scholarly journals Environmental Inequalities in Flood Exposure: A Matter of Scale

2021 ◽  
Vol 3 ◽  
Author(s):  
Clémence Poussard ◽  
Benjamin Dewals ◽  
Pierre Archambeau ◽  
Jacques Teller
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Economic Status ◽  
Flood Hazards ◽  
Socio Economic Status ◽  
Flood Exposure ◽  
Class 1 ◽  
Riverine Floods ◽  
Peripheral Areas ◽  
Hazard Level

Studies on inequalities in exposure to flood risk have explored whether population of a lower socio-economic status are more exposed to flood hazard. While evidence exist for coastal flooding, little is known on inequalities for riverine floods. This paper addresses two issues: (1) is the weakest population, in socio-economic terms, more exposed to flood hazard, considering different levels of exposure to hazard? (2) Is the exposure to flood risk homogeneous across the territory, considering different scales of analysis? An analysis of the exposure of inhabitants of Liège province to flood risk was conducted at different scales (province, districts, and municipalities), considering three levels of exposure to flood hazard (level 1- low hazard, level 3- high hazard), and five socio-economic classes (class 1-poorest, class 5-wealthiest households). Our analysis confirms that weaker populations (classes 2 and 3) are usually more exposed to flood hazards than the wealthiest (classes 4 and 5). Still it should be stressed that the most precarious households (class 1) are less exposed than low to medium-range ones (classes 2 and 3). Further on the relation between socio-economic status and exposure to flood hazard varies along the spatial scale considered. At the district level, it appears that classes 4 and 5 are most exposed to flood risk in some peripheral areas. In municipalities located around the center of the city, differences of exposure to risk are not significant.

scholarly journals Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps?

2021 ◽  
Vol 21 (10) ◽  
pp. 2921-2948
Author(s):  
Sara Lindersson ◽  
Luigia Brandimarte ◽  
Johanna Mård ◽  
Giuliano Di Baldassarre
Keyword(s):  
High Resolution ◽  
Flood Risk ◽  
Flood Hazard ◽  
Global Scale ◽  
Research Centre ◽  
Hazard Maps ◽  
Joint Research ◽  
Flood Exposure ◽  
Population Grid ◽  
Flood Hazard Maps

Abstract. Riverine flood risk studies often require the identification of areas prone to potential flooding. This modelling process can be based on either (hydrologically derived) flood hazard maps or (topography-based) hydrogeomorphic floodplain maps. In this paper, we derive and compare riverine flood exposure from three global products: a hydrogeomorphic floodplain map (GFPLAIN250m, hereinafter GFPLAIN) and two flood hazard maps (Flood Hazard Map of the World by the European Commission's Joint Research Centre, hereinafter JRC, and the flood hazard maps produced for the Global Assessment Report on Disaster Risk Reduction 2015, hereinafter GAR). We find an average spatial agreement between these maps of around 30 % at the river basin level on a global scale. This agreement is highly variable across model combinations and geographic conditions, influenced by climatic humidity, river volume, topography, and coastal proximity. Contrary to expectations, the agreement between the two flood hazard maps is lower compared to their agreement with the hydrogeomorphic floodplain map. We also map riverine flood exposure for 26 countries across the global south by intersecting these maps with three human population maps (Global Human Settlement population grid, hereinafter GHS; High Resolution Settlement Layer, hereinafter HRSL; and WorldPop). The findings of this study indicate that hydrogeomorphic floodplain maps can be a valuable way of producing high-resolution maps of flood-prone zones to support riverine flood risk studies, but caution should be taken in regions that are dry, steep, very flat, or near the coast.

Sign in / Sign up

Export Citation Format

Share Document