Damage to residential buildings due to flooding of New Orleans after hurricane Katrina

This article analyzes the direct damage to residential buildings caused by the flooding of New Orleans after hurricane Katrina in the year 2005. A public dataset has been analyzed that contains information on the economic damage levels for approximately 95,000 residential buildings in the flooded area. The relationship between the flood characteristics and economic damage to residential buildings has been investigated. Results of hydrodynamic flood simulations have been used that give insight in water depths and flow velocities in the study area. In general, differences between the three polders in the observed distributions of damage estimates are related to differences in flood conditions. The highest damage percentages and structural damage mainly occurred in areas where higher flow velocities occurred, especially near the breaches in the Lower 9th Ward neighborhood. Further statistical analysis indicated that there is not any strong one-to-one relationship between the damage percentage and the water depth or the depth–velocity product. This suggests that there is considerable uncertainty associated with stage-damage functions, especially when they are applied to individual structures or smaller clusters of buildings. Based on the data, a more general approach has been proposed that could be used to distinguish different damage zones based on water depth and flow velocity for an area that is affected by flooding due to breaching of flood defenses. Further validation of existing damage models with the dataset and further inclusion of information on building type in the analysis of damage levels is recommended.     

Coastal inundation and damage exposure estimation: a case study for Jakarta

Coastal flooding poses serious threats to coastal areas, and the vulnerability of coastal communities and economic sectors to flooding will increase in the coming decades due to environmental and socioeconomic changes. It is increasingly recognised that estimates of the vulnerability of cities are essential for planning adaptation measures. Jakarta is a case in point, since parts of the city are subjected to regular flooding on a near-monthly basis. In order to assess the current and future coastal flood hazard, we set up a GIS-based flood model of northern Jakarta to simulate inundated area and value of exposed assets. Under current conditions, estimated damage exposure to extreme coastal flood events with return periods of 100 and 1,000 years is high (€4.0 and €5.2 billion, respectively). Under the scenario for 2100, damage exposure associated with these events increases by a factor 4–5, with little difference between low/high sea-level rise scenarios. This increase is mainly due to rapid land subsidence and excludes socioeconomic developments. We also develop a detemporalised inundation scenario for assessing impacts associated with any coastal flood scenario. This allows for the identification of critical points above which large increases in damage exposure can be expected and also for the assessment of adaptation options against hypothetical user-defined levels of change, rather than being bound to a discrete set of a priori scenarios. The study highlights the need for urgent attention to the land subsidence problem; a continuation of the current rate would result in catastrophic increases in damage exposure.     

Estimation of structural vulnerability for flooding using geospatial tools in the rural area of Orissa,India

Vulnerability assessment of natural disasters is a crucial input for risk assessment and management. In the light of increasing frequency of disasters, societies must become more disaster resilient. This research tries to contribute to this aim. For risk assessment, insight is needed into the hazard, the elements at risk and their vulnerabilities. This study focused on the estimation of structural vulnerability due to flood for a number of structural elements at risk in the rural area of Orissa, India (Kendrapara), using a community-based approach together with geospatial analysis tools. Sixty-three households were interviewed about the 2003 floods in 11 villages and 166 elements at risk (buildings) were identified. Two main structural types were identified in the study area, and their vulnerability curves were made by plotting the relationships between flood depth and vulnerability for each structural type. The vulnerability ranges from 0 (no damage) to 1 (collapse/total damage). Structural type-1 is characterized by mud wall/floor material and a roof of paddy straw, and structural type-2 is characterized by reinforced cement concrete (RCC) walls/floor and a RCC roof. The results indicate that structural type-1 is most vulnerable for flooding. Besides flood depth, flood duration is also of major importance. Houses from structural type-1 were totally collapsed after 3 days of inundation. Damage of the houses of structural type-2 began after 10 days of inundation.     

Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling

Thanks to modelling advances and the increase in computational resources in recent years, it is now feasible to perform 2-D urban flood simulations at very high spatial resolutions and to conduct flood risk assessments at the scale of single buildings. In this study, we explore the sensitivity of flood loss estimates obtained in such micro-scale analyses to the spatial representation of the buildings in the 2D flood inundation model and to the hazard attribution methods in the flood loss model. The results show that building representation has a limited effect on the exposure values (i.e. the number of elements at risk), but can have a significant impact on the hazard values attributed to the buildings. On the other hand, the two methods for hazard attribution tested in this work result in remarkably different flood loss estimates. The sensitivity of the predicted flood losses to the attribution method is comparable to the one associated with the vulnerability curve. The findings highlight the need for incorporating these sources of uncertainty into micro-scale flood risk prediction methodologies.     

Assessing flood inundation mapping through estimated discharge using GIS and HEC-RAS model

Water discharge is the main parameter in hydraulic modeling for flood hazard assessment. However, the unavailability of data on discharge and observed river morphologies resulted in erroneous calculations and irregularities in flood inundation mapping. The objectives of this study are (i) to investigate uncertainties of hydraulic parameters (width, cross-sectional depth, and channel slope) used in discharge equation and (ii) to examine the influence of estimate discharge on water extent and flood depth with different boundary conditions on interferometric synthetic aperture radar (IFSAR) and modified IFSAR DEMs. Sensitivity analysis was conducted with the Monte Carlo simulation method to generate random data combinations. Bjerklie’s equation was used to calculate discharge based on the three variables, and Manning’s n was substituted into the Hydrologic Engineering Center River Analysis System (HEC-RAS) model. TerraSAR-X was used to distinguish existing flood water bodies and normal water extent. The uncertainty of the combined variables was assessed with the likelihood measures such as F-statistic, mean absolute error, root mean square error, and Nash–Sutcliffe efficiency which compares observed and predicted inundated area as well as flood water depth simulated using the HEC-RAS model.     

Simulation-based decision support system for flood damage assessment under uncertainty using remote sensing and census block information

The level of damage of flood events does not solely depend on exposure to flood waters. Vulnerabilities due to various socio-economic factors such as population at risk, public awareness, and presence of early warning systems, etc. should also be taken into account. Federal and state agencies, watershed management coalitions, insurance companies, need reliable decision support system to evaluate flood risk, to plan and design flood damage assessment and mitigation systems. In current practice, flood damage evaluations are generally carried out based on results obtained from one dimensional (1D) numerical simulations. In some cases, however, 1D simulation is not able to accurately capture the dynamics of the flood events. The present study describes a decision support system, which is based on 2D flood simulation results obtained with CCHE2D-FLOOD. The 2D computational results are complemented with information from various resources, such as census block layer, detailed survey data, and remote sensing images, to estimate loss of life and direct damages (meso or micro scale) to property under uncertainty. Flood damage calculations consider damages to residential, commercial, and industrial buildings in urban areas, and damages to crops in rural areas. The decision support system takes advantage of fast raster layer operations in a GIS platform to generate flood hazard maps based on various user-defined criteria. Monte Carlo method based on an event tree analysis is introduced to account for uncertainties in various parameters. A case study illustrates the uses of the proposed decision support system. The results show that the proposed decision support system allows stake holders to have a better appreciation of the consequences of the flood. It can also be used for planning, design, and evaluation of future flood mitigation measures.     

Assessment of flood hazard,vulnerability and risk of mid-eastern Dhaka using DEM and 1D hydrodynamic model

Floods are regular feature in rapidly urbanizing Dhaka, the capital city of Bangladesh. It is observed that about 60% of the eastern Dhaka regularly goes under water every year in monsoon due to lack of flood protection. Experience gathered from past devastating floods shows that, besides structural approach, non-structural approach such as flood hazard map and risk map is effective tools for reducing flood damages. In this paper, assessment of flood hazard by developing a flood hazard map for mid-eastern Dhaka (37.16 km²) was carried out by 1D hydrodynamic simulation on the basis of digital elevation model (DEM) data from Shuttle Radar Topography Mission and the hydrologic field-observed data for 32 years (1972–2004). As the topography of the area has been considerably changed due to rapid land-filling by land developers which was observed in recent satellite image (DigitalGlobe image; Date of imagery: 7th March 2007), the acquired DEM data were modified to represent the current topography. The inundation simulation was conducted using hydrodynamic program HEC-RAS for flood of 100-year return period. The simulation has revealed that the maximum depth is 7.55 m at the southeastern part of that area and affected area is more than 50%. A flood hazard map was prepared according to the simulation result using the software ArcGIS. Finally, to assess the flood risk of that area, a risk map was prepared where risk was defined as the product of hazard (i.e., depth of inundation) and vulnerability (i.e., the exposure of people or assets to flood). These two maps should be helpful in raising awareness of inhabitants and in assigning priority for land development and for emergency preparedness including aid and relief operations in high-risk areas in the future.     

Geomorphological zoning for flood inundation using satellite data

The authors investigated geomorphological features on the central plain of Thailand utilizing satellite remote sensing data and made geomorphological land classification map showing flood-stricken area. Land classification maps showing flood-striken area tell us former flood inundation area, such as inundation depth, inundation width, flood flow course and flood direction, as well as estimating of the features of flooding. Thus map is useful for planning of flood control works.We classified land form units in the central plain of Thailand as following; delta, tidal flat, lagoon, mud spit, back marsh, natural levee, fan and former river course and so on. After that, the principal component analysis is applied to Landsat TM data and gives good results for photo interpretation of land form units and we transfer geomorphological land classification map to make zoning map of flood risk for the purpose of evaluating the flood damages.     

Driving forces of the villages hollowing based on geographically weighted regression model: a case study of Longde County,the Ningxia Hui Autonomous Region,China

Flooding is a serious problem in Jakarta, and detailed estimation of flood damage is necessary to design optimal flood management strategies. This study aims to estimate flood damage in a densely populated area in Jakarta by means of a survey, to develop the relationship between flood characteristics and flood damage, and to compare the damage estimates from the survey with the damage estimates obtained by a flood damage model for Jakarta, i.e. the damage scanner model. We collected data on economic losses of the January 2013 flood in a survey of flood-affected households and business units in Pesanggrahan River. The actual flood damage in the survey area is US$ 0.5 million for the residential sector and US$ 0.7 million for the business sector. The flood damage for a similar event in the same area based on the damage scanner model is estimated to be US$ 1.3 million for the residential sector and US$ 9.2 million for the business sector. The flood damage estimates obtained by the survey approach are lower compared to the damage scanner approach due to different ways in obtaining flood damage data and in defining the maximum flood damage per object, the different spatial levels of analysis, and uncertainties in constructing the flood damage curves that were applied in the damage scanner model.     

Probabilistic flood risk analysis considering morphological dynamics and dike failure

A comprehensive flood risk assessment should aim not only at quantifying uncertainties but also the variability of risk over time. In this study, an efficient modelling framework was proposed to perform probabilistic hazard and risk analysis in dike-protected river systems accounting for morphological variability and uncertainty. The modelling framework combined the use of: (1) continuous synthetic discharge forcing, (2) a stochastic dike breach model dynamically coupled to a stochastic unsteady one-dimensional hydraulic model (MIKE1D) describing river flows, (3) a catalogue of pre-run probabilistic inundation maps (MIKE SHE) and (4) a damage and loss model (CAPRA). The methodology was applied using continuous simulations to a 45-km reach of the Upper Koshi River, Nepal, to investigate the changes in breach and flood hazards and subsequent risks after 2 and 5 years of probable river bed aggradation. The study results indicated an increase in annual average loss of 4% per year driven by changes in loss distribution in the most frequent loss return periods (20–500 years). The use of continuous simulations and dike breach model also provided a more robust estimation of risk metrics as compared to traditional binary treatment of flood defence and/or the direct association of flow with loss return periods. The results were helpful to illustrate the potential impacts of dynamic river morphology, dike failure and continuous simulation and their significance when devising flood risk study methodologies.     

Application of fragility curves to estimate building damage and economic loss at a community scale: a case study of Seaside,Oregon

Community-scale estimates of building damage and economic loss are modeled for Seaside, Oregon, for Cascadia subduction zone events ranging from 8.7 to 9.3 M_W with corresponding slip distances of 3–25 m considering only the effects of the tsunami. Numerical simulations are obtained from the National Oceanic and Atmospheric Administration’s method of splitting tsunami model which includes a source model, subsidence, and calculations of the propagation and inundation flow characteristics. The damage estimates are based on fragility curves from the literature which relate flow depth with probability of damage for two different structural materials of buildings. Calculations are performed at the parcel level for the inundation hazard without including damage caused by the earthquake itself. Calculations show that the severity of building damage in Seaside is sensitive to the magnitude of the event or degree of slip because the majority of the city is located on low-lying coastal land within the estimated inundation zone. For the events modeled, the percentage of building within the inundation zone ranges from 9 to 88 %, with average direct economic losses ranging from $2 million to $1.2 billion.     

Fuzzy algorithm for estimating average breach widths of embankment dams

Dam breach width significantly influences peak breach outflow, inundation levels, and flood arrival time, but uncertainties inherent in the prediction of its value for embankment dams make its accurate estimation a challenging task in dam risk assessments. The key focus of this paper is to provide a fuzzy logic (FL) model for estimating the average breach width of embankment dams as an alternative to regression equations (RE). The FL approach is capable of handling nonlinear behavior, imprecision in discrete measurements, and parameter uncertainty. Historical data from 69 embankment dam failures are used in the development and testing of the FL model. Application of the FL model is also presented for estimating average breach widths of two case studies that have adequately documented data. The accuracy of the FL rule-based model is investigated using uncertainty analysis: the mean prediction error between the FL estimates and the observed average breach widths is very small (=0.03) and comparable to that achieved using the best available RE. Moreover, the FL uncertainty band is found to be approximately ±0.51 order of magnitude smaller than the ±0.56 order of magnitude achieved with the best available RE. The simulation results indicate the potential of the FL model to be used as a predictive tool for estimating the average breach width of embankment dams.     

Waterlogging and flood hazards vulnerability and risk assessment in Indo Gangetic plain

The recurrent flooding during monsoon and subsequent waterlogging in the northern Bihar plains and the magnitude of losses due to these hazards indicate the continuing vulnerability of the region to flood and waterlogging. Management of floods and waterlogging hazards in highly flood-prone regions of India, including Bihar state has been largely response oriented with little or no attention to mitigation and preparedness. This paper presents a method for spatial, Geographic Information Systems-based assessment of flood and waterlogging vulnerability and risk in northern Bihar plains. Multitemporal satellite data was used to evaluate the area statistics and dynamics of waterlogging over the period from 1975 to 2008. The flood proneness is evaluated at district level with reference to flood inundation during a period from 1998 to 2008. Census data were used to examine the socio-economic characteristics of the region through computation of population density, cultivators, agricultural labourers, sex ratio, children in age group 0–6 years and literates. The geohazard map derived by combining area prone to waterlogging and flood inundation was multiplied with socio-economic vulnerability map to derive the flood-waterlogging risk map of the region. The result shows that flood and water-logging pose highest risk to the central districts in the northern Bihar plains with 50.95% of the total area under high and very high risk.     

Flood damage assessment of an urban area in Chennai, India, part I: methodology

Floods are random phenomena that not only cause damage to the lives, natural resources and the environment, but also affect the health of people. The severity of flooding tends to increase with urbanization. Socio-economic impacts of floods depend on the area, duration and depth of inundation, population density, housing typology, construction materials of dwellings, etc. This article examines the different available methods to trace the flood damage and illustrates the methodology to explore the economic loss through social investigation in Velachery, a part of urban Chennai in India. This paper is Part I of a two-part series in which the objectives and methodology are discussed. Based on the objectives and methodology developed for the study, a comprehensive flood management strategy can be proposed for the efficient management of future flood disasters. The results of the study are discussed in Part II.     

Large-scale natural disaster risk scenario analysis: a case study of Wenzhou City, China

Based on the analysis and calculation of the hazard intensity of typhoon rainstorms and floods as well as the vulnerability of flood receptors and the possibility of great losses, risk scenarios are proposed and presented in Wenzhou City, Zhejiang Province, China, using the Pearson-III model and ArcGIS spatial analyst tools. Results indicate that the elements of risk scenarios include time–space scenarios, disaster scenarios, and man-made scenarios. Ten-year and 100-year typhoon rainstorms and flood hazard areas are mainly concentrated in the coastal areas of Wenzhou City. The average rainfall across a 100-year frequency is 450 mm. The extreme water depth of a 100-year flood is 600 mm. High-vulnerability areas are located in Yueqing, Pingyang, Cangnan, and Wencheng counties. The average loss rate of a 100-year flood is more than 50%. The greatest possible loss of floods shows an obvious concentration-diffusion situation. There is an area of about 20–25% flood loss of 6–24 million Yuan RMB/km² in the Lucheng, Longwan and Ouhai districts. The average loss of a 100-year flood is 12 million Yuan RMB/km², and extreme loss reaches 49.33 million Yuan RMB/km². The classification of risk scenario may be used for the choice of risk response priorities. For the next 50 years, the 10-year typhoon rainstorm-flood disaster is the biggest risk scenario faced by most regions of Wenzhou City. For the Yueqing, Ruian, and Ouhai districts, it is best to cope with a 100-year disaster risk scenario and the accompanying losses.     

Method of Data Reduction and Uncertainty Estimation for Platinum-Group Element Data Using Inductively Coupled Plasma-Mass Spectrometry

A data reduction method is described for determining platinum-group element (PGE) abundances by inductively coupled plasma-mass spectrometry (ICP-MS) using external calibration or the method of standard addition. Gravimetric measurement of volumes, the analysis of reference materials and the use of procedural blanks were all used to minimise systematic errors. Internal standards were used to correct for instrument drift. A linear least squares regression model was used to calculate concentrations from drift-corrected counts per second (cps). Furthermore, mathematical manipulations also contribute to the uncertainty estimates of a procedure. Typical uncertainty estimate calculations for ICP-MS data manipulations involve: (1) Carrying standard deviations from the raw cps through the data reduction or (2) calculating a standard deviation from multiple final concentration calculations. It is demonstrated that method 2 may underestimate the uncertainty estimate of the calculated data. Methods 1 and 2 do not typically include an uncertainty estimate component from a regression model. As such models contribute to the uncertainty estimates affecting the calculated data, an uncertainty estimate component from the regression must be included in any final error calculations. Confidence intervals are used to account for uncertainty estimates from the regression model. These confidence intervals are simpler to calculate than uncertainty estimates from method 1, for example. The data reduction and uncertainty estimation method described here addresses problems of reporting PGE data from an article in the literature and addresses both precision and accuracy. The method can be applied to any analytical technique where drift corrections or regression models are used.     

Assessing flood risk associated with waste disposals: methodology,application and uncertainties

Waste disposal sites are mostly located in lowland areas close to residential areas inducing a long-term risk of potential environmental contamination due to flooding. During recent flood events, these areas were reportedly exposed to inundations. This paper aims to develop a qualitative approach to assess flood risk associated with flood-prone waste disposals at the basis of Austrian case studies. Risk is investigated as a function of the probability of an event and the consequences of that event. The presented assessment approach is characterized as qualitative as consequences are expressed in risk categories but not in expected (monetary) losses. The probability of inundation, the hydrodynamic impacts on considered waste disposal sites and the expected consequences to the environment (potential emissions of hazardous substances) were linked. Derived risk categories from “minor risk” to “serious risk” were used to express flood risk to environmental goods like groundwater bodies, nature reserves and recreation areas. A screening of 1,064 waste disposals yielded roughly 30% of sites located within or close to flood risk zones. Three representative case study areas were selected and investigated in detail by applying 2D hydrodynamic models to calculate flow depths and shear stress and by developing emission scenarios. The hydrodynamic modelling covered three hydrologic scenarios with statistical recurrence intervals of 30, 100 and 300 years. Derived leaching scenarios ranged from minor emissions up to total erosion of the waste disposal site. Based on four parameters representing flood characteristics, the susceptibility to erosion (flow velocity and shear stress) and the estimated leaching behaviour, a flood risk evaluation matrix (FREM) was elaborated. The study outlines that in case of flooding the hazardous emissions could lead to partly tremendous impacts on environmental goods. Identified uncertainties associated with considered processes were considerably high. However, the developed qualitative approach provides a decision support aid to identify waste disposals with imminent risk for humans and the environment.     

Flash flood risk estimation along the St. Katherine road,southern Sinai,Egypt using GIS based morphometry and satellite imagery

Flash floods are considered to be one of the worst weather-related natural disasters. They are dangerous because they are sudden and are highly unpredictable following brief spells of heavy rain. Several qualitative methods exist in the literature for the estimations of the risk level of flash flood hazard within a watershed. This paper presents the utilization of remote sensing data such as enhanced Thematic Mapper Plus (ETM+), Shuttle Radar Topography Mission (SRTM), coupled with geological, geomorphological, and field data in a GIS environment for the estimation of the flash flood risk along the Feiran–Katherine road, southern Sinai, Egypt. This road is a vital corridor for the tourists visiting here for religious purposes (St. Katherine monastery) and is subjected to frequent flash floods, causing heavy damage to man-made features. In this paper, morphometric analyses have been used to estimate the flash flood risk levels of sub-watersheds within the Wadi Feiran basin. First, drainage characteristics are captured by a set of parameters relevant to the flash flood risk. Further, comparison between the effectiveness of the sub-basins has been performed in order to understand the active ones. A detailed geomorphological map for the most hazardous sub-basins is presented. In addition, a map identifying sensitive sections is constructed for the Feiran–Katherine road. Finally, the most influenced factors for both flash flood hazard and critical sensitive zones have been discussed. The results of this study can initiate appropriate measures to mitigate the probable hazards in the area.     

How Accurate are Disaster Loss Data? The Case of U.S. Flood Damage

Policy makers need accurate disaster loss data for decisions about disaster assistance, policy evaluation, and scientific research priorities. But loss estimation is difficult in a disaster situation, and initial loss estimates are seldom evaluated in comparison with actual costs. This paper uses the example of historical flood damage data in the U.S. to evaluate disaster loss data. It evaluates the accuracy of historical flood damage estimates from two federal agencies. The U.S. National Weather Service (NWS) has compiled annual flood loss estimates for each state since 1955. Comparison of the NWS data with similar estimates from five state emergency management agencies reveals substantial disagreement between estimates from different sources. The Federal Emergency Management Agency (FEMA) began in the 1990s to systematically collect damage estimates and cost data associated with its disaster assistance programs. Comparison of early damage estimates with actual expenditures in a California flood disaster reveals large errors in some estimates for individual counties, but no statistically significant tendency to underestimate or overestimate. Positive and negative errors tend to average out and the total damage estimate for the state approximates the final expenditures. Both comparisons indicate that damage estimates for small events or local jurisdictions often are extremely inaccurate. On the other hand, estimates aggregated over large areas or long time periods appear to be reasonably reliable; that is, this study finds that independent estimates for events with losses greater than $500 million disagree by less than 40. The paper suggests ways of interpreting and using such loss estimates to reduce the likelihood of misinterpretation.The National Center for Atmospheric Research is sponsored by the National Science Foundation.