A methodology for estimating business interruption loss caused by flood disasters: insights from business surveys after Tokai Heavy Rain in Japan

This study proposes a probabilistic methodology for estimating the business interruption loss of industrial sectors as an extension of current methodology. The functional forms and parameters are selected and calibrated based on survey data obtained from businesses located in the inundated area at the time of the 2000 Tokai Heavy Rain in Japan. The Tokai Heavy Rain was a rare event that hit a densely populated and industrialized area. In the estimation of business interruption losses, functional fragility curves and accelerated failure time models are selected to estimate the extent of damage to production capacity and production recovery time. Significant explanatory variables, such as inundation depth, distinct vulnerability, and the resilience characteristics of each sector, as well as the accuracy of fit of the model, are analyzed in the study. The function obtained and the estimated parameters can be utilized as benchmarks in estimating the probabilistic distribution of business interruption losses, especially in the case of urban flood disasters.

     

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.     

Assessing building vulnerability to tsunami using the PTVA-3 model: A case study of Chabahar Bay,Iran

Chabahar Bay, in southeastern Iran, lies at the north of the Gulf of Oman and close to the Makran Subduction Zone, which makes it a region that is susceptible to tsunamis. This bay has an increasingly important role in Iran’s international trade, and therefore the assessment of the regional vulnerability to the effects of a tsunami is vital. Based on both the details of historical events and the results of numerical modeling of the propagation pattern of a tsunami in this region, this study assessed the vulnerability of buildings within the Chabahar Bay region to a tsunami event. The Papathoma Tsunami Vulnerability Assessment (PTVA) model was used to calculate a relative vulnerability index (RVI) for the affected buildings based on their physical and structural characteristics. The results showed that in a postulated worst-case-scenario tsunami event in the Chabahar Bay area, approximately 60 % of the residential buildings would be affected, a level of damage that is categorized as “Average” in the RVI classification. Overall, the economic losses related to the damage of residential buildings due to a tsunami in the Chabahar Bay area are anticipated to be the equivalent of US$ 16.5 million.     

Estimating <Emphasis Type="Italic">probable maximum loss</Emphasis> from a Cascadia tsunami

The Cascadia margin is capable of generating large magnitude seismic-tsunami. We use a 1:500 year tsunami hazard flood layer produced during a probabilistic tsunami hazard assessment as the input to a pilot study of the vulnerability of residential and commercial buildings in Seaside, OR, USA. We map building exposure, apply the Papathoma Tsunami Vulnerability Assessment Model to calculate building vulnerability and estimate probable maximum loss (PML) associated with a 1:500 year tsunami flood. Almost US$0.5 billion worth of buildings would be inundated, 95% of single story residential and 23% of commercial buildings would be destroyed with PML’s exceeding US$0.5 billion worth of buildings would be inundated, 95% of single story residential and 23% of commercial buildings would be destroyed with PML’s exceeding US116 million. These figures only represent a tiny fraction of the total values of exposed assets and loss that would be associated with a Cascadia tsunami impacting the NW Pacific coast. Not withstanding the various issues associated with our approach, this study represents the first time that PML’s have ever been calculated for a Cascadia type tsunami, and these results have serious implications for tsunami disaster risk management in the region. This method has the potential to be rolled out across the United States and elsewhere for estimating building vulnerability and loss to tsunami.     

Direct tangible damage assessment for regional snowmelt flood disasters with HJ-1 and HR satellite images: a case study of the Altay region,northern Xinjiang,China

Regional snowmelt flood disasters (RSFDs) can cause significant direct tangible damage which generally refers to the physical destruction due to direct contact with the flood water, such as damage to buildings, croplands, livestock, and infrastructure. Information about people, habitations, and infrastructure affected by the flood is essential for disaster responders and the humanitarian community to plan and coordinate emergency response activities. However, this direct tangible damage information obtained in the ground is limited, incomplete, contradictory, and sometimes impossible to obtain in a short time. Earth observation satellites help overcome operational uncertainties after the RSFDs. Here, we present an improved rapid direct tangible damage assessment model using HJ-1 and GF-1/2 satellite images. We selected the Altay region in northern Xinjiang, China, as the study area, and investigated a RSFD occurring in spring 2017. A series of HJ-1 and GF-1 images were used to track the flood extent over the duration of the disaster, and the maximum affected flood area was assigned as the area in which direct tangible damage occurred. Pre-disaster GF-2 images were then used to estimate direct tangible damage to habitations (2375 households and 6388 rooms), infrastructure (102 km of roads), and affected population (7125) in the flood area, which covered an area of 185,240 m². Our method is an effective approach for the design of rescue plans and disaster subsidy programs.     

Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates

With the recent transition to a more risk-based approach in flood management, flood risk models—being a key component in flood risk management—are becoming increasingly important. Such models combine information from four components: (1) the flood hazard (mostly inundation depth), (2) the exposure (e.g. land use), (3) the value of elements at risk and (4) the susceptibility of the elements at risk to hydrologic conditions (e.g. depth–damage curves). All these components contain, however, a certain degree of uncertainty which propagates through the calculation and accumulates in the final damage estimate. In this study, an effort has been made to assess the influence of uncertainty in these four components on the final damage estimate. Different land-use data sets and damage models have been used to represent the uncertainties in the exposure, value and susceptibility components. For the flood hazard component, inundation depth has been varied systematically to estimate the sensitivity of flood damage estimations to this component. The results indicate that, assuming the uncertainty in inundation depth is about 25 cm (about 15% of the mean inundation depth), the total uncertainty surrounding the final damage estimate in the case study area can amount to a factor 5–6. The value of elements at risk and depth–damage curves are the most important sources of uncertainty in flood damage estimates and can both introduce about a factor 2 of uncertainty in the final damage estimates. Very large uncertainties in inundation depth would be necessary to have a similar effect on the uncertainty of the final damage estimate, which seem highly unrealistic. Hence, in order to reduce the uncertainties surrounding potential flood damage estimates, these components deserve prioritisation in future flood damage research. While absolute estimates of flood damage exhibit considerable uncertainty (the above-mentioned factor 5–6), estimates for proportional changes in flood damages (defined as the change in flood damages as a percentage of a base situation) are much more robust.     

Trickle Down? Private sector participation and the pro-poor water supply debate in Jakarta, Indonesia

Private sector partnerships (PSPs) have been increasingly advocated as an instrument of ‘pro-poor’ water supply policies. This article examines the performance of the private sector with respect to network connections for poor households in Jakarta, Indonesia, drawing on three sources: data collected through a household survey of poor households in six Jakarta neighbourhoods in 2005; data provided by the two private concessionaires and the Jakarta municipal government; and interviews with water supply managers, government officials, and NGO representatives in 2001 and 2005. The analysis concludes that the Jakarta PSP contract has not been pro-poor: new connections were preferentially targeted at middle and upper-income households over the period 1998-2005, and the numbers of new connections have been lower than the original targets. The paper argues that the failure to connect the poor is not solely attributable to the private operators, and identifies disincentives to provide individual network connections to poor households on the part of the municipality, the private concessionaires and poor households. The paper concludes by questioning the long-term ability of private sector operators to supply water to the poor.     

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.     

Coping with floods in the city of Dresden,Germany

During August 2002 and again in March 2005 as well as in April 2006 the city of Dresden was hit by floods. The flood in 2002 was an extreme event, only comparable to flooding in 1862 and 1890 in Dresden. The flood discharge in 2006 was the second highest discharge since 1940 at the Dresden gauge although its return period was only about 15 years. This special situation enables a comparison of the preparedness of authorities and households in the flood endangered city of Dresden in 2002 after a long period of relatively low flood discharges and in 2005/2006 just a few years after a severe flood event. Before August 2002, the flood risk awareness and flood preparedness of authorities and households in Dresden was low. The inundation channels and the Elbe riverbed had not been maintained well. Just 13% of the households had undertaken building precautionary measures. The severe flood situation as well as the low flood preparedness led to tremendous damage, e.g., losses to residential buildings amounted to 304 million €. After 2002, the municipal authorities in Dresden developed a new flood management concept and many households were motivated to undertake precautionary measures. Building precautionary measures had been actually undertaken by 67% of the households before the floods in 2005 and 2006. Flood damage was significantly lower, due to the less severe flood situations and the much better preparedness. It is an important challenge for the future to keep preparedness at a high level also without recurrent flood experiences.     

Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach

An innovative approach in the investigation of complex landscapes for hydraulic modelling applications is the use of terrestrial laser scanner (TLS) that can lead to a high-resolution digital elevation model (DEM). Another notable factor in flood modelling is the selection of the hydrodynamic model (1D, 2D and 1D/2D), especially in complex riverine topographies, that can influence the accuracy of flood inundation area and mapping. This paper uses different types of hydraulic–hydrodynamic modelling approaches and several types of river and riparian area spatial resolution for the implementation of a sensitivity analysis for floodplain mapping and flood inundation modelling process at ungauged watersheds. Four data sets have been used for the construction of the river and riparian areas: processed and unprocessed TLS data, topographic land survey data and typical digitized contours from 1:5000-scale topographic maps. Modelling approaches combinations consist of: one-dimensional hydraulic models (HEC-RAS, MIKE 11), two-dimensional hydraulic models (MIKE 21, MIKE 21 FM) and combinations of coupled hydraulic models (MIKE 11/MIKE 21) within the MIKE FLOOD platform. Historical flood records and estimated flooded area derived from an observed extreme flash-flood event have been used in the validation process using 2 × 2 contingency tables. Flood inundation maps have been generated for each modelling approach and landscape configuration at the lower part of Xerias River reach at Volos, Greece, and compared for assessing the sensitivity of input data and model structure uncertainty. Results provided from contingency table analysis indicate the sensitivity of floodplain modelling on the DEM spatial resolution and the hydraulic modelling approach.     

An innovative micro-scale approach for vulnerability and flood risk assessment with the application to property-level protection adoptions

Economic damage assessment for flood risk estimation is established in many countries, but attentions have been focused on macro- or meso-scale approaches and less on micro-scale approaches. Whilst the macro- or meso-scale approaches of flood damage assessment are suitable for regional- or national-oriented studies, micro-scale approaches are more suitable for cost–benefit analysis of engineered protection measures. Furthermore, there remains lack of systematic and automated approaches to estimate economic flood damage for multiple flood scenarios for the purpose of flood risk assessment. Studies on flood risk have also been driven by the assumption of stationary characteristic of flood hazard, hence the stationary-oriented vulnerability assessment. This study proposes a novel approach to assess vulnerability and flood risk and accounts for adaptability of the approach to nonstationary conditions of flood hazard. The approach is innovative in which an automated concurrent estimation of economic flood damage for a range of flood events on the basis of a micro-scale flood risk assessment is made possible. It accounts for the heterogeneous distribution of residential buildings of a community exposed to flood hazard. The feasibility of the methodology was tested using real historical flow records and spatial information of Teddington, London. Vulnerability curves and residual risk associated with a number of alternative extents of property-level protection adoptions are estimated by the application of the proposed methodology. It is found that the methodology has the capacity to provide valuable information on vulnerability and flood risk that can be integrated in a practical decision-making process for a reliable cost–benefit analysis of flood risk reduction options.     

Flood vulnerability assessment of residential buildings by explicit damage process modelling

Natural Hazards - The present paper introduces a vulnerability modelling approach for residential buildings in flood. The modelling approach explicitly considers relevant damage processes, i.e....     

Flood events, fatalities and damages in India from 1978 to 2006

High temporal and spatial variability of rainfall qualifies India to be highly vulnerable to floods. Recurring floods of various magnitudes play havoc with the lives and property of the people, leading to unplanned development and unchecked environmental degradation, thwarting and retarding the overall development of the country. Therefore, the purpose of the present study is to analyze the types and trends in terms of flood events, frequency, number of people killed, injured, missing and economic damage both in space and time on the basis of a nationwide database published by India Meteorological Department, Pune, from 1978 to 2006. Analysis of these long-term data has revealed that 2,443 flood events claimed about 44,991 lives with the average of 1,551 lives each year. In terms of population size, these figures translate into a loss of 1.5 human lives per million of the population. A majority (56 %) of flood fatalities were caused during severe flood events. However, the frequency of these events was just 19 % in comparison with heavy rainfall events (65 %). In spatial context, flood-related fatalities are distributed all over the country with highest fatalities in Uttar Pradesh (17 %), Maharashtra (13 %), and Bihar and Gujarat (10 % each). Most fatalities occurred during the summer season monsoon months of August (30 %) followed by July (29 %) and September (20 %). The country suffered a cumulative flood-related economic loss of about 16 billion US$ between 1978 and 2006 and a maximum economic loss of 1.6 billion US$ in the year 2000 alone. The study further suggests that both flood events and fatalities have increased in India over a period of time.     

Scour hole depth prediction around pile groups: review,comparison of existing methods,and proposition of a new approach

Flooding is the most costly natural hazard event worldwide and can severely impact communities, both through economic losses and social disruption. To predict and reduce the flood risk facing a community, a reliable model is needed to estimate the cost of repairing flood-damaged buildings. In this paper, we describe the development and assessment of two models for predicting direct economic losses for single-family residential buildings, based on the experience of the 2013 Boulder, Colorado riverine floods. The first model is based on regression analyses on empirical data from over 3000 residential building damage inspections conducted by the Federal Emergency Management Agency (FEMA). This model enables a probabilistic assessment of loss (in terms of FEMA grants paid to homeowners for post-flood repairs) as a function of key building and flood hazard parameters, considering uncertainties in structural properties, building contents, and damage characteristics at a given flood depth. The second model is an assembly-based prediction of loss considering unit prices for damaged building components to predict mean repair costs borne by the homeowner, which is based on typical Boulder construction practices and local construction and material costs. Comparison of the two proposed models illustrates benefits that arise from each of the two approaches, while also serving to validate both models. These models can be used as predictive tools in the future, in Boulder and other US communities, due to adaptability of the model for other context, and similarities in home characteristics across the country. The assembly-based model quantifies the difference between the FEMA grants and true losses, providing a quantification of out-of-pocket homeowner expenses.     

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.     

Land Subsidence of Jakarta (Indonesia) and its Geodetic Monitoring System

Jakarta is the capital city of Indonesia with a population of about 10 million people, inhabiting an area of about 25 × 25 km. It has been reported for sometime that locations in Jakarta are subsiding at different rates. Up to the present, there has been no comprehensive information about the characteristics and pattern of land subsidence in the Jakarta area. Usually land subsidence in Jakarta is measured using extensometers and ground water level observations, or estimated using geological and hydrological parameters. To give a better picture about land subsidence, geodetic-based monitoring systems utilizing leveling and GPS surveys have also been implemented.The land subsidence characteristics of Jakarta and its surrounding area areinvestigated using data from three repeated leveling surveys performed in1982, 1991, and 1997, and two repeated GPS surveys conducted in 1997and 1999. Leveling surveys detected subsidence up to about 80 cm duringthe period of 1982–1991, and up to about 160 cm during the 1991–1997period; while GPS surveys observed subsidence up to about 20 cm duringthe period of 1997–1999. Comparison with the hydrological data shows thatland subsidence in Jakarta is strongly related to excessive groundwater extraction.     

Land subsidence of Jakarta (Indonesia) and its relation with urban development

Jakarta is the capital city of Indonesia with a population of about 9.6 million people, inhabiting an area of about 660 square-km. In the last three decades, urban development of Jakarta has grown very rapidly in the sectors of industry, trade, transportation, real estate, and many others. This exponentially increased urban development introduces several environmental problems. Land subsidence is one of them. The resulted land subsidence will also then affect the urban development plan and process. It has been reported for many years that several places in Jakarta are subsiding at different rates. The leveling surveys, GPS survey methods, and InSAR measurements have been used to study land subsidence in Jakarta, over the period of 1982–2010. In general, it was found that the land subsidence exhibits spatial and temporal variations, with the rates of about 1–15 cm/year. A few locations can have the subsidence rates up to about 20–28 cm/year. There are four different types of land subsidence that can be expected to occur in the Jakarta basin, namely: subsidence due to groundwater extraction, subsidence induced by the load of constructions (i.e., settlement of high compressibility soil), subsidence caused by natural consolidation of alluvial soil, and tectonic subsidence. It was found that the spatial and temporal variations of land subsidence depend on the corresponding variations of groundwater extraction, coupled with the characteristics of sedimentary layers and building loads above it. In general, there is strong relation between land subsidence and urban development activities in Jakarta.     

A real-time operation optimization model for flood management in river-reservoir systems

In this paper, a new methodology has been developed for real-time flood management in river-reservoir systems. This methodology is based upon combining a Genetic Algorithm (GA) reservoir operation optimization model for a cascade of two reservoirs, a hydraulic-based flood routing simulation model in downstream river system, a Geographical Information System (GIS) based database, and application of K-Nearest Neighbor (K-NN) algorithm for development of optimal operating rules. The GA optimization model estimates the optimal hourly reservoirs’ releases to minimize the flood damages in the downstream river. GIS tools have also been used for specifying different land-uses and damage functions in the downstream floodplain and it has been linked to the unsteady module of HEC-RAS flood routing model using Hec-GeoRAS module. An innovative approach has also been developed using K-NN algorithm to formulate the optimal operating rules for a system of two cascade reservoirs based on optimal releases obtained from the optimization model. During a flood event, the K-NN algorithm searches through the historical flood hydrographs and optimal reservoir storages determined by the optimization model to find similar situations. The similarity between the hydrographs is quantified based on the slopes of rising and falling limbs of inflow hydrographs and reservoir storages at the beginning of each hourly time step during the flood events for two cascade reservoirs. The developed methodology have been applied to the Bakhtiari and Dez River-Reservoir systems in southwest of Iran. The results show that the proposed models can be effectively used for flood management and real-time operation of cascade river-reservoir systems.     

Evaluation of food risk parameters in the Day River Flood Diversion Area,Red River Delta,Vietnam

An interdisciplinary approach is necessary for flood risk assessment. Questions are often raised about which factors should be considered important in assessing the flood risk in an area and how to quantify these factors. This article defines and quantitatively evaluates the flood risk factors that would affect the Day River Flood Diversion Area in the context of integrated flood management in the Red River Delta, Vietnam. Expert analysis, in conjunction with field survey and Analytical Hierarchy Process (AHP), is applied to define and quantify parameters (indicators, subcomponents, and components) that contribute to flood risk. Flood duration is found to be the most prominent indicator in determining flood hazard. Residential buildings, population, and pollution are other fairly significant indicators contributing to flood vulnerability from the economic, social, and environmental perspectives, respectively. The study results will be useful in developing comprehensive flood risk maps for policy-makers and responsible authorities. Besides, local residents will also be able to implement suitable measures for reducing flood risk in the study area.