Flood Damage In Urban Areas Research Articles

Flood risk assessment using an indicator based approach combined with flood risk maps and grid data

The increasing frequency of tropical cyclones, such as typhoons and localized heavy rainfall, increases the risk of flood damage in urban areas around the world. Countries implementing flood prevention projects use qualitative risk assessments, such as flood risk assessments, to support decision-making. However, existing flood risk assessment methods are not able to select and reflect only the damage targets that are directly exposed to flood risk. In addition, existing indexing methods are limited in improving the skewness of the raw data distribution, which distorts the calculated flood risk index. This study conducted a flood risk assessment based on an indicator-based approach using flood risk maps and grid data utilizing indicators (buildings, road area, etc.) from 2016 to 2019 for 44 cities and counties in the Gyeongsang-do Province. The flood risk assessment in this study consists of four items (Hazard, Exposure, Vulnerability, and Capacity) and nine indicators. Instead of using statistical data, we used the overlapped grids with the flood risk map for Exposure and Vulnerability indicators to reflect the flood risk exposed targets in the risk assessment. The limitations of existing indexing methods, such as min–max normalization, were improved by dividing the distribution into ten quantiles and scoring each quantile interval when indexing the indicators. Finally, entropy weights and Euclidean distance were applied to calculate the annual flood risk index of 44 cities and counties. The annual flood risk indices for local governments were arranged in descending order and then, the rankings of flood damage amount in 2019 were compared with the calculated index rankings. The sum and mean of absolute errors were 386 and 9.897, and the root mean square error was calculated as 11.930, which showed an improvement over the existing method. Using the calculated indices, it is possible to create Hazard vs. Capacity graph, Exposure vs. Vulnerability graph, or annual flood risk index graph. These graphs can be utilized to understand the level of exposure to flood risk of local governments and to assess the level of response through the Capacity index that contributes to damage reduction. It is believed that the flood risk assessment method presented in this study not only accurately identify the flood risk for local governments but can also be used to support decision-making processes to strengthen the government’s disaster prevention capabilities.

Comparison of Assessments of Urban Areas Using the Flood Vulnerability and Potential Flood Damage Methods

Recently, urban flood damage has rapidly increased due to climate change, rapid urbanization, and frequent guerrilla heavy rains. Therefore, a quantitative flood damage analysis technique is required for effective policy regarding flooding in urban areas. In this study, the flood vulnerability and potential flood damage (PFD) methods, which are representative methods for analyzing the degree of flood damage in urban areas, were applied. In addition, the results of each analysis method were compared and analyzed using the flood prevention capacity-damage (PCD) matrix technique, which intuitively shows that even if many existing flood protection facilities are built, flood damage can be large when there is insufficient management or heavy rainfall exceeding the design rainfall occurs. The two existing flood damage techniques estimated Seocho-gu to have low flood vulnerability due to high financial independence and many flood damage protection facilities. However, application of the PCD matrix resulted in classifying Seocho-gu as highly vulnerable to flooding. These conflicting results thus demonstrate that a more detailed review and analysis are necessary when establishing a flood protection policy.

Impact Assessment of Flood Damage in Urban Areas Using RCP 8.5 Climate Change Scenarios and Building Inventory

Korea has frequent flood damage due to localized torrential rain and typhoons as a result of climate change, which causes many casualties and property damage. In particular, much damage occurs due to urban inundation caused by stream flooding as a result of climate change. Thus, this study aims to analyze the effect of climate change on flood damage targeting the Wonjucheon basin, which is an urban stream flowing the city. For future rainfall data, RCP (Representative Concentration Pathways) 8.5 climate change scenario data was used, statistical detailed using SDQDM (Spatial Disaggregation with Quantile Delta Mapping) techniques, and daily data was downscaled using Copula model. In general, the flood damage rate is calculated by using the area ratio according to the land use in the administrative district, but in this study, the flood damage rate is calculated using the flood damage rate proposed in the multi-dimensional flood damage analysis using Building Inventory. Using the created future rainfall data and current data, the runoff in the Wonjucheon basin, Wonju-si, South Korea, by rainfall frequency was calculated through the Spatial Runoff Assessment Tool (S-RAT) model, which was a distributed rainfall-runoff model. The runoff was calculated using 100-year and 200-year frequency rainfalls for a four-hour duration and the flood damage area was calculated by applying the calculated runoff to the Flo-2D model, was developed by Federal Emergency Management Agency (FEMA) in United State of America, which was a flood inundation model. As a result of calculating the amount of discharge, it was analyzed that the average amount of discharge increased by 16% over the 100-year, 200-year frequency. The calculated result of the flood damage area was analyzed and the analysis results showed that the future flood damage area increased by around 30% at the 100-year frequency and around 15% at the 200-year frequency. The estimated flood damage by rainfall frequency was calculated using the flood damage area by frequency and multi-dimensional analysis, and the analysis result exhibited that the damage increased by around 23% at the 100-year frequency and around 45% at the 200-year frequency.

Planning green infrastructure to mitigate urban surface water flooding risk – A methodology to identify priority areas applied in the city of Ghent

Urban surface water floods pose growing threats in urban areas, which cause not only massive physical water disturbance, but also loss of human lives, destruction of social and economic infrastructures and disorder of society. The number and scale of flood damage in urban areas will continue to increase in the next several decades due to global trend in urbanization and climate change. Despite the extensive construction of grey infrastructures, many cities in the world remain vulnerable to surface water flooding, especially during the extremely weather events. Since the 1990s, green infrastructure has developed as an alternative and sustainable approach to mitigate flood hazard in urban areas. Despite the great effectiveness of urban green infrastructures in alleviating storm water runoff, there is comparatively little research for planners and designers to determine an appropriate strategy for green infrastructure planning. To address this gap, we propose a GIS-based multi-criteria evaluation method to identify the priority areas to site green infrastructure, based on five criteria: 1) storm-water runoff mitigation; 2) social flood vulnerable group protection; 3) flood sensitive area road infrastructures protection; 4) flood sensitive area buildings protection and 5) environmental justice. The weights of the five criteria are defined by the Analytic Hierarchy Process. We focus particularly on mitigating urban surface water flooding risk and demonstrate how the method can be applied using a case study of Ghent.

Algorithm to Predict the Rainfall Starting Point as a Function of Atmospheric Pressure, Humidity, and Dewpoint

Forecasting extreme precipitations is one of the main priorities of hydrology in Latin America and the Caribbean (LAC). Flood damage in urban areas increases every year, and is mainly caused by convective precipitations and hurricanes. In addition, hydrometeorological monitoring is limited in most countries in this region. Therefore, one of the primary challenges in the LAC region the development of a good rainfall forecasting model that can be used in an early warning system (EWS) or a flood early warning system (FEWS). The aim of this study was to provide an effective forecast of short-term rainfall using a set of climatic variables, based on the Clausius–Clapeyron relationship and taking into account that atmospheric water vapor is one of the variables that determine most meteorological phenomena, particularly regarding precipitation. As a consequence, a simple precipitation forecast model was proposed from data monitored at every minute, such as humidity, surface temperature, atmospheric pressure, and dewpoint. With access to a historical database of 1237 storms, the proposed model allows use of the right combination of these variables to make an accurate forecast of the time of storm onset. The results indicate that the proposed methodology was capable of predicting precipitation onset as a function of the atmospheric pressure, humidity, and dewpoint. The synoptic forecast model was implemented as a hydroinformatics tool in the Extreme Precipitation Monitoring Network of the city of Queretaro, Mexico (RedCIAQ). The improved forecasts provided by the proposed methodology are expected to be useful to support disaster warning systems all over Mexico, mainly during hurricanes and flashfloods.

A Remote Sensing Based Integrated Approach to Quantify the Impact of Fluvial and Pluvial Flooding in an Urban Catchment

Pluvial (surface water) flooding is often the cause of significant flood damage in urban areas. However, pluvial flooding is often overlooked in catchments which are historically known for fluvial floods. In this study, we present a conceptual remote sensing based integrated approach to enhance current practice in the estimation of flood extent and damage and characterise the spatial distribution of pluvial and fluvial flooding. Cockermouth, a town which is highly prone to flooding, was selected as a study site. The flood event caused by named storm Desmond in 2015 (5-6/12/2015) was selected for this study. A high resolution digital elevation model (DEM) was produced from a composite digital surface model (DSM) and a digital terrain model (DTM) obtained from the Environment Agency. Using this DEM, a 2D flood model was developed in HEC-RAS (v5) 2D for the study site. Simulations were carried out with and without pluvial flooding. Calibrated models were then used to compare the fluvial and combined (pluvial and fluvial) flood damage areas for different land use types. The number of residential properties affected by both fluvial and combined flooding was compared using a combination of modelled results and data collected from Unmanned Aircraft Systems (UAS). As far as the authors are aware, this is the first time that remote sensing data, hydrological modelling and flood damage data at a property level have been combined to differentiate between the extent of flooding and damage caused by fluvial and pluvial flooding in the same event. Results show that the contribution of pluvial flooding should not be ignored, even in a catchment where fluvial flooding is the major cause of the flood damages. Although the additional flood depths caused by the pluvial contribution were lower than the fluvial flood depths, the affected area is still significant. Pluvial flooding increased the overall number of affected properties by 25%. In addition, it increased the flood depths in a number of properties that were identified as being affected by fluvial flooding, in some cases by more than 50%. These findings show the importance of taking pluvial flooding into consideration in flood management practices. Further, most of the data used in this study was obtained via remote sensing methods, including UAS. This demonstrates the merit of developing a remote sensing based framework to enhance current practices in the estimation of both flood extent and damage.

Experimental estimation of the head loss coefficient at surcharged four-way junction manholes

ABSTRACTThe head loss caused by the surcharged flow from four-way junction manholes is the main cause of increased flood damage in urban areas. The flow pattern significantly varies depending on the inflow conditions of the inlet pipes and constitutes the flow conditions of a four-way junction manhole, three-way junction manholes, and middle manholes. Therefore, the head loss changes with various manhole shapes must be analyzed. In this study, physical model study apparatus was prepared. Various flow rate conditions were selected by changing the flow rate ratios of the inlet pipes at 10% intervals. The head loss coefficients were also estimated. A head loss coefficient range diagram was generated based on the results. A head loss coefficient empirical formula that considers all flow conditions for surcharged four-way junction manholes is proposed. The proposed equation should be applicable to the design and assessment of drainage systems with varying inlet pipe flow rates.

Experimental Studies on Surface Vortex Mitigation Using the Floating Anti-Vortex Device in Sump Pumps

The maintenance of the performance of sump pumps is important to mitigate flood damage in urban areas and lowlands. However, the air-entraining vortex in the sump leads to undesirable performance degradation. Thus, in this study, the newly designed floating anti-vortex device (F-AVD) was employed in the intake pipe to enhance the efficiency of water intake in the sump by decreasing the surface vortex. The performance of the F-AVD was evaluated from the model experiments, in which the sump model was designed to represent the pump station that operates in Korea. The flow in the sump was measured using the particle image velocimetry (PIV) technique, and the velocity and vorticity distributions were compared both with and without the adoption of the F-AVD. The experimental results indicated that the vortex structures behind the intake pipe were effectively mitigated by installing the F-AVD. The vorticity magnitude behind the intake pipe was reduced in range of 24.8–52.5% after the installation of the F-AVD. However, in the case of a flow rate increase, the efficiency of the F-AVD decreased because of the strong vortex. Thus, an additional anti-vortex device (AVD), which is attached to the backwall or the floor in the sump, is required to prevent the air entrainment in conditions with high flow rates.

Application of Flood Nomograph for Flood Forecasting in Urban Areas

Imperviousness has increased due to urbanization, as has the frequency of extreme rainfall events by climate change. Various countermeasures, such as structural and nonstructural measures, are required to prepare for these effects. Flood forecasting is a representative nonstructural measure. Flood forecasting techniques have been developed for the prevention of repetitive flood damage in urban areas. It is difficult to apply some flood forecasting techniques using training processes because training needs to be applied at every usage. The other flood forecasting techniques that use rainfall data predicted by radar are not appropriate for small areas, such as single drainage basins. In this study, a new flood forecasting technique is suggested to reduce flood damage in urban areas. The flood nomograph consists of the first flooding nodes in rainfall runoff simulations with synthetic rainfall data at each duration. When selecting the first flooding node, the initial amount of synthetic rainfall is 1 mm, which increases in 1 mm increments until flooding occurs. The advantage of this flood forecasting technique is its simple application using real-time rainfall data. This technique can be used to prepare a preemptive response in the process of urban flood management.

Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

Abstract. The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth–damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.

Ｘバンド偏波レーダを用いた発達する降水セルの検出に関する研究

In recent years, flood damage in urban areas due to localized heavy rain has been a serious problem. In order to save life from the flood damage, rainfall forecast is important even if 10-minute lead time. To improve the rainfall forecast system, an index is necessary to detect the hazardous storm. High ZDR area which is extending above the freezing level, i.e. a ZDR column, is associated with strong updraft. We investigated a relation between the ZDR column and storm development using X-band polarimetric radar observations. It is known that ZDR is susceptible from rainfall attenuation especially in X-band radar. On the other hand, KDP is not affected from rainfall attenuation. Therefore, we also studied the effectiveness of KDP column. We found that ZDR column (KDP column) were formed about 15 min (10 min) prior to the onset of heavy rainfall on the ground based on the cell tracking algorithm.

Bayesian inference analysis of the uncertainty linked to the evaluation of potential flood damage in urban areas

Flood damage in urbanized watersheds may be assessed by combining the flood depth-damage curves and the outputs of urban flood models. The complexity of the physical processes that must be simulated and the limited amount of data available for model calibration may lead to high uncertainty in the model results and consequently in damage estimation. Moreover depth-damage functions are usually affected by significant uncertainty related to the collected data and to the simplified structure of the regression law that is used. The present paper carries out the analysis of the uncertainty connected to the flood damage estimate obtained combining the use of hydraulic models and depth-damage curves. A Bayesian inference analysis was proposed along with a probabilistic approach for the parameters estimating. The analysis demonstrated that the Bayesian approach is very effective considering that the available databases are usually short.

수해취약성인자를 이용한 고위험 도시침수지역의 평가기법에 대한 연구

Due to urban population growth and increase of impervious ratio, backwardness of major infrastructure, increased rainfall intensity in climate change, and so on, the risk of flood damage in urban areas is increasing. In order to establish measures for this, quantitative analysis for flood damage that occurs in urban areas is needed. In this study, a methodology assessing high-risk areas vulnerable to flooding in units of drainage catchments by comparing the city`s flood zone and flood vulnerability factors is proposed. Using flood damage data, the city`s flood zone is delimited by inundation area and inundation frequency to be analyzed. Taking into account the ease of date collection, lowland areas, lack of sewer discharge capacity, imperviousness, and runoff curve number are selected as the flood vulnerability factors. As an application, high-risk drainage catchments vulnerable to flooding in Juanang stream watershed are identified.

Coupled 1D and Noninertia 2D Flood Inundation Model for Simulation of Urban Flooding

Pluvial flooding in urban areas drained by storm sewer networks is characterized by surcharge-induced inundation. Urban inundation models need to reproduce the complex interaction between the sewer flow and the surcharge-induced inundation to make reasonable predictions of the likely flood damage in urban areas. In the framework of the present work, the storm sewer model SWMM5 and a newly developed two-dimensional (2D) noninertia overland-flow model have been coupled to simulate the interaction between the sewer system and the urban floodplain. The solution of the 2D model is on the basis of an alternating direction implicit scheme that solves the 2D noninertia free-surface shallow-water equations. For accuracy reasons, the time step is limited and controlled by the use of iteration to home-in on an accurate solution at each sweep. The dynamic interaction between the two models is bidirectional, and the interacting discharges are calculated according to the water level differences between the flows in the sewer system network and aboveground flows. The paper presents details of the newly developed 2D model and describes the way in which the model was coupled with a one-dimensional (1D) sewer network model (SWMM5). The models were tested on one hypothetical case study and one real-life case study.

On the use of 1D and coupled 1D-2D modelling approaches for assessment of flood damage in urban areas

Urban flooding has become an increasingly important problem and a growing social issue around the world. Since it continues to be regarded as an almost inevitable danger, the development of cost-effective flood management strategies has become of the utmost importance for many cities, and particularly for those cities in developing countries where the financial resources for recovery from flood-related disasters are almost nonexistent. As a consequence, there is nowadays a range of modelling approaches available for modelling floods and developing flood management strategies. Typically, one-dimensional (1D) hydrodynamic models are used as a standard industry practice. More recently, however, model formulations have included a 1D representation of the main channels and a 2D representation of the floodplains. Since the physical process of describing exchanges of flows with the floodplains can be represented in different ways, the predictive capability of the different modelling approaches can also vary. The present paper explores the difference in predictive capabilities of 1D and 1D-2D modelling approaches for the purpose of urban flood analysis across irregular terrains. It is shown, as expected, that in the case of terrains suited to exclusively 1D models the prediction of flow variables along the channel can be realistic, but that, when it comes to the projection onto a 2D map, the representation of the terrain topography together with the mapping techniques that are employed introduce a limiting factor in their successful application. Practical implications of these two modelling approaches are analysed and illustrated on a case study from St Maarten, NA. The results of this study provide users of numerical models with information that can be used to aid them in determining which tool to use and which aspects to consider in order to make more reliable analyses of flooding processes in urban areas.

A PROPOSALE FOR FLOOD DAMAGE REDUCTION IN URBAN AREA BY“WATER PATHWAY”

By analogy to the concept of “Wind Ventilation Lane” used in urban heat island studies, the present paper proposes a new approach to reduce flood damage in urban areas, which is hereafter referred to as “Water Pathway”. The basic idea is to take advantage of the urban flooding characteristics that flood water tends to concentrate in roads and thus to channel flood water to designated areas where flood damage could be minimized or controlled.For feasibility study, a hybrid model is constructed, which combines a 2-D inundation model with a 1-D model for “Water Pathway”. The application to the Sanjo city flooding, which occurred last summer, shows clearly that the water pathway approach is promising. Besides, we propose that PTSD (Posttraumatic Stress Disorder) should be dealt with as an important factor in flood damage reduction planning.