scholarly journals Risk Type Analysis of Building on Urban Flood Damage

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2505
Author(s):  
Kiyong Park ◽  
Sang-Hyun Choi ◽  
Insang Yu
Keyword(s):  
Flood Risk ◽  
Urban Areas ◽  
Flood Damage ◽  
Vulnerability Analysis ◽  
Precipitation Pattern ◽  
City Development ◽  
Urban Flood ◽  
Risk Class ◽  
Exposure Analysis ◽  
Building Type

Climate change caused by global warming has resulted in an increase in average temperature and changes in precipitation pattern and intensity. Consequently, this has led to an increase in localized heavy rain which intensifies the uncertainty of the development of urban areas. To minimize flood damage in an urban area, this study aims to analyze the flood risk effect on buildings by ranking the risk of flood damage for each building type and sorting the long-term land use plan and the building type that requires particular consideration. To evaluate the flood risk of each building type, vulnerability analysis and exposure analysis were conducted in five regions of the Ulsan City. The vulnerability analysis includes determination of each building type by using the building elements which are sensitive to flood damage. In terms of the exposure analysis, environmental factors were applied to analyze the flood depth. The mapping based on the results from two analyses provided the basis for classifying the flood risk into five classes (green, yellowish green, yellow, orange, red). The results were provided in the urban spatial form for each building type. This analysis shows that the district near the Taehwa river is the area with the highest risk class buildings (red and orange class buildings). Notably, this area plays a pivotal functional role in administrating the Ulsan City and has a high density of buildings. This phenomenon is explained by city development which is centered around the lowland; however, given the high value of property, the potential risk is proven to be high.

Flood risk modelling based on tangible and intangible urban flood damage quantification

2010 ◽  
Vol 62 (1) ◽  
pp. 189-195 ◽  
Author(s):  
J. A. E. ten Veldhuis ◽  
F. H. L. R. Clemens
Keyword(s):  
Flood Risk ◽  
Urban Areas ◽  
Human Health Risk ◽  
Flood Damage ◽  
Call Centre ◽  
Damage Functions ◽  
Urban Flood ◽  
Risk Modelling ◽  
Traffic Disturbance ◽  
Risk Curves

The usual way to quantify flood damage is by application stage-damage functions. Urban flood incidents in flat areas mostly result in intangible damages like traffic disturbance and inconvenience for pedestrians caused by pools at building entrances, on sidewalks and parking spaces. Stage-damage functions are not well suited to quantify damage for these floods. This paper presents an alternative method to quantify flood damage that uses data from a municipal call centre. The data cover a period of 10 years and contain detailed information on consequences of urban flood incidents. Call data are linked to individual flood incidents and then assigned to specific damage classes. The results are used to draw risk curves for a range of flood incidents of increasing damage severity. Risk curves for aggregated groups of damage classes show that total flood risk related to traffic disturbance is larger than risk of damage to private properties, which in turn is larger than flood risk related to human health. Risk curves for detailed damage classes show how distinctions can be made between flood risks related to many types of occupational use in urban areas. This information can be used to support prioritisation of actions for flood risk reduction. Since call data directly convey how citizens are affected by urban flood incidents, they provide valuable information that complements flood risk analysis based on hydraulic models.

scholarly journals Impact Assessment of Urban Flood on Traffic Disruption using Rainfall–Depth–Vehicle Speed Relationship

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 926 ◽  
Author(s):  
Kyung-Su Choo ◽  
Dong-Ho Kang ◽  
Byung-Sik Kim
Keyword(s):  
Urban Areas ◽  
Assessment Tool ◽  
Transportation Network ◽  
Flood Damage ◽  
Target Area ◽  
Vehicle Speed ◽  
Urban Flood ◽  
Socioeconomic Impacts ◽  
Flood Depth ◽  
Driving Speed

The transportation network enables movement of people and goods and is the basis of economic activity. Recently, short-term locally heavy rains occur frequently in urban areas, causing serious obstacles to road flooding and increasing economic and social effects. Therefore, in advanced weather countries, many studies have been conducted on realistic and reliable impact forecasting by analyzing socioeconomic impacts, not just information transmission as weather forecasts. In this paper, we use the Spatial Runoff Assessment Tool (S-RAT) and Flood Inundation model (FLO-2D model) to calculate the flooding level in urban areas caused by rainfall and use the flooding rate. In addition, the rainfall–flood depth curve and the Flood–Vehicle Speed curve were presented during the analysis, and the traffic disruption map was prepared using this. The results of this study were compared with previous studies and verified by rainfall events in 2011. As a result of the verification, the result was similar to the actual flooding, and when the same rainfall occurred within the range of the target area, it was confirmed that there were sections that could not be passed and sections that could be passed smoothly. Therefore, the results suggested in this study will be helpful for the driver’s route selection by using the urban flood damage analysis and vehicle driving speed analysis.

scholarly journals Vulnerability Assessment of Urban Floods in Lahore, Pakistan using GIS based integrated Analytical Hierarchy Approach

2021 ◽  
Vol 58 (1) ◽  
pp. 85-96
Author(s):  
Sahar Zia ◽  
Safdar A. Shirazi ◽  
Muhammad Nasar-u-Minallah
Keyword(s):  
Land Use ◽  
Flood Risk ◽  
Urban Areas ◽  
Physical Factors ◽  
Urban Flooding ◽  
Residential Areas ◽  
Urban Flood ◽  
Risk Areas ◽  
Practical Tool ◽  
Flood Risk Mapping

Urban flooding is getting attention due to its adverse impact on urban lives in mega cities of the developing world particularly Pakistan. This study aims at finding a suitable methodology for mapping urban flooded areas to estimate urban flooding vulnerability risks in the cities of developing countries particularly Lahore, Pakistan. To detect the urban flooded vulnerability and risk areas due to natural disaster, GIS-based integrated Analytical Hierarchy Process (AHP) is applied for the case of Lahore, which is the second most populous city and capital of the Punjab, Pakistan. For the present research, the flood risk mapping is prepared by considering these significant physical factors like elevation, slope, and distribution of rainfall, land use, density of the drainage network, and soil type. Results show that the land use factor is the most significant to detect vulnerable areas near roads and commercial areas. For instance, this method of detection is 88%, 80% and 70% accurate for roads, commercial and residential areas. The methodology implemented in the present research can provide a practical tool and techniques to relevant policy and decision-makers authorities to prioritize and actions to mitigate flood risk and vulnerabilities and identify certain vulnerable urban areas, while formulating a methodology for future urban flood risk and vulnerability mitigation through an objectively simple and organizationally secure approach. 

scholarly journals Methodology for qualitative urban flooding risk assessment

2013 ◽  
Vol 68 (4) ◽  
pp. 829-838 ◽  
Author(s):  
João P. Leitão ◽  
Maria do Céu Almeida ◽  
Nuno E. Simões ◽  
André Martins
Keyword(s):  
Risk Assessment ◽  
Public Transportation ◽  
Flood Risk ◽  
Urban Areas ◽  
Overland Flow ◽  
Urban Flood ◽  
Rainfall Events ◽  
Transportation Services ◽  
Recent Developments ◽  
Flooding Risk

Pluvial or surface flooding can cause significant damage and disruption as it often affects highly urbanised areas. Therefore it is essential to accurately identify consequences and assess the risks associated with such phenomena. The aim of this study is to present the results and investigate the applicability of a qualitative flood risk assessment methodology in urban areas. This methodology benefits from recent developments in urban flood modelling, such as the dual-drainage modelling concept, namely one-dimensional automatic overland flow network delineation tools (e.g. AOFD) and 1D/1D models incorporating both surface and sewer drainage systems. To assess flood risk, the consequences can be estimated using hydraulic model results, such as water velocities and water depth results; the likelihood was estimated based on the return period of historical rainfall events. To test the methodology two rainfall events with return periods of 350 and 2 years observed in Alcântara (Lisbon, Portugal) were used and three consequence dimensions were considered: affected public transportation services, affected properties and pedestrian safety. The most affected areas in terms of flooding were easily identified; the presented methodology was shown to be easy to implement and effective to assess flooding risk in urban areas, despite the common difficulties in obtaining data.

scholarly journals Managing Large Geodatasets for Urban Flood Risk Mapping: The Mexican Flood Risk Atlas

10.29007/l6jd ◽  
2018 ◽  
Author(s):  
Laurent Guillaume Courty ◽  
Jose Agustín Breña-Naranjo ◽  
Adrián Pedrozo-Acuña
Keyword(s):  
Time Series ◽  
Flood Risk ◽  
Urban Areas ◽  
Risk Mapping ◽  
Post Processing ◽  
Urban Flood ◽  
Gis Database ◽  
Flood Risk Mapping ◽  
Flood Maps ◽  
Urban Flood Risk

We present a flood risk mapping framework created in the context of the update of the Mexican flood risk atlas. This framework is based on a nation-wide GIS database of map time-series. Those maps are used as forcing for a deterministic, raster-based numerical model. For each catchment of interest, the model retrieves the data from the GIS and perform the computation on the specified area. The results are written directly in the GIS database, which facilitate their post-processing. This methodology allows 1) the generation of flood risk maps in cities located across the national territory, without too much effort in the pre and post-processing of information and 2) a very efficient process to create new flood maps for urban areas that have not been included in the original batch.

scholarly journals A GIS based urban flood risk analysis model for vulnerability assessment of critical structures during flood emergencies

2014 ◽  
Vol 2 (4) ◽  
pp. 2405-2441
Author(s):  
R. Albano ◽  
A. Sole ◽  
J. Adamowski ◽  
L. Mancusi
Keyword(s):  
Risk Analysis ◽  
Urban Area ◽  
Flood Risk ◽  
Urban Areas ◽  
Quantitative Estimation ◽  
Urban System ◽  
Analysis Model ◽  
Urban Flood ◽  
Practical Applications ◽  
Flood Risk Analysis

Abstract. Risk analysis has become a priority for authorities and stakeholders in many European countries, with the aim of reducing flooding risk by considering the priority and benefits of possible interventions. Within this context, a flood risk analysis model was developed in this study that is based on GIS, and integrated with a model that assesses the degree of accessibility and operability of strategic emergency response structures in an urban area. The proposed model is unique in that it provides a quantitative estimation of flood risk on the basis of the operability of the strategic emergency structures in an urban area, their accessibility, and connection within the urban system of a city (i.e., connection between aid centres and buildings at risk) in the emergency phase. The results of a case study in the Puglia Region in Southern Italy are described to illustrate the practical applications of this newly proposed approach. The main advantage of the proposed approach is that it allows for the defining of a hierarchy between different infrastructures in the urban area through the identification of particular components whose operation and efficiency are critical for emergency management. This information can be used by decision makers to prioritize risk reduction interventions in flood emergencies in urban areas.

scholarly journals Development and Application of an Urban Flood Forecasting and Warning Process to Reduce Urban Flood Damage: A Case Study of Dorim River Basin, Seoul

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 187
Author(s):  
Yong-Man Won ◽  
Jung-Hwan Lee ◽  
Hyeon-Tae Moon ◽  
Young-Il Moon
Keyword(s):  
Deep Learning ◽  
Flood Risk ◽  
Flood Forecasting ◽  
Flood Damage ◽  
Urban Stream ◽  
Urban Flood ◽  
Model Driven ◽  
Forecasting And Warning ◽  
Rainfall Runoff Model ◽  
Pump Stations

Early and accurate flood forecasting and warning for urban flood risk areas is an essential factor to reduce flood damage. This paper presents the urban flood forecasting and warning process to reduce damage in the main flood risk area of South Korea. This process is developed based on the rainfall-runoff model and deep learning model. A model-driven method was devised to construct the accurate physical model with combined inland-river and flood control facilities, such as pump stations and underground storages. To calibrate the rainfall-runoff model, data of gauging stations and pump stations of an urban stream in August 2020 were used, and the model result was presented as an R2 value of 0.63~0.79. Accurate flood warning criteria of the urban stream were analyzed according to the various rainfall scenarios from the model-driven method. As flood forecasting and warning in the urban stream, deep learning models, vanilla ANN, Long Short-Term Memory (LSTM), Stack-LSTM, and Bidirectional LSTM were constructed. Deep learning models using 10-min hydrological time-series data from gauging stations were trained to warn of expected flood risks based on the water level in the urban stream. A forecasting and warning method that applied the bidirectional LSTM showed an R2 value of 0.9 for the water level forecast with 30 min lead time, indicating the possibility of effective flood forecasting and warning. This case study aims to contribute to the reduction of casualties and flood damage in urban streams and accurate flood warnings in typical urban flood risk areas of South Korea. The developed urban flood forecasting and warning process can be applied effectively as a non-structural measure to mitigate urban flood damage and can be extended considering watershed characteristics.

scholarly journals Real-time urban flood forecasting and modelling – a state of the art

2013 ◽  
Vol 15 (3) ◽  
pp. 717-736 ◽  
Author(s):  
Justine Henonin ◽  
Beniamino Russo ◽  
Ole Mark ◽  
Philippe Gourbesville
Keyword(s):  
Real Time ◽  
Flood Risk ◽  
Urban Areas ◽  
Urban Drainage ◽  
Flood Forecast ◽  
Coupled Models ◽  
Urban Flood ◽  
Maximum Rainfall ◽  
One Dimensional ◽  
Drainage Networks

All urban drainage networks are designed to manage a maximum rainfall. This situation implies an accepted flood risk for any greater rainfall event. This risk is often underestimated as factors such as city growth and climate change are ignored. But even major structural changes cannot guarantee that urban drainage networks would cope with all future rain events. Thus, being able to forecast urban flooding in real time is one of the main issues of integrated flood risk management. Runoff and hydraulic models can be essential elements of flood forecast systems, as an active part of the system or as studying tools. This paper gives an overview of current available options for pluvial flood modelling in urban areas, from basic estimations with a one-dimensional urban drainage model to detailed flood process representation with one dimensional–two dimensional hydrodynamic coupled models. Each type of modelling solution is described with pros and cons regarding urban flood analysis. The paper then elaborates on real-time flood forecast systems and the influence of their main components. A classification of real-time urban flood systems is given based on the use of urban models, i.e. empirical scenarios, pre-simulated scenarios and real-time simulations. A review of existing operational systems is done using this classification.

Sign in / Sign up

Export Citation Format

Share Document