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

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.

2012 ◽  
Vol 66 (8) ◽  
pp. 1669-1677 ◽  
Author(s):  
C. M. Fontanazza ◽  
G. Freni ◽  
V. Notaro

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.


Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2505
Author(s):  
Kiyong Park ◽  
Sang-Hyun Choi ◽  
Insang Yu

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.


2021 ◽  
Author(s):  
Fatemeh Yavari ◽  
Seyyed Ali Akbar Salehi Neyshabouri ◽  
Jafar Yazdi ◽  
amir molajou

Abstract The study of non-stationary effects of hydrological time series and land-use changes in urban areas is essential to predict future floods and their probable damage. In the current study, a novel method was proposed for analyzing their simultaneous impact. For this purpose, rainfall frequency and land-use changes analyses were conducted for two different long-term periods, and the results were compared. Then, hydrologic modeling of the catchment was carried out using the HEC-HMS model, and obtained hydrographs were fed to the HEC-RAS2D model for estimating flood inundation areas. Using the economic information of assets and their damage functions, flood damages related to these two periods were evaluated through the HEC-FIA model. The results indicated that in the low return periods (e.g., 2-year flood), the damage in the second period was increased with respect to the first one but increased for the return periods of 5 to 100 years. Furthermore, surface runoff showed a 4.65% increase due to land-use change and a 12% increase due to rainfall non-stationarity. Moreover, flood damage showed a 136% increase on average, and among the two studied factors, the non-stationarity of rainfalls is considerably more effective on flood intensification.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 926 ◽  
Author(s):  
Kyung-Su Choo ◽  
Dong-Ho Kang ◽  
Byung-Sik Kim

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.


2019 ◽  
Author(s):  
Matteo U. Parodi ◽  
Alessio Giardino ◽  
Ap van Dongeren ◽  
Stuart G. Pearson ◽  
Jeremy D. Bricker ◽  
...  

Abstract. Considering the likely increase of coastal flooding in Small Island Developing States (SIDS), coastal managers at the local and global level have been developing initiatives aimed at implementing Disaster Risk Reduction (DRR) measures and adapting to climate change. Developing science-based adaptation policies requires accurate coastal flood risk (CFR) assessments, which are often subject to the scarcity of sufficiently accurate input data for insular states. We analysed the impact of uncertain inputs on coastal flood damage estimates, considering: (i) significant wave height, (ii) storm surge level and (iii) sea level rise (SLR) contributions to extreme sea levels, as well as the error-driven uncertainty in (iv) bathymetric and (v) topographic datasets, (vi) damage models and (vii) socioeconomic changes. The methodology was tested through a sensitivity analysis using an ensemble of hydrodynamic models (XBeach and SFINCS) coupled with an impact model (Delft-FIAT) for a case study at the islands of São Tomé and Príncipe. Model results indicate that for the current time horizon, depth damage functions (DDF) and digital elevation model (DEM) dominate the overall damage estimation uncertainty. We find that, when introducing climate and socioeconomic uncertainties to the analysis, SLR projections become the most relevant input for the year 2100 (followed by DEM and DDF). In general, the scarcity of reliable input data leads to considerable predictive error in CFR assessments in SIDS. The findings of this research can help to prioritise the allocation of limited resources towards the acquisitions of the most relevant input data for reliable impact estimation.


Author(s):  
Daniela Molinari ◽  
Karin De Bruijn ◽  
Jessica Castillo ◽  
Giuseppe T. Aronica ◽  
Laurens M. Bouwer

Abstract. Although often neglected, model validation is a key topic in flood risk analysis, as flood risk estimates are characterised by significant levels of uncertainty. In this paper, we discuss the state of art of flood risk models validation, as concluded from the discussion among more than 50 experts at two main scientific events. The events aimed at identifying policy and research recommendations towards promoting more common practice of validation, and an improvement of flood risk models reliability. We pay specific attention to the different components of the risk modelling chain (i.e. flood hazard, defence failure and flood damage analysis) as well as to their role into risk estimates, to highlight specificities and commonalities with respect to implemented techniques and research needs. The main conclusions from this review can be summarised as the need of higher quality data to perform validation and of benchmark solutions to be followed in different contexts, along with a greater involvement of end-users in the debate on flood risk models validation.


Author(s):  
Sahar Zia ◽  
Safdar A. Shirazi ◽  
Muhammad Nasar-u-Minallah

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. 


2018 ◽  
Vol 39 (2) ◽  
pp. 229-246 ◽  
Author(s):  
Akinola Adesuji Komolafe ◽  
Srikantha Herath ◽  
Ram Avtar ◽  
Jean-Francois Vuillaume

2013 ◽  
Vol 68 (4) ◽  
pp. 829-838 ◽  
Author(s):  
João P. Leitão ◽  
Maria do Céu Almeida ◽  
Nuno E. Simões ◽  
André Martins

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.


10.29007/l6jd ◽  
2018 ◽  
Author(s):  
Laurent Guillaume Courty ◽  
Jose Agustín Breña-Naranjo ◽  
Adrián Pedrozo-Acuña

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.


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