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.

scholarly journals Integrate Weather Radar and Monitoring Devices for Urban Flooding Surveillance

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 825 ◽  
Author(s):  
Shih-Yen Hsu ◽  
Tai-Been Chen ◽  
Wei-Chang Du ◽  
Jyh-Horng Wu ◽  
Shih-Chieh Chen
Keyword(s):  
Real Time ◽  
Urban Areas ◽  
Weather Radar ◽  
Water Levels ◽  
Mitigation Measures ◽  
Extreme Weather Events ◽  
Television System ◽  
Urban Flood ◽  
Flood Monitoring ◽  
Image Capturing

With the increase of extreme weather events, the frequency and severity of urban flood events in the world are increasing drastically. Therefore, this study develops ARMT (automatic combined ground weather radar and CCTV (Closed Circuit Television System) images for real-time flood monitoring), which integrates real-time ground radar echo images and automatically estimates a rainfall hotspot according to the cloud intensity. Furthermore, ARMT combines CCTV image capturing, analysis, and Fourier processing, identification, water level estimation, and data transmission to provide real-time warning information. Furthermore, the hydrograph data can serve as references for relevant disaster prevention, and response personnel may take advantage of them and make judgements based on them. The ARMT was tested through historical data input, which showed its reliability to be between 83% to 92%. In addition, when applied to real-time monitoring and analysis (e.g., typhoon), it had a reliability of 79% to 93%. With the technology providing information about both images and quantified water levels in flood monitoring, decision makers can quickly better understand the on-site situation so as to make an evacuation decision before the flood disaster occurs as well as discuss appropriate mitigation measures after the disaster to reduce the adverse effects that flooding poses on urban areas.

scholarly journals Patch Similarity Convolutional Neural Network for Urban Flood Extent Mapping Using Bi-Temporal Satellite Multispectral Imagery

2019 ◽  
Vol 11 (21) ◽  
pp. 2492 ◽  
Author(s):  
Bo Peng ◽  
Zonglin Meng ◽  
Qunying Huang ◽  
Caixia Wang
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Real Time ◽  
Spectral Reflectance ◽  
Urban Areas ◽  
Flood Mapping ◽  
Urban Flooding ◽  
Urban Flood ◽  
Before And After ◽  
Flood Maps

Urban flooding is a major natural disaster that poses a serious threat to the urban environment. It is highly demanded that the flood extent can be mapped in near real-time for disaster rescue and relief missions, reconstruction efforts, and financial loss evaluation. Many efforts have been taken to identify the flooding zones with remote sensing data and image processing techniques. Unfortunately, the near real-time production of accurate flood maps over impacted urban areas has not been well investigated due to three major issues. (1) Satellite imagery with high spatial resolution over urban areas usually has nonhomogeneous background due to different types of objects such as buildings, moving vehicles, and road networks. As such, classical machine learning approaches hardly can model the spatial relationship between sample pixels in the flooding area. (2) Handcrafted features associated with the data are usually required as input for conventional flood mapping models, which may not be able to fully utilize the underlying patterns of a large number of available data. (3) High-resolution optical imagery often has varied pixel digital numbers (DNs) for the same ground objects as a result of highly inconsistent illumination conditions during a flood. Accordingly, traditional methods of flood mapping have major limitations in generalization based on testing data. To address the aforementioned issues in urban flood mapping, we developed a patch similarity convolutional neural network (PSNet) using satellite multispectral surface reflectance imagery before and after flooding with a spatial resolution of 3 meters. We used spectral reflectance instead of raw pixel DNs so that the influence of inconsistent illumination caused by varied weather conditions at the time of data collection can be greatly reduced. Such consistent spectral reflectance data also enhance the generalization capability of the proposed model. Experiments on the high resolution imagery before and after the urban flooding events (i.e., the 2017 Hurricane Harvey and the 2018 Hurricane Florence) showed that the developed PSNet can produce urban flood maps with consistently high precision, recall, F1 score, and overall accuracy compared with baseline classification models including support vector machine, decision tree, random forest, and AdaBoost, which were often poor in either precision or recall. The study paves the way to fuse bi-temporal remote sensing images for near real-time precision damage mapping associated with other types of natural hazards (e.g., wildfires and earthquakes).

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 Real-Time Control-Oriented Quality Modelling in Combined Urban Drainage Networks * *This research is funded by EU funding for the project LIFE EFFIDRAIN LIFE14 ENV/ES/00080

2017 ◽  
Vol 50 (1) ◽  
pp. 3941-3946 ◽  
Author(s):  
Congcong Sun ◽  
Bernat Joseph-Duran ◽  
Thibaud Maruejouls ◽  
Gabriela Cembrano ◽  
Jordi Meseguer ◽  
...  
Keyword(s):  
Real Time ◽  
Urban Drainage ◽  
Real Time Control ◽  
Time Control ◽  
Drainage Networks ◽  
Project Life

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.

Courtyard-level sewer data-enhanced two-dimensional hydraulic model for urban flood hazard assessment in Kunming, China

Water Policy ◽  
2014 ◽  
Vol 17 (1) ◽  
pp. 143-161
Author(s):  
Zhiqiang Xie ◽  
Qingyun Du ◽  
Zhongliang Cai ◽  
Huaixiang Liu ◽  
Sam Jamieson
Keyword(s):  
Statistical Method ◽  
Urban Areas ◽  
Flood Hazard ◽  
Ground Surface ◽  
Hydraulic Model ◽  
Two Dimensional ◽  
Urban Flood ◽  
One Dimensional ◽  
Municipal Level ◽  
Overlay Approach

This paper describes a study of urban flooding in downtown Kunming, China, simulating a major flood event that occurred in July 2008 using an improved two-dimensional (2D) hydraulic model enhanced with courtyard-level sewer data (CLSD). Although municipal authorities are not responsible for ‘private’ courtyard sewers, available records were specifically added to this model, enhancing its accuracy and usefulness. Geographic information system (GIS) flood maps, a mapping overlay approach and statistical method compared both predicted results and the recorded flood area. A statistical method also provided a measure of the correlation between the extent of the predicted flood areas and recorded flood areas (parameter ‘F’). Results of the improved 2D/CLSD model showed a correlation value for F of 51, 32.6% higher than the basic one-dimensional municipal-level sewer data (1D/MLSD) model; 26.2% higher than an interim version of the model that included a 2D ground surface (2D/MLSD). The 2D/CLSD model predicted flooding in 10 of the 12 courtyards with observed flooding. This was a major improvement over the 1D/MLSD model (three out of 12) and the 2D/MLSD model (five out of 12). Thus a CLSD-enhanced 2D hydraulic model potentially improves accuracy in predicting, mapping and understanding flood risk in urban areas.

Development of a Decision Support System for Flood Warning in Jinan City

2011 ◽  
Vol 219-220 ◽  
pp. 1267-1270 ◽  
Author(s):  
Chuan Qi Li ◽  
Chao Jia ◽  
Bang Shu Xu
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Real Time ◽  
Support System ◽  
Urban Areas ◽  
Flood Simulation ◽  
Urban Flood ◽  
Web Based ◽  
Flood Warning ◽  
Jinan City

A decision support system for flood warning has been developed for Jinan city. It is a web based distributed system that integrates GIS, databases and models. Urban Flood Simulation model is used as a real-time flood forecasting model. Mike Flood model is used to simulate pre-formulated flood scenarios for urban areas. The objective of the system is to simulate and forecast river and urban floods on the basis of real-time meteorological situation and rainfall available, and to serve as a tool for making decision.

scholarly journals Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1577
Author(s):  
David C. Mason ◽  
John Bevington ◽  
Sarah L. Dance ◽  
Beatriz Revilla-Romero ◽  
Richard Smith ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Real Time ◽  
Rural Areas ◽  
Urban Areas ◽  
Flood Hazard ◽  
Synthetic Aperture ◽  
Hazard Maps ◽  
Urban Flood ◽  
Flood Hazard Maps ◽  
Aperture Radar

Remotely sensed flood extents obtained in near real-time can be used for emergency flood incident management and as observations for assimilation into flood forecasting models. High-resolution synthetic aperture radar (SAR) sensors have the potential to detect flood extents in urban areas through clouds during both day- and night-time. This paper considers a method for detecting flooding in urban areas by merging near real-time SAR flood extents with model-derived flood hazard maps. This allows a two-way symbiosis, whereby currently available SAR urban flood extent improves future model flood predictions, while flood hazard maps obtained after the SAR overpasses improve the SAR estimate of urban flood extents. The method estimates urban flooding using SAR backscatter only in rural areas adjacent to urban ones. It was compared to an existing method using SAR returns in both rural and urban areas. The method using SAR solely in rural areas gave an average flood detection accuracy of 94% and a false positive rate of 9% in the urban areas and was more accurate than the existing method.

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.

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