scholarly journals Predicting Accurate Urban Flooding from Nuisance Flows to Major Disasters

10.29007/81mt ◽  
2018 ◽  
Author(s):  
Noemi Gonzalez-Ramirez ◽  
Fernando Nardi ◽  
James S. O'Brien
Keyword(s):  
Surface Water ◽  
Urban Areas ◽  
Flood Hazard ◽  
Water Flooding ◽  
System Capacity ◽  
Urban Flooding ◽  
Urban Flood ◽  
Building Roof ◽  
Building Collapse ◽  
Storm Drain

Two-dimensional flood models are becoming increasing more accurate in simulating surface water flooding. Concurrently flood hazard maps have higher resolution to support flood mitigation planning. Most flood studies focus on large river flooding (~ 100-yr flood), but in urban areas, emergency access and evacuation routes are needed for frequent rainfall and flood events (< 10-yr return periods). Urban flooding is more complex than river margin flooding and requires significantly more model detail to accurate access risk and hazard for frequent storms. Urban flooding is an event characterized by its frequent repetitive and systematic impact on population and urban infrastructure. Detailed urban flood inundation is now being performed with spatially and temporally variable rainfall and infiltration, channel and street flow, hydraulic structures, surface water storm drain exchange, building loss of storage and flow obstruction, building collapse, levee/wall overtopping and collapse, groundwater flow, sediment scour/deposition and mudflows. In residential neighborhoods, shallow flooding is controlled by streets, buildings, walls and storm drain facilities. Several flood model details and their impact on shallow flooding are discussed including spatially variable storm intensities on pervious and impervious surfaces, surface water exchange with limited storm drain system capacity, and building roof runoff. Several predictive strategies are highlighted to simulate flooding from nuisance flows to major disasters.

scholarly journals Urban surface water flood modelling – a comprehensive review of current models and future challenges

2020 ◽  
Author(s):  
Kaihua Guo ◽  
Mingfu Guan ◽  
Dapeng Yu
Keyword(s):  
Surface Water ◽  
Urban Areas ◽  
Scale Effects ◽  
Water Flooding ◽  
Urban Surface ◽  
Economic Losses ◽  
Intense Rainfall ◽  
Urban Flood ◽  
Comprehensive Review ◽  
Flood Modelling

Abstract. Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.

scholarly journals Assessment of Community Vulnerability to Different Types of Urban Floods: A Case for Lishui City, China

2020 ◽  
Vol 12 (19) ◽  
pp. 7865 ◽  
Author(s):  
Quntao Yang ◽  
Shuliang Zhang ◽  
Qiang Dai ◽  
Rui Yao
Keyword(s):  
Urban Areas ◽  
Flood Hazard ◽  
Urban Flooding ◽  
Urban Floods ◽  
Flood Vulnerability ◽  
Urban Flood ◽  
Indicator Method ◽  
Comprehensive Method ◽  
Different Types ◽  
Hydrometeorological Conditions

Urban flooding is a severe and pervasive hazard caused by climate change, urbanization, and limitations of municipal drainage systems. Cities face risks from different types of floods, depending on various geographical, environmental, and hydrometeorological conditions. In response to the growing threat of urban flooding, a better understanding of urban flood vulnerability is needed. In this study, a comprehensive method was developed to evaluate the vulnerability of different types of urban floods. First, a coupled urban flood model was built to obtain the extent of influence of various flood scenarios caused by rainfall and river levee overtopping. Second, an assessment framework for urban flood vulnerability based on an indicator method was used to evaluate the vulnerability in different flood hazard scenarios. Finally, the method was applied to Lishui City, China, and the distribution and pattern of urban flood vulnerability were studied. The results highlight the spatial variability of flooding and the vulnerability distributions of different types of urban floods. Compound floods were identified to cause more severe effects in the urban areas.

scholarly journals Urban surface water flood modelling – a comprehensive review of current models and future challenges

2021 ◽  
Vol 25 (5) ◽  
pp. 2843-2860
Author(s):  
Kaihua Guo ◽  
Mingfu Guan ◽  
Dapeng Yu
Keyword(s):  
Surface Water ◽  
Urban Areas ◽  
Scale Effects ◽  
Water Flooding ◽  
Urban Surface ◽  
Economic Losses ◽  
Intense Rainfall ◽  
Urban Flood ◽  
Comprehensive Review ◽  
Flood Modelling

Abstract. Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses, are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances, and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.

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 Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding

2017 ◽  
Vol 17 (2) ◽  
pp. 205-224 ◽  
Author(s):  
Joanne Comer ◽  
Agnieszka Indiana Olbert ◽  
Stephen Nash ◽  
Michael Hartnett
Keyword(s):  
Moving Boundary ◽  
Flood Hazard ◽  
Hazard Identification ◽  
Water Levels ◽  
Urban Flooding ◽  
Coastal Zones ◽  
Urban Flood ◽  
Multi Scale ◽  
Scale Modelling ◽  
Modelling System

Abstract. Urban developments in coastal zones are often exposed to natural hazards such as flooding. In this research, a state-of-the-art, multi-scale nested flood (MSN_Flood) model is applied to simulate complex coastal-fluvial urban flooding due to combined effects of tides, surges and river discharges. Cork city on Ireland's southwest coast is a study case. The flood modelling system comprises a cascade of four dynamically linked models that resolve the hydrodynamics of Cork Harbour and/or its sub-region at four scales: 90, 30, 6 and 2 m. Results demonstrate that the internalization of the nested boundary through the use of ghost cells combined with a tailored adaptive interpolation technique creates a highly dynamic moving boundary that permits flooding and drying of the nested boundary. This novel feature of MSN_Flood provides a high degree of choice regarding the location of the boundaries to the nested domain and therefore flexibility in model application. The nested MSN_Flood model through dynamic downscaling facilitates significant improvements in accuracy of model output without incurring the computational expense of high spatial resolution over the entire model domain. The urban flood model provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.

scholarly journals Methodologies to study the surface hydraulic behaviour of urban catchments during storm events

2011 ◽  
Vol 63 (11) ◽  
pp. 2666-2673 ◽  
Author(s):  
M. Gómez ◽  
F. Macchione ◽  
B. Russo
Keyword(s):  
Urban Areas ◽  
Flood Hazard ◽  
Spatial Density ◽  
Hydraulic Efficiency ◽  
Storm Events ◽  
Accurate Analysis ◽  
Numerical Application ◽  
Urban Flood ◽  
Hydraulic Behaviour ◽  
Urban Catchments

A good knowledge of the hydraulic behaviour of an urban catchment and its surface drainage system is an essential requirement to guarantee traffic and pedestrian safety. In many cases, inlets have been situated according to spatial density criteria. Indeed a more rational location of inlets on urban catchments must be defined according to an accurate analysis of the relationship between street flow and inlet hydraulic efficiency. Moreover we lack specific hazard criteria in terms of the maximum acceptable flow depths and velocities on the streets that do not cause problems to pedestrians. In this paper the results of two different experimental campaigns are presented. The first was carried out to evaluate inlet hydraulic efficiency; the second was carried out to address the pedestrian stability in urban flood conditions, whose aim was to propose new hazard criteria. On the basis of the experimental results, a methodology was developed to assess flood hazard in urban areas during storm events. If a refined topographic representation of urban areas is available, a two-dimensional numerical simulation of urban flooding can be performed using complete shallow water equations. According to this approach a numerical application for flood hazard assessment in a street of Barcelona is shown.

scholarly journals An Exploratory Optimal Framework of Low Impact Development Measures Spatial Arrangement based on Source Tracking for Urban Flood Mitigation

2021 ◽  
Author(s):  
Wenchao Qi ◽  
Chao Ma ◽  
Hongshi Xu ◽  
Zifan Chen ◽  
Kai Zhao ◽  
...  
Keyword(s):  
Urban Areas ◽  
Flood Hazard ◽  
Low Impact Development ◽  
Spatial Arrangement ◽  
Source Tracking ◽  
Urban Flood ◽  
Tracking Method ◽  
Source Areas ◽  
Optimization Framework ◽  
Flood Source

Abstract Urban areas are vulnerable to flooding as a result of climate change and population growth and thus rainstorm-induced flood losses are becoming increasingly severe. Low impact development (LID) measures are a storm management technique designed for controlling runoff in urban areas, which is critical for solving urban flood hazard. Therefore, this study developed an exploratory simulation-optimization framework for the spatial arrangement of LID measures. The proposed framework begins by applying a numerical model to simulate hydrological and hydrodynamic processes during a storm event, and the urban flood model coupled with the source tracking method was then used to identify the flood source areas. Next, based on source tracking data, the LID investment in each subcatchment was determined using the inundation volume contribution ratio of the flood source area (where most of the investment is required) to the flood hazard area (where most of the flooding occurs). Finally, the resiliency and sustainability of different LID scenarios were evaluated using several different storm events in order to provide suggestions for flooding predictions and the decision-making process. The results of this study emphasized the importance of flood source control. Furthermore, to quantitatively evaluate the impact of inundation volume transport between subcatchments on the effectiveness of LID measures, a regional relevance index (RI) was proposed to analyze the spatial connectivity between different regions. The simulation-optimization framework was applied to Haikou City, China, wherein the results indicated that LID measures in a spatial arrangement based on the source tracking method are a robust and resilient solution to flood mitigation. This study demonstrates the novelty of combining the source tracking method and highlights the spatial connectivity between flood source areas and flood hazard areas. Further, the framework acts as a strategic tool for the effective spatial arrangement design of LID measures.

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. 

Reviewing operational and near operational progress in surface water flood forecasting for urban areas

2020 ◽  
Author(s):  
Linda Speight ◽  
Michael Cranston ◽  
Laura Kelly ◽  
Christopher White
Keyword(s):  
Surface Water ◽  
Urban Areas ◽  
Prediction Models ◽  
Rapid Development ◽  
Weather Prediction ◽  
Flood Forecasting ◽  
Water Flooding ◽  
Environment Protection ◽  
Probabilistic Forecasting ◽  
Protection Agency

<p>Surface water flooding is caused by intense rainfall before it enters rivers or drainage systems. As the climate changes and urban populations grow, the number of people around the world at risk of surface water flooding increases. Although it may not be possible to prevent such flooding, reliable and timely flood forecasts can help improve preparedness and recovery. Unlike river and coastal flooding where flood forecasting methods are well established, surface water forecasting techniques that address the challenges around predicting the location, timing and impact of events are still in their infancy.</p><p>Over the past five years there has been a rapid development of convection permitting numerical weather prediction models and probabilistic forecasting. Combined with an increase in computational ability, this has meant that it is potentially feasible to develop operational surface water forecasting systems for urban areas. The ability to make flood risk management decisions based on such forecasts depends on an interdisciplinary understanding of their strengths and limitations.</p><p>In 2019, the Scottish Environment Protection Agency (SEPA) commissioned a systematic review of UK and international surface water forecasting capabilities to inform the development of forecasting capabilities for Scotland (Speight et al, 2019). As part of the review process a literature review of international examples of operational surface water forecasting tools was conducted alongside discussion with a number of industry experts and leading academics to incorporate emerging capabilities.</p><p>This PICO will summarise the three approaches to surface water forecasting identified as part of this review; empirical based rainfall scenarios, hydrological forecasts linked to pre-simulated impact scenarios, and, real time hydrodynamic simulation. International examples of each type of approach will be presented along with discussion of their ability to meet the varying needs of decision makers. It will conclude by identifying ‘grand interdisciplinary challenges’ that still need to be addressed to provide effective solutions for reliable and timely surface water forecasts. For example although the emergence of new meteorological and hydrological capabilities is promising there is a scientific limit to the predictability of convective rainfall. To overcome this challenge re-thinking of the established role of flood forecasting is needed alongside developing interdisciplinary solutions for communicating uncertainty, making the best use of all available data and increasing preparedness.</p><p> </p><p><em>Speight, L., Cranston, M., Kelly, L. and White, C.J. (2019) Towards improved surface water flood forecasts for Scotland: A review of UK and international operational and emerging capabilities for the Scottish Environment Protection Agency. University of Strathclyde, Glasgow, pp 1-63, doi:10.17868/69416 Available online at https://strathprints.strath.ac.uk/69416/</em></p>

Implementation of Low Impact Development Concept for New Town Construction in the Republic of Korea

2013 ◽  
Vol 742 ◽  
pp. 30-33 ◽  
Author(s):  
Ree Ho Kim ◽  
Jung Hun Lee ◽  
Mik Yeong Kim ◽  
Hyun Dong Lee
Keyword(s):  
Urban Areas ◽  
Hydrological Cycle ◽  
Low Impact Development ◽  
Development Planning ◽  
Ecosystem Functions ◽  
Natural Ecosystem ◽  
Urban Flood ◽  
Flow Control Devices ◽  
The Republic ◽  
Storm Drain

New approach in stormwater management is urgent to address those water related problems and supplement the limitations of existed water management system. It should have functions to restore water and heat cycles in urban areas, that is, to restore hydrological cycle by promoting infiltration and evaporation, to secure water resources, to alleviate heat island phenomena, to prevent urban flood, and to conserve and restore the ecosystem. LID practices are one of prominent measures to mitigate the impacts of development and urbanization. It is important to have a LID approach in the step of site development planning. LID facilities could be categorized as flow control devices, detention, retention, vegetated filtration, infiltration and treatment. LID emphasizes local, decentralized solutions that capitalize on the beneficial services that natural ecosystem functions can provide. LID also focuses on controlling urban runoff and pollution right at the source, rather than at the end of the storm drain outlet. Since there are many different aspects of LID approach, the policy to promote or regulate LID should consider water, energy and ecology conservation.

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