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 Improved Framework for Assessing Vulnerability to Different Types of Urban Floods

2020 ◽  
Vol 12 (18) ◽  
pp. 7668
Author(s):  
Quntao Yang ◽  
Shuliang Zhang ◽  
Qiang Dai ◽  
Rui Yao
Keyword(s):  
Land Use ◽  
Vulnerability Assessment ◽  
Network Flow ◽  
Urban Flooding ◽  
Flood Vulnerability ◽  
Urban Flood ◽  
Vulnerability Curve ◽  
Storm Water Management Model ◽  
Different Types ◽  
The Impact

Vulnerability assessment is an essential tool in mitigating the impact of urban flooding. To date, most flood vulnerability research has focused on one type of flood, such as a pluvial or fluvial flood. However, cities can suffer from urban flooding for several reasons, such as precipitation and river levee overtopping. Therefore, a vulnerability assessment considering different types of floods (pluvial floods, fluvial floods, and compound flooding induced by both rainfall and river overtopping) was conducted in this study. First, a coupled urban flood model, considering both overland and sewer network flow, was developed using the storm water management model (SWMM) and LISFLOOD-FP model to simulate the different types of flood and applied to Lishui, China. Then, the results of the flood modeling were combined with a vulnerability curve to obtain the potential impact of flooding on different land-use classes. The results indicated that different types of floods could have different influence areas and result in various degrees of flood vulnerability for different land-use classes. The results also suggest that urban flood vulnerability can be underestimated due to a lack of consideration of the full flood-induced factors.

scholarly journals Climate Justice Planning in Global South: Applying a Coupled Nature–Human Flood Risk Assessment Framework in a Case for Ho Chi Minh City, Vietnam

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2021
Author(s):  
Chen-Fa Wu ◽  
Szu-Hung Chen ◽  
Ching-Wen Cheng ◽  
Luu Van Thong Trac
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Climate Justice ◽  
Ho Chi Minh City ◽  
Flood Risk Assessment ◽  
Urban Floods ◽  
Flood Vulnerability ◽  
Urban Flood ◽  
Vulnerability Map ◽  
The City

Developing countries in the global south that contribute less to climate change have suffered greater from its impacts, such as extreme climatic events and disasters compared to developed countries, causing climate justice concerns globally. Ho Chi Minh City has experienced increased intensity and frequency of climate change-induced urban floods, causing socio-economic damage that disturbs their livelihoods while urban populations continue to grow. This study aims to establish a citywide flood risk map to inform risk management in the city and address climate justice locally. This study applied a flood risk assessment framework integrating a coupled nature–human approach and examined the spatial distribution of urban flood hazard and urban flood vulnerability. A flood hazard map was generated using selected morphological and hydro-meteorological indicators. A flood vulnerability map was generated based on a literature review and a social survey weighed by experts’ priorities using the Fuzzy Delphi Method and Analytic Network Process. Vulnerability indicators including demographic characteristics, infrastructure, and land use patterns were used to generate a flood vulnerability map. The results illustrate that almost the entire central and northeastern parts of the city are at high flood risk, whereas the western part is at low flood risk. The findings have implications in urban planning via identifying risk hot spots in order to prioritize resources for mitigating hazards and enhancing community resilience to urban floods.

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 1D-2D MODELING OF URBAN FLOODS AND RISK MAP GENERATION FOR THE PART OF HYDERABAD CITY

2018 ◽  
Vol XLII-5 ◽  
pp. 445-450 ◽  
Author(s):  
V. A. Rangari ◽  
R. Gonugunta ◽  
N. V. Umamahesh ◽  
A. K. Patel ◽  
C. M. Bhatt
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Extreme Rainfall ◽  
Storm Water ◽  
Urban Flooding ◽  
Flood Inundation ◽  
Urban Floods ◽  
Urban Flood ◽  
Extreme Flood ◽  
Risk Maps

<p><strong>Abstract.</strong> Space for water is now becoming guiding principle of urban planning because urban flooding is the major problem facing by most of the cities in India. Urban development in developing countries like India usually occurs with high population concentrating in small areas, with poor drainage conditions. People occupy floodplain areas in low flood years and when larger flood occurs it causes high damage. The origin for urban floods is floodplains encroachment and unplanned drainage systems. Complexities in the urban environment and drainage infrastructure have an inherent influence on surface runoff. This runoff generates urban flooding which poses challenges to modeling urban flood hazard and risk. As like in river flooding satellite images are not available for unban flooding scenario. So better modelling provides minimizing loss of life and property. The present study focuses on recognizing the highly effected areas which are liable to flooding when extreme rainfall occurs for part of Hyderabad city (Zone XIII). The entire Hyderabad city is divided into 16 zones and each zone having details of existing drain network. A coupled 1D-2D flood modelling approach is used to identify flood prone areas and develop flood inundation and flood risk maps. 1D model for pilot area is developed using storm water management model (SWMM) and coupled with 2D PCSWMM. A web based GIS platform INPPINS is used to geo reference the existing network details and exported to 1D SWMM model. The model is simulated for extreme flood event occurred in past. The simulation run results identifies overflowing drainage nodes and flood inundation maps and risk maps prepared. The flood risk maps identify the low lying areas which need immediate attention in case of emergency. The overflowing nodes suggest the need of improvement of drainage in the area to safely dispose of the storm water and minimize the flooding.</p>

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.

One-dimensional modelling of the interactions between heavy rainfall-runoff in an urban area and flooding flows from sewer networks and rivers

2009 ◽  
Vol 60 (4) ◽  
pp. 927-934 ◽  
Author(s):  
G. Lipeme Kouyi ◽  
D. Fraisse ◽  
N. Rivière ◽  
V. Guinot ◽  
B. Chocat
Keyword(s):  
Urban Areas ◽  
Heavy Rainfall ◽  
Original Method ◽  
Urban Flooding ◽  
Rainfall Runoff ◽  
Urban Floods ◽  
One Dimensional ◽  
Overland Flows ◽  
Variable Water ◽  
Sewer Networks

Many investigations have been carried out in order to develop models which allow the linking of complex physical processes involved in urban flooding. The modelling of the interactions between overland flows on streets and flooding flows from rivers and sewer networks is one of the main objectives of recent and current research programs in hydraulics and urban hydrology. This paper outlines the original one-dimensional linking of heavy rainfall-runoff in urban areas and flooding flows from rivers and sewer networks under the RIVES project framework (Estimation of Scenario and Risks of Urban Floods). The first part of the paper highlights the capacity of Canoe software to simulate the street flows. In the second part, we show the original method of connection which enables the modelling of interactions between processes in urban flooding. Comparisons between simulated results and the results of Despotovic et al. or Gomez & Mur show a good agreement for the calibrated one-dimensional connection model. The connection operates likes a manhole with the orifice/weir coefficients used as calibration parameters. The influence of flooding flows from river was taken into account as a variable water depth boundary condition.

scholarly journals GIS-Based Urban Flood Risk Assessment and Management—A Case Study of Delhi National Capital Territory (NCT), India

2021 ◽  
Vol 13 (22) ◽  
pp. 12850
Author(s):  
Pallavi Tomar ◽  
Suraj Kumar Singh ◽  
Shruti Kanga ◽  
Gowhar Meraj ◽  
Nikola Kranjčić ◽  
...  
Keyword(s):  
Urban Areas ◽  
Field Survey ◽  
Drainage System ◽  
Yamuna River ◽  
Urban Centers ◽  
Urban Floods ◽  
Urban Flood ◽  
National Capital ◽  
Risk Assessment And Management

Urban floods are very destructive and have significant socioeconomic repercussions in regions with a common flooding prevalence. Various researchers have laid down numerous approaches for analyzing the evolution of floods and their consequences. One primary goal of such approaches is to identify the areas vulnerable to floods for risk reduction and management purposes. The present paper proposes an integrated remote sensing, geographic information system (GIS), and field survey-based approach for identifying and predicting urban flood-prone areas. The work is unique in theory since the methodology proposed finds application in urban areas wherein the cause of flooding, in addition to heavy rainfall, is also the inefficient urban drainage system. The work has been carried out in Delhi’s Yamuna River National Capital Territory (NCT) area, considered one of India’s most frequently flooded urban centers, to analyze the causes of its flooding and supplement the existing forecasting models. Research is based on an integrated strategy to evaluate and map the highest flood boundary and identify the area affected along the Yamuna River NCT of Delhi. In addition to understanding the causal factors behind frequent flooding in the area, using field-based information, we developed a GIS model to help authorities to manage the floods using catchment precipitation and gauge level relationship. The identification of areas susceptible to floods shall act as an early warning tool to safeguard life and property and help authorities plan in advance for the eventuality of such an event in the study area.

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.

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