Building hazard maps with differentiated risk  perception for flood impact assessment

Bhola, Punit Kumar; Leandro, Jorge; Disse, Markus

doi:10.5194/nhess-20-2647-2020

Cited by 15 publications

(8 citation statements)

References 56 publications

(77 reference statements)

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“…Years of economic development and infrastructural assets are washed off with every flooding event, particularly in the developing countries of Southeast Asia, such as India, Pakistan, and Bangladesh [59][60][61][62][63]. The difference between the developed and developing worlds in the case of managing floods lies in their complex differential socioeconomic setups [64][65][66][67][68]. Moreover, many disasters are localized in nature having a lesser spatial extent of the damage.…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Resultsmentioning

confidence: 99%

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

et al. 2021

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“…One-dimensional hydrodynamic simulation can competently identify the river risks, but the impacts of embankment b reach is ignored. The river flood will spread along the breach and inundate the depressions in the basin [47]. Thus, this paper further couples the one-dimension and two-dimension models by using the Mike Flood model to analyze the dynamic flood process using indicators with submerged depth, submerged area and arrival time, and identify the risk in the watershed.…”

Section: Processes and Risks Of Flood In River Under Exceeding Contro...mentioning

confidence: 99%

“…River flood evolution can be described by a one-dimensional hydrodynamic model, and flood evolution in the floodplain can be simulated by a two-dimensional hydrodynamic model. After obtaining the flood process by simulation, the flood arrival time, submerged area, submerged depth, people, road network, socio-economic and other key elements are imported into GIS to describe the flood risk and generate the contingency plan [47,48].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Small and Medium–Scale River Flood Risk in Case of Exceeding Control Standard Floods Using Hydraulic Model

Wang

Sun

et al. 2021

Water

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Exceeding control standard floods pose threats to the management of small and medium–scale rivers. Taking Fuzhouhe river as an example, this paper analyzes the submerged depth, submerged area and arrival time of river flood risk in the case of exceeding control standard floods (with return period of 20, 50, 100 and 200 years) through a coupled one– and two–dimensional hydrodynamic model, draws the flood risk maps and proposes emergency plans. The simulation results of the one–dimensional model reveal that the dikes would be at risk of overflowing for different frequencies of floods, with a higher level of risk on the left bank. The results of the coupled model demonstrate that under all scenarios, the inundation area gradually increases with time until the flood peak subsides, and the larger the flood peak, the faster the inundation area increases. The maximum submerged areas are 42.73 km2, 65.95 km2, 74.86 km2 and 82.71 km2 for four frequencies of flood, respectively. The change of submerged depth under different frequency floods shows a downward–upward–downward trend and the average submerged depth of each frequency floods is about 1.4 m. The flood risk maps of different flood frequencies are created by GIS to analyze flood arrival time, submerged area and submerged depth to plan escape routes and resettlement units. The migration distances are limited within 4 km, the average migration distance is about 2 km, the vehicle evacuation time is less than 20 min, and the walking evacuation time is set to about 70 min. It is concluded that the flood risk of small and medium–scale rivers is a dynamic change process, and dynamic flood assessment, flood warning and embankment modification scheme should be further explored.

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“…Other authors considered additional uncertainties in flood hazard by including extreme value statistics [19][20][21], in many cases, by relating the changes in rainfall or flow results that may occur as a result of climate change (e.g., [22][23][24][25][26]). The importance of an uncertainty analysis in flood risk management was pointed out previously [7,27] in order to understand the implications for decision makers of limited data availability, model uncertainties, or other uncertainty sources. Monte Carlo simulations (MC) as a technique to reduce uncertainty in flood hazard analyses have been widely used.…”

Section: Introductionmentioning

confidence: 99%

“…Monte Carlo simulations (MC) as a technique to reduce uncertainty in flood hazard analyses have been widely used. Previous studies have used MC methods (e.g., [15,17,19,[27][28][29]) to analyse all variables: surface roughness, boundary conditions, and return period as flow frequency variable.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Flood Hazard Maps from Monte Carlo Derived Peak Flow Values—An Application to Flood Risk Management in Zamora City (Spain)

2021

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All flood hazard and risk assessment suffer from a certain degree of uncertainty due to multiple factors, such as flood frequency analysis, hydrodynamic model calibration, or flood damage (magnitude–damage functions) models. The uncertainty linked to the flood frequency analysis is one of the most important factors (previous and present estimation point to 40%). Flood frequency analysis uncertainty has been approached from different points of view, such as the application of complex statistical models, the regionalization processes of peak flows, or the inclusion of non-systematic data. Here, we present an achievable approach to defining the uncertainty linked to flood frequency analysis by using the Monte Carlo method. Using the city of Zamora as the study site, the uncertainty is delimited by confidence intervals of a peak flow quantile of a 500-year return period. Probabilistic maps are derived from hydrodynamic results, and further analysis include flood hazard maps for human loss of stability and vehicle damage. Although the effect of this uncertainty is conditioned by the shape of the terrain, the results obtained may allow managers to achieve more consistent land-use planning. All those Zamora city results point out the probable underestimation of flood hazard (the higher hazard areas increase around 20%) and risk when the uncertainty analysis is not considered, thus limiting the efficiency of flood risk management tasks.

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Building hazard maps with differentiated risk perception for flood impact assessment

Cited by 15 publications

References 56 publications

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

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

Analysis of Small and Medium–Scale River Flood Risk in Case of Exceeding Control Standard Floods Using Hydraulic Model

Probabilistic Flood Hazard Maps from Monte Carlo Derived Peak Flow Values—An Application to Flood Risk Management in Zamora City (Spain)

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