Analysis of Effect of Rainfall Patterns on Urban Flood Process by Coupled Hydrological and Hydrodynamic Modeling

Cheng, Tao; Xu, Zongxue; Yang, Hong; Hong, Siyang; Leitão, João P.

doi:10.1061/(asce)he.1943-5584.0001867

Cited by 36 publications

(11 citation statements)

References 23 publications

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“…Moreover, a short-term rainstorm is more likely to inundate cities. Li et al [ 49 ] and Cheng et al [ 50 ] reached a similar conclusion in their study of urban inundation. However, compared with them, we clearly and intuitively showed the impact of different factors on inundation through the presentation of data and details.…”

Section: Discussionsupporting

confidence: 59%

Urban Inundation under Different Rainstorm Scenarios in Lin’an City, China

Chen

Hou

et al. 2022

IJERPH

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Under the circumstances of global warming and rapid urbanization, damage caused by urban inundation are becoming increasingly severe, attracting the attention of both researchers and governors. The accurate simulation of urban inundation is essential for the prevention of inundation hazards. In this study, a 1D pipe network and a 2D urban inundation coupling model constructed by InfoWorks ICM was used to simulate the inundation conditions in the typical urbanized area in the north of Lin’an. Two historical rainfall events in 2020 were utilized to verify the modeling results. The spatial–temporal variation and the causes of urban inundation under different designed rainfalls were studied. The results were as follows: (1) The constructed model had a good simulation accuracy, the Nash–Sutcliffe efficiency coefficient was higher than 0.82, R2 was higher than 0.87, and the relative error was ±20%. (2) The simulation results of different designed rainfall scenarios indicated that the maximum inundation depth and inundation extent increased with the increase in the return period, rainfall peak position coefficient, and rainfall duration. According to the analysis results, the urban inundation in Lin’an is mainly affected by topography, drainage network (spatial distribution and pipe diameter), and rainfall patterns. The results are supposed to provide technical support and a decision-making reference for the urban management department of Lin’an to design inundation prevention measures.

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Section: Discussionsupporting

confidence: 59%

Urban Inundation under Different Rainstorm Scenarios in Lin’an City, China

Chen

Hou

et al. 2022

IJERPH

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“…Rainfall is a main and important component of the flood prediction model. The greater the amount and intensity of rainfall, the greater the risk of flooding (Cheng et al, 2020). Rainfall data related to meteorological stations in and around the study area were received from the National Meteorological Organization.…”

Section: Flood Inventory Mapmentioning

confidence: 99%

Comparison of hydrological modeling, Artificial Neural Networks and multi-criteria decision making approaches for determining Flood Source Areas

Azari,

Mahmoodi,

Dastorani

et al. 2024

Preprint

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Flood risk management is a critical task which necessitates flood forecasting and identifying flood source areas for implementation of prevention measures in a basin. Hydrological models, multi-criteria decision models (MCDM) and data-driven models such as Artificial Neural Networks (ANN) have been used for identifying flood source areas within a watershed. The aim of this study is comparing the results of hydrological modeling, MCDM and ANN approaches in order to identify and prioritize flood source areas. The study results show that the classification results of the hydrological model and the artificial neural network have a significant correlation; also the correlation between the TOPSIS method with the hydrological model (0.252) and the artificial neural network (0.233) indicates that none of the sub-basins in the Very high, High and Very low classes are similar in the above methods. Since the neural network model has simulated the HEC-HMS classifications very accurately, it can be concluded that this model has performed very well as compared to the TOPSIS multi-criteria decision-making method.

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“…Simulations were performed with a 1D/2D coupled model that was created using the software Infoworks ICM by Innovyze [37] and was already applied in earlier studies of urban floods [38,39] The model combines a 1D model of the sub-surface network with a 2D model of the overland surface network and also simulates the interaction between both networks (1D/2D linkage).…”

Section: Numerical Modelmentioning

confidence: 99%

Effectiveness of Nature-Based Solutions on Pluvial Flood Hazard Mitigation: The Case Study of the City of Eindhoven (The Netherlands)

Costa

Peters²,

Martins

et al. 2021

Resources

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Urbanization leads to changes in the surface cover that alter the hydrological cycle of cities, particularly by increasing the impervious area and, thereby, reducing the interception, storage and infiltration capacity of rainwater. Nature-based solutions (NBS) can contribute to flood risk mitigation in urbanized areas by restoring hydrological functions. However, the effects of NBS on flood risk mitigation are complex and can differ substantially with the type of the NBS. Therefore, the effectiveness of NBS at the urban catchment scale is still subject to much debate, especially at the scale of urban catchments. In this study, the effects of different NBS on urban flood mitigation were evaluated for the city of Eindhoven in The Netherlands, as it has a history of urban flood events. To this end, various NBS scenarios were defined by municipal stakeholders and their impacts modelled with the numerical model Infoworks ICM. This was done for design storms with short, medium and long return periods (5, 10 and 100 years). Overall, the simulated NBS were effective in flood risk mitigation, reducing the flooded area as well as flood depth. The effectiveness of the individual NBS scenarios, however, depended strongly on the location and extension of the NBS, as well as on storm intensity. The effectiveness tended to increase with the increase in NBS surface area, while it tended to decrease with increasing storm intensity and, hence, return period. The NBS solution increasing street water storage was revealed to be more effective than those involving green car parks and green roofs. This study showed that numerical flooding models can be useful tools to assess the effects of NBS to reduce flood extent, water depth and/or velocity, providing insights that can support city planners to design and compare alternative strategies and plans for urban flood risk mitigation.

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Analysis of Effect of Rainfall Patterns on Urban Flood Process by Coupled Hydrological and Hydrodynamic Modeling

Cited by 36 publications

References 23 publications

Urban Inundation under Different Rainstorm Scenarios in Lin’an City, China

Urban Inundation under Different Rainstorm Scenarios in Lin’an City, China

Comparison of hydrological modeling, Artificial Neural Networks and multi-criteria decision making approaches for determining Flood Source Areas

Effectiveness of Nature-Based Solutions on Pluvial Flood Hazard Mitigation: The Case Study of the City of Eindhoven (The Netherlands)

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