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Water
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Urban Flood Frequency Analysis and Risk Assessment
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Urban Flood Frequency Analysis and Risk Assessment

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 25 December 2024 | Viewed by 2949

Special Issue Editors

Dr. Khaled Haddad

E-Mail Website
Guest Editor
School of Engineering, Design and Built Environment, Penrith Campus, Western Sydney University, Building XB, Kingswood, NSW 2751, Australia
Interests: hydrology; floods; statistical methods; environmental modeling; education
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ataur Rahman

E-Mail Website
Guest Editor
Core Member, Renewable Energy and Water Research Group (Sustainability and Resilience Theme), School of Engineering, Design and Built Environment, Western Sydney University, Penrith, Australia
Interests: water and environmental engineering; hydrology; climate change impacts; floods; water-sensitive urban design; rainwater harvesting; engineering education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on flood estimation in catchments using flood frequency analysis and different modelling methods.

Flood frequency analysis (FFA) is often adopted to estimate design floods, which are needed for many water resource management tasks, e.g., to size hydraulic structures and to carry out flood risk and ecology assessments, as well as flood insurance studies. Therefore, FFA remains an active area of interest and research. The most direct method of design flood estimation is at-site FFA analysis, which relies on a relatively long period of recorded streamflow data at a given site. Hence, the selection of an appropriate probability distribution-associated parameter estimation procedure, accounting for climate change and uncertainty is of prime importance in at-site FFA. With recent advancements in statistical and computational modelling and computing facilities, FFA estimates can be assessed more reliably and efficiently.

We invite original research articles that contribute to the continuing efforts to understand hydrological data and the complex hydrological processes that they exhibit to study furthermore reliable FFA estimates. This Special Issue also welcomes manuscripts on uncertainty analysis in FFA and the application of flood modelling to support decision making.

Potential topics for this Special Issue include, but are not limited to, the following:

  • Flood frequency analysis: advances in methods, regional case studies, variability, and trend analysis.
  • Annual maximum and peaks-over-threshold flood frequency analysis.
  • Impacts of climate change on flood frequency analysis: stationary vs. non-stationary flood frequency analysis.
  • Uncertainty in flood frequency analysis.
  • Impact of rating curve errors on flood frequency analysis.
  • Impact of distributional assumptions, parameter estimates, record lengths, and outliers on flood frequency analysis.
  • Bayesian methods and Monte Carlo simulation in flood frequency analysis.
  • Goodness-of-fit methods for flood frequency analysis.
  • Bivariate flood frequency analysis using copulas.
  • Historical and paleohydrologic information in flood frequency analysis.
  • Entropy-based flood frequency analysis.
  • Urbanization effects on flood frequency analysis.
  • Insights and lessons learnt from streamflow data preparation for flood frequency analysis.
  • Regional flood frequency analysis including and not limited to linear and nonlinear modelling approaches.

Dr. Khaled Haddad
Prof. Dr. Ataur Rahman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • flood frequency analysis
  • Bayesian
  • regional flood frequency analysis
  • distributions
  • uncertainty
  • modelling
  • annual maximum data
  • peaks-over-threshold data

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Published Papers (4 papers)

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Research

14 pages, 2303 KiB  
Article
Decomposing Future Exposure from Increasing Flood Risk and Forecast Population Changes Across Shared Socioeconomic Pathways (SSPs) in the United States
by Jeremy R. Porter, Evelyn G. Shu, Matthew Hauer, Zachary M. Hirsch and Jasmina Buresch
Water 2024, 16(22), 3289; https://doi.org/10.3390/w16223289 - 16 Nov 2024
Viewed by 576
Abstract
Extreme weather events, like flooding, are expected to become more severe due to climate change and increasingly impact populations across the US. Adding to this challenge, populations have concurrently settled in risky areas that were previously thought to have low, or no, exposure. [...] Read more.
Extreme weather events, like flooding, are expected to become more severe due to climate change and increasingly impact populations across the US. Adding to this challenge, populations have concurrently settled in risky areas that were previously thought to have low, or no, exposure. Objective: This research seeks to understand the unique contribution of population growth and climate change as independent components of future risk levels in the US. To do so, future population level forecasts are coupled with future flood projections along all five Shared Socioeconomic Pathways (SSPs) at the block group level across the US. The results indicate that, across the five SSPs, the most increase in exposure will occur in SSP5 (+470,719), and the least will occur in SSP 3 (+57,189). By decomposing the contributions from flood and population growth, we find that the population growth-induced effect contributed to an increase in the population exposure for all of the SSPs except for SSP3. This research, and these results, provide a foundation for understanding future risks of flood exposure in an isolated framework and lay the groundwork for the development and integration of planning, adaptation, and mitigation efforts that may be used to address the growing risk of flooding in the context of the population forecasts provided here. Full article
(This article belongs to the Special Issue Urban Flood Frequency Analysis and Risk Assessment)
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13 pages, 8412 KiB  
Article
Grain Size in an Alpine Lake from the Chinese Loess Plateau: Implications for Paleofloods and East Asian Summer Monsoon Variability
by Chao Zhang, Keke Yu, Aizhen Li, Tianao Li and Suyue Xin
Water 2024, 16(21), 3129; https://doi.org/10.3390/w16213129 - 1 Nov 2024
Viewed by 536
Abstract
Reliable paleoflood proxies can help reconstruct past flood variation patterns. Here, we investigated the grain-size data of a 63 cm core retrieved from Lake Chaonaqiu, western Chinese Loess Plateau, in order to build a long time-series of flood occurrence from sedimentology that extends [...] Read more.
Reliable paleoflood proxies can help reconstruct past flood variation patterns. Here, we investigated the grain-size data of a 63 cm core retrieved from Lake Chaonaqiu, western Chinese Loess Plateau, in order to build a long time-series of flood occurrence from sedimentology that extends the period of instrumental data. Our results indicate that three parameters (mean, standard deviation and grain-size ratio of 16–63/2–16 μm) are sensitive to hydrodynamic changes in Lake Chaonaqiu, which are further linked to high-energy inflow associated with high-intensity rainfall or flood events. These three parameters’ variations were well correlated with the precipitation records reconstructed from tree-rings and historical documents in neighboring regions and overlapped with 109 historical flood events from historical documents in counties around the lake for the past 300 years. Therefore, we propose that the grain size in the sediments of Lake Chaonaqiu is a reliable paleoflood proxy. The sensitivity of flood signals to grain size may be related to the precipitation and vegetation cover in the catchment of the lake, which are further linked to the strength of the East Asian summer monsoon. Full article
(This article belongs to the Special Issue Urban Flood Frequency Analysis and Risk Assessment)
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22 pages, 9161 KiB  
Article
Modeling Three-Dimensional Exfiltration Rates from Permeable Street Stormwater Inlets as One-Dimensional Water Flux in Urban Hydrological Models
by Ryuga Iinuma, Shigeki Harada and Nana Yamauchi
Water 2024, 16(21), 3076; https://doi.org/10.3390/w16213076 - 27 Oct 2024
Viewed by 643
Abstract
Climate change has increased the intensity and frequency of weather systems, increasing the risk of inundation in urban areas. To mitigate these risks, not only rivers but also entire catchments need to be managed, and the use of infiltration and retention units needs [...] Read more.
Climate change has increased the intensity and frequency of weather systems, increasing the risk of inundation in urban areas. To mitigate these risks, not only rivers but also entire catchments need to be managed, and the use of infiltration and retention units needs to be expanded. The ability to evaluate the effects of promoting infiltration and retention in catchments using distributed hydrological models, clarify the three-dimensional behavior of exfiltration from catchments into natural base soils, and parameterize this flow as a one-dimensional hypothetical water flux is essential. Using VGFlow2D (Forum8) and field observations, numerical analyses were conducted to parametrize the flux and assess the features of q/Ks values, representing the volume of three-dimensional water exfiltration from stormwater inlet bases into natural soils relative to the saturated hydraulic conductivity (Ks) of the soils. The findings were integrated into the hydrological model Infoworks ICM (Innovyze) by adding a single parameter, the “exfiltration loss rate”, to each inlet without increasing computational demands. The obtained q/Ks values were compared to previously reported values, and variations were evaluated using infiltration theory. Full article
(This article belongs to the Special Issue Urban Flood Frequency Analysis and Risk Assessment)
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20 pages, 22795 KiB  
Article
Runoff Control Performance of Three Typical Low-Impact Development Facilities: A Case Study of a Community in Beijing
by Jiayi Xiao, Zhiwei Zhou, Zhiyu Yang, Zhili Li, Xiaolong Li, Jinjun Zhou and Hao Wang
Water 2024, 16(17), 2373; https://doi.org/10.3390/w16172373 - 23 Aug 2024
Viewed by 858
Abstract
The development of sponge cities advocates for sustainable urban rainwater management, effectively alleviating urban flood disasters, reducing non-point-source pollution, and promoting the recycling of rainwater resources. Low-Impact Development (LID) serves as a key strategy in this context, providing essential support for urban rainwater [...] Read more.
The development of sponge cities advocates for sustainable urban rainwater management, effectively alleviating urban flood disasters, reducing non-point-source pollution, and promoting the recycling of rainwater resources. Low-Impact Development (LID) serves as a key strategy in this context, providing essential support for urban rainwater control and pollution reduction. To investigate the runoff control effects of LID measures and to reveal the relationship between facility runoff control performance and installation scale, this study focuses on a sponge community in Beijing. A SWMM model was constructed to analyze the rainwater flood control and pollutant load reduction effects of different LID facilities, including bio-retention cells, green roofs, and permeable pavements. Using evaluation indicators such as surface runoff, node overflow, and pollutant control rates, this study examined how facility performance varies with installation scale under different rainfall conditions. The combination scheme of LID equipment optimal configuration is designed by using multiple criteria decision analysis (MCDA) and cost–benefit theory. The results indicate significant differences in performance among the various LID facilities across different rainfall scenarios. Specifically, the optimal installation proportion for runoff and overflow control of permeable pavements were found to be between 30% and 70%. Green roofs demonstrate superior performance in handling extreme rainfall events, while bio-retention cells exhibit significant effectiveness in controlling Total Suspended Solids (TSSs). Through comprehensive performance evaluation, this study identified the optimal combination scale under a 3-year rainfall recurrence interval as 30% permeable pavements, 20% green roof, and 60% bio-retention cells. This combination effectively leverages the strengths of each facility, ensuring system stability and efficiency while also demonstrating optimal management efficiency in cost–benefit analyses. The findings of this research provide valuable insights for future urban water management and infrastructure development. Full article
(This article belongs to the Special Issue Urban Flood Frequency Analysis and Risk Assessment)
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