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Special Issue "Modelling of Floods in Urban Areas"

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

Deadline for manuscript submissions: 31 December 2020.

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Special Issue Editors

Prof. Dr. Jorge Leandro
Website
Guest Editor

Department of Civil, Geo and Environmental Engineering, Technical University of Munich, Munich, Germany
Interests: Hydrology, Hydraulics, Hydrological Modeling, Rainfall Runoff Modelling, Watershed Hydrology, Hydraulic Engineering, Fluid Mechanics, Numerical Modeling, Civil Engineering, Computational Fluid Dynamics
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Dr. James Shucksmith
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Guest Editor

Department of Civil and Structural Engineering, the University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK
Interests: physical processes associated with urban flooding; model validation and uncertainty quantification; pollutant transport in river and urban catchments

Special Issue Information

Dear Colleagues,

Understanding the risk of flooding in urban areas is a societal priority. However, there are significant technical challenges associated with the appropriate charaterisation and representation of the numerous complex physical and hydrodinamic processes envolved.

The aim of this Special Issue is thus to publish the latest advances and developments concerning the modelling of flooding in urban areas and contribute to our scientific understanding of the flooding procceeses and the appropriate evaluation of flood risk.

It is anticipated that this issue will contain contributions of novel methodologies including (but not limited to) flood forecasting methods, data acquisition techniques, experimental research in urban drainage systems and/or sustainable drainage systems and new numerical approaches.

We further encourage the submission of original research, synthetic reviews or case study papers applying numerical or experimental modelling techniques in order to study the following topics:

Shallow overland flows over urban terrains

Flood forecasting

Evaluation of urban flood risk

Drainage system/surface flow interactions

Calibration and validation

Uncertainty quantification

The accepted papers will be published as open access ensuring widespread availability.

Dr. Jorge Leandro
Dr. James Shucksmith
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 papers will be 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 1800 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

floods
urban drainage
surface flow
shallow water equations
calibration
validation
flood forecasting
uncertainty

Published Papers (5 papers)

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Research

Open AccessArticle

Multistep Flood Inundation Forecasts with Resilient Backpropagation Neural Networks: Kulmbach Case Study

and

Water 2020, 12(12), 3568; https://doi.org/10.3390/w12123568 - 19 Dec 2020

Abstract

Flooding, a significant natural disaster, attracts worldwide attention because of its high impact on communities and individuals and increasing trend due to climate change. A flood forecast system can minimize the impacts by predicting the flood hazard before it occurs. Artificial neural networks (ANN) could efficiently process large amounts of data and find relations that enable faster flood predictions. The aim of this study is to perform multistep forecasts for 1–5 h after the flooding event has been triggered by a forecast threshold value. In this work, an ANN developed for the real-time forecast of flood inundation with a high spatial resolution (4 m × 4 m) is extended to allow for multiple forecasts. After trained with 120 synthetic flood events, the ANN was first tested with 60 synthetic events for verifying the forecast performance for 3 h, 6 h, 9 h and 12 h lead time. The model produces good results, as shown by more than 81% of all grids having an RMSE below 0.3 m. The ANN is then applied to the three historical flood events to test the multistep inundation forecast. For the historical flood events, the results show that the ANN outputs have a good forecast accuracy of the water depths for (at least) the 3 h forecast with over 70% accuracy (RMSE within 0.3 m), and a moderate accuracy for the subsequent forecasts with (at least) 60% accuracy. Full article

(This article belongs to the Special Issue Modelling of Floods in Urban Areas)

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Open AccessFeature PaperArticle

Modelling Pluvial Flooding in Urban Areas Coupling the Models Iber and SWMM

Esteban Sañudo

Luis Cea

and

Jerónimo Puertas

Water 2020, 12(9), 2647; https://doi.org/10.3390/w12092647 - 22 Sep 2020

Abstract

Dual urban drainage models allow users to simulate pluvial urban flooding by analysing the interaction between the sewer network (minor drainage system) and the overland flow (major drainage system). This work presents a free distribution dual drainage model linking the models Iber and Storm Water Management Model (SWMM), which are a 2D overland flow model and a 1D sewer network model, respectively. The linking methodology consists in a step by step calling process from Iber to a Dynamic-link Library (DLL) that contains the functions in which the SWMM code is split. The work involves the validation of the model in a simplified urban street, in a full-scale urban drainage physical model and in a real urban settlement. The three study cases have been carefully chosen to show and validate the main capabilities of the model. Therefore, the model is developed as a tool that considers the main hydrological and hydraulic processes during a rainfall event in an urban basin, allowing the user to plan, evaluate and design new or existing urban drainage systems in a realistic way. Full article

(This article belongs to the Special Issue Modelling of Floods in Urban Areas)

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Open AccessEditor’s ChoiceArticle

CFD Modelling of the Transport of Soluble Pollutants from Sewer Networks to Surface Flows during Urban Flood Events

and

Water 2020, 12(9), 2514; https://doi.org/10.3390/w12092514 - 09 Sep 2020

Abstract

Surcharging urban drainage systems are a potential source of pathogenic contamination of floodwater. While a number of previous studies have investigated net sewer to surface hydraulic flow rates through manholes and gullies during flood events, an understanding of how pollutants move from sewer networks to surface flood water is currently lacking. This paper presents a 3D CFD model to quantify flow and solute mass exchange through hydraulic structures featuring complex interacting pipe and surface flows commonly associated with urban flood events. The model is compared against experimental datasets from a large-scale physical model designed to study pipe/surface interactions during flood simulations. Results show that the CFD model accurately describes pipe to surface flow partition and solute transport processes through the manhole in the experimental setup. After validation, the model is used to elucidate key timescales which describe mass flow rates entering surface flows from pipe networks. Numerical experiments show that following arrival of a well-mixed solute at the exchange structure, solute mass exchange to the surface grows asymptotically to a value equivalent to the ratio of flow partition, with associated timescales a function of the flow conditions and diffusive transport inside the manhole. Full article

(This article belongs to the Special Issue Modelling of Floods in Urban Areas)

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Open AccessArticle

Modeling Urban Flood Inundation and Recession Impacted by Manholes

Merhawi GebreEgziabher

and

Yonas Demissie

Water 2020, 12(4), 1160; https://doi.org/10.3390/w12041160 - 18 Apr 2020

Cited by 1

Abstract

Urban flooding, caused by unusually intense rainfall and failure of storm water drainage, has become more frequent and severe in many cities around the world. Most of the earlier studies focused on overland flooding caused by intense rainfall, with little attention given to floods caused by failures of the drainage system. However, the drainage system contributions to flood vulnerability have increased over time as they aged and became inadequate to handle the design floods. Adaption of the drainages for such vulnerability requires a quantitative assessment of their contribution to flood levels and spatial extent during and after flooding events. Here, we couple the one-dimensional Storm Water Management Model (SWMM) to a new flood inundation and recession model (namely FIRM) to characterize the spatial extent and depth of manhole flooding and recession. The manhole overflow from the SWMM model and a fine-resolution elevation map are applied as inputs in FIRM to delineate the spatial extent and depth of flooding during and aftermath of a storm event. The model is tested for two manhole flooding events in the City of Edmonds in Washington, USA. Our two case studies show reasonable match between the observed and modeled flood spatial extents and highlight the importance of considering manholes in urban flood simulations. Full article

(This article belongs to the Special Issue Modelling of Floods in Urban Areas)

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Open AccessArticle

GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment

Saeid Khosrobeigi Bozchaloei

Faeze Jafari

and

Indra Prakash

Water 2020, 12(3), 683; https://doi.org/10.3390/w12030683 - 02 Mar 2020

Cited by 16

Abstract

Flash floods are one of the most devastating natural hazards; they occur within a catchment (region) where the response time of the drainage basin is short. Identification of probable flash flood locations and development of accurate flash flood susceptibility maps are important for proper flash flood management of a region. With this objective, we proposed and compared several novel hybrid computational approaches of machine learning methods for flash flood susceptibility mapping, namely AdaBoostM1 based Credal Decision Tree (ABM-CDT); Bagging based Credal Decision Tree (Bag-CDT); Dagging based Credal Decision Tree (Dag-CDT); MultiBoostAB based Credal Decision Tree (MBAB-CDT), and single Credal Decision Tree (CDT). These models were applied at a catchment of Markazi state in Iran. About 320 past flash flood events and nine flash flood influencing factors, namely distance from rivers, aspect, elevation, slope, rainfall, distance from faults, soil, land use, and lithology were considered and analyzed for the development of flash flood susceptibility maps. Correlation based feature selection method was used to validate and select the important factors for modeling of flash floods. Based on this feature selection analysis, only eight factors (distance from rivers, aspect, elevation, slope, rainfall, soil, land use, and lithology) were selected for the modeling, where distance to rivers is the most important factor for modeling of flash flood in this area. Performance of the models was validated and compared by using several robust metrics such as statistical measures and Area Under the Receiver Operating Characteristic (AUC) curve. The results of this study suggested that ABM-CDT (AUC = 0.957) has the best predictive capability in terms of accuracy, followed by Dag-CDT (AUC = 0.947), MBAB-CDT (AUC = 0.933), Bag-CDT (AUC = 0.932), and CDT (0.900), respectively. The proposed methods presented in this study would help in the development of accurate flash flood susceptible maps of watershed areas not only in Iran but also other parts of the world. Full article

(This article belongs to the Special Issue Modelling of Floods in Urban Areas)

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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Title: Urbanisation and Risk of Flooding in Antananarivo (Madagascar)
Authors: F. Nantenaina Ramiaramanana; Jacques Teller
Abstract: The risk of flooding is currently on the list of major recent threats affecting most countries and those of Africa are among the most affected. Urbanisation is a major factor. This article shows that the rapid demographic change caused by the high rate of natural increase and the considerable migration towards the urban center leads to a strong demand in terms of housing and promotes urban sprawl. However, with the insufficiency or even the absence of adequate planning, many constructions are gradually being installed in the areas exposed to floods and often without equipment they can reach a high degree of precariousness. Without an adequate drainage network, they become even more vulnerable. This is the case of the agglomeration of Antananarivo. A first analysis is made on the growth of the population between 1993 and 2018 allowing to estimate the number of population in flood-prone areas and a second on the evolution of built spaces in four years to assess the increase of the part of construction in flood-prone areas. Case studies are added to this in order to see potential problems related to densification and the drainage system in low areas. The document concludes that urban planning is essential to avoid installations in prohibited areas or risk areas. The integration of flood risk management into spatial planning policies is an essential step in order to guide decisions and the coupling of spatial planning and the drainage network remains fundamental.
Keywords: demographic change ; urbanisation ; risk of flooding ; African cities ; Antananarivo ; drainage system ; urban planning

2. 1 paper from Jorge Leandro <[email protected]> et al.

3. 1 paper from Benjamin Dewals <[email protected]> et al.

4. 1 paper from Jaan Pu <[email protected]> et al.

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