Editorial

Jump to: Research, Review

3 pages, 159 KiB

Open AccessEditorial

Editorial—Modelling of Floods in Urban Areas

by Jorge Leandro and James Shucksmith

Water 2021, 13(12), 1689; https://doi.org/10.3390/w13121689 - 18 Jun 2021

Viewed by 2098

Abstract

Understanding the risk of flooding in urban areas is a societal priority [...] Full article

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

Research

Jump to: Editorial, Review

17 pages, 7975 KiB

Open AccessArticle

Development of a Simulation Model for Real-Time Urban Floods Warning: A Case Study at Sukhumvit Area, Bangkok, Thailand

by Detchphol Chitwatkulsiri, Hitoshi Miyamoto and Sutat Weesakul

Water 2021, 13(11), 1458; https://doi.org/10.3390/w13111458 - 22 May 2021

Cited by 9 | Viewed by 3831

Abstract

Increasingly frequent, high-intensity rain events associated with climatic change are driving urban drainage systems to function beyond their design discharge capacity. It has become an urgent issue to mitigate the water resource management challenge. To address this problem, a real-time procedure for predicting [...] Read more.

Increasingly frequent, high-intensity rain events associated with climatic change are driving urban drainage systems to function beyond their design discharge capacity. It has become an urgent issue to mitigate the water resource management challenge. To address this problem, a real-time procedure for predicting the inundation risk in an urban drainage system was developed. The real-time procedure consists of three components: (i) the acquisition and forecast of rainfall data; (ii) rainfall-runoff modeling; and (iii) flood inundation mapping. This real-time procedure was applied to a drainage system in the Sukhumvit area of Bangkok, Thailand, to evaluate its prediction efficacy. The results showed precisely that the present real-time procedure had high predictability in terms of both the water level and flood inundation area mapping. It could also determine hazardous areas with a certain amount of lead time in the drainage system of the Sukhumvit area within an hour of rainfall data. These results show the real-time procedure could provide accurate flood risk warning, resulting in more time to implement flood management measures such as pumping and water gate operations, or evacuation. Full article

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

► Show Figures

Figure 1

24 pages, 24572 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Flood Suspended Sediment Transport: Combined Modelling from Dilute to Hyper-Concentrated Flow

by Jaan H. Pu, Joseph T. Wallwork, Md. Amir Khan, Manish Pandey, Hanif Pourshahbaz, Alfrendo Satyanaga, Prashanth R. Hanmaiahgari and Tim Gough

Water 2021, 13(3), 379; https://doi.org/10.3390/w13030379 - 01 Feb 2021

Cited by 30 | Viewed by 4232

Abstract

During flooding, the suspended sediment transport usually experiences a wide-range of dilute to hyper-concentrated suspended sediment transport depending on the local flow and ground conditions. This paper assesses the distribution of sediment for a variety of hyper-concentrated and dilute flows. Due to the [...] Read more.

During flooding, the suspended sediment transport usually experiences a wide-range of dilute to hyper-concentrated suspended sediment transport depending on the local flow and ground conditions. This paper assesses the distribution of sediment for a variety of hyper-concentrated and dilute flows. Due to the differences between hyper-concentrated and dilute flows, a linear-power coupled model is proposed to integrate these considerations. A parameterised method combining the sediment size, Rouse number, mean concentration, and flow depth parameters has been used for modelling the sediment profile. The accuracy of the proposed model has been verified against the reported laboratory measurements and comparison with other published analytical methods. The proposed method has been shown to effectively compute the concentration profile for a wide range of suspended sediment conditions from hyper-concentrated to dilute flows. Detailed comparisons reveal that the proposed model calculates the dilute profile with good correspondence to the measured data and other modelling results from literature. For the hyper-concentrated profile, a clear division of lower (bed-load) to upper layer (suspended-load) transport can be observed in the measured data. Using the proposed model, the transitional point from this lower to upper layer transport can be calculated precisely. Full article

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

► Show Figures

Figure 1

23 pages, 12015 KiB

Open AccessArticle

Urbanization and Floods in Sub-Saharan Africa: Spatiotemporal Study and Analysis of Vulnerability Factors—Case of Antananarivo Agglomeration (Madagascar)

by Fenosoa Nantenaina Ramiaramanana and Jacques Teller

Water 2021, 13(2), 149; https://doi.org/10.3390/w13020149 - 10 Jan 2021

Cited by 25 | Viewed by 7414

Abstract

Flooding is currently one of the major threats to cities in Sub-Saharan Africa (SSA). The demographic change caused by the high rate of natural increase, combined with the migration toward cities, leads to a strong demand for housing and promotes urbanization. Given the [...] Read more.

Flooding is currently one of the major threats to cities in Sub-Saharan Africa (SSA). The demographic change caused by the high rate of natural increase, combined with the migration toward cities, leads to a strong demand for housing and promotes urbanization. Given the insufficiency or absence of adequate planning, many constructions are installed in flood-prone zones, often without adequate infrastructure, especially drainage systems. This makes them very vulnerable. Our research consists of carrying out a spatiotemporal analysis of the agglomeration of Antananarivo (Madagascar). It shows that urbanization leads to increased exposure of populations and constructions to floods. There is a pressure on land in flood-prone zones due to the exponential growth of the population at the agglomeration level. Some 32% of the population of the Antananarivo agglomeration lived in flood-prone zones in 2018. An analysis of the evolution of built spaces from 1953 to 2017 highlights that urban expansion was intense over those years (6.1% yearly increase of built areas). This expansion triggered the construction of built areas in flood-prone zones, which evolved from 399 ha in 1953 to 3675 ha in 2017. In 2017, 23% of the buildings in the agglomeration, i.e., almost one out of every four buildings, were in flood-prone zones. A share of the urban expansion in flood-prone zones is related to informal developments that gather highly vulnerable groups with very little in terms of economic resources. Better integration of flood risk management in spatial planning policies thus appears to be an essential step to guide decisions so as to coordinate the development of urban areas and drainage networks in a sustainable way, considering the vulnerability of the population living in the most exposed areas. Full article

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

► Show Figures

Figure 1

20 pages, 4030 KiB

Open AccessArticle

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

by Qing Lin, Jorge Leandro, Stefan Gerber and Markus Disse

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

Cited by 11 | Viewed by 2970

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 [...] Read more.

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)

► Show Figures

Figure 1

15 pages, 8076 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

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

by Esteban Sañudo, Luis Cea and Jerónimo Puertas

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

Cited by 43 | Viewed by 6810

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 [...] Read more.

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)

► Show Figures

Figure 1

17 pages, 3650 KiB

Open AccessEditor’s ChoiceArticle

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

by Md Nazmul Azim Beg, Matteo Rubinato, Rita F. Carvalho and James D. Shucksmith

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

Cited by 19 | Viewed by 4536

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 [...] Read more.

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)

► Show Figures

Figure 1

22 pages, 6518 KiB

Open AccessEditor’s ChoiceArticle

Modeling Urban Flood Inundation and Recession Impacted by Manholes

by Merhawi GebreEgziabher and Yonas Demissie

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

Cited by 26 | Viewed by 7568

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 [...] Read more.

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)

► Show Figures

Figure 1

30 pages, 6129 KiB

Open AccessEditor’s ChoiceArticle

GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment

by Binh Thai Pham, Mohammadtaghi Avand, Saeid Janizadeh, Tran Van Phong, Nadhir Al-Ansari, Lanh Si Ho, Sumit Das, Hiep Van Le, Ata Amini, Saeid Khosrobeigi Bozchaloei, Faeze Jafari and Indra Prakash

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

Cited by 130 | Viewed by 7926

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 [...] Read more.

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)

► Show Figures

Figure 1

Review

Jump to: Editorial, Research

13 pages, 4335 KiB

Open AccessFeature PaperReview

Porosity Models for Large-Scale Urban Flood Modelling: A Review

by Benjamin Dewals, Martin Bruwier, Michel Pirotton, Sebastien Erpicum and Pierre Archambeau

Water 2021, 13(7), 960; https://doi.org/10.3390/w13070960 - 31 Mar 2021

Cited by 13 | Viewed by 2637

Abstract

In the context of large-scale urban flood modeling, porosity shallow-water models enable a considerable speed-up in computations while preserving information on subgrid topography. Over the last two decades, major improvements have been brought to these models, but a single generally accepted model formulation [...] Read more.

In the context of large-scale urban flood modeling, porosity shallow-water models enable a considerable speed-up in computations while preserving information on subgrid topography. Over the last two decades, major improvements have been brought to these models, but a single generally accepted model formulation has not yet been reached. Instead, existing models vary in many respects. Some studies define porosity parameters at the scale of the computational cells or cell interfaces, while others treat the urban area as a continuum and introduce statistically defined porosity parameters. The porosity parameters are considered either isotropic or anisotropic and depth-independent or depth-dependent. The underlying flow models are based either on the full shallow-water equations or approximations thereof, with various flow resistance parameterizations. Here, we provide a review of the spectrum of porosity models developed so far for large-scale urban flood modeling. Full article

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

► Show Figures

Figure 1

Journal Menu

Journal Browser

Modelling of Floods in Urban Areas

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (10 papers)

Editorial

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI