Simulation and Analysis of Flood Disaster in River Basins during Typhoons and Heavy Rainstorms

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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 9741

Special Issue Editors


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Guest Editor
Department of River & Harbor Engineering, National Taiwan Ocean University, Keelung City, Taiwan
Interests: surface water hydrology; open channel hydraulics; sediment transport; geographic information system

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Guest Editor
Civil Engineering Department, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
Interests: hydrological modelling; remote sensing; flood; hydrology and watershed management; impacts of climate change on water resources

Special Issue Information

Dear Colleagues,

Global warming and climate change have increased typhoons and heavy rainstorms in recent years. The loss in occasions of flood disaster is severe than before because the population is more concentrated in urban areas. The simulation of a flood event is initiated from the upstream rainfall–runoff process, midstream flood wave propagation, and finally to the downstream inundation imitation. Flood disaster prevention can be implemented either through structural measures or nonstructural measures. Since both are based on a series of hydrological simulations, a better understanding of current flood simulation methods is considered necessary.

This Special Issue will focus on the following relevant topics:

  • Innovation of watershed rainfall–runoff simulations;
  • Innovation of flood wave propagation simulations;
  • Innovation of inundation simulations;
  • Integrated flood forecasting systems;
  • Extreme historical flood event analysis;
  • Numerical instability alleviation;
  • Analysis of flood economic impact;
  • Uncertainties of flood forecasting;
  • Comparison of inundation simulation in different storm sizes;

Submissions of both general methodological contributions and case studies of flood disaster simulation and analysis are strongly encouraged.

Prof. Dr. Kwan Tun Lee
Dr. Chaiwat Ekkawatpanit
Guest Editors

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Keywords

  • hydrology and hydraulic
  • rainfall–runoff processes
  • flood wave propagation
  • inundation simulation
  • stability of numerical algorithms
  • historic flood analysis
  • flood forecasting
  • flood risk analysis
  • sediment transport during flood
  • flood economic impact

Published Papers (4 papers)

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Research

18 pages, 2135 KiB  
Article
An Improved Flood Susceptibility Assessment in Jeddah, Saudi Arabia, Using Advanced Machine Learning Techniques
by Abdulnoor A. J. Ghanim, Ahmad Shaf, Tariq Ali, Maryam Zafar, Ahmed M. Al-Areeq, Saleh H. Alyami, Muhammad Irfan and Saifur Rahman
Water 2023, 15(14), 2511; https://doi.org/10.3390/w15142511 - 09 Jul 2023
Cited by 10 | Viewed by 1784
Abstract
The city of Jeddah experienced a severe flood in 2020, resulting in loss of life and damage to property. In such scenarios, a flood forecasting model can play a crucial role in predicting flood events and minimizing their impact on communities. The proposed [...] Read more.
The city of Jeddah experienced a severe flood in 2020, resulting in loss of life and damage to property. In such scenarios, a flood forecasting model can play a crucial role in predicting flood events and minimizing their impact on communities. The proposed study aims to evaluate the performance of machine learning algorithms in predicting floods and non-flood regions, including Gradient Boosting, Extreme Gradient Boosting, AdaBoosting Gradient, Random Forest, and the Light Gradient Boosting Machine, using the dataset from Jeddah City, Saudi Arabia. This study identified fourteen continuous parameters and various classification variables to assess the correlation between these variables and flooding incidents in the analyzed region. The performance of the proposed algorithms was measured using classification matrices and regression matrices. The highest accuracy (86%) was achieved by the Random Forest classifier, and the lowest error rate (0.06) was found with the Gradient Boosting regressor machine. The performance of other algorithms was also exceptional compared to existing literature. The results of the study suggest that the application of these machine learning algorithms can significantly enhance flood prediction accuracy, enabling various industries and sectors to make more informed decisions. Full article
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15 pages, 4520 KiB  
Article
A Dilemma between Flood and Drought Management: Case Study of the Upper Chao Phraya Flood-Prone Area in Thailand
by Weerayuth Pratoomchai, Chaiwat Ekkawatpanit, Naphol Yoobanpot and Kwan Tun Lee
Water 2022, 14(24), 4056; https://doi.org/10.3390/w14244056 - 12 Dec 2022
Cited by 1 | Viewed by 1865
Abstract
Floods are the greatest natural disaster in Thailand, but they are an important part of recharging the water volume for groundwater resources. This paper focused on evaluating and discussing the relationship between flood magnitudes and flood management impacting groundwater storage in the Upper [...] Read more.
Floods are the greatest natural disaster in Thailand, but they are an important part of recharging the water volume for groundwater resources. This paper focused on evaluating and discussing the relationship between flood magnitudes and flood management impacting groundwater storage in the Upper Chao Phraya River basin in Thailand, where the intensive rice production of the region is located. Based on satellite image data, there were annual flood inundations varying from 1950 to 10,470 km2 over the period 2005–2019. The evaluation shows those flooding events yielded floodwater recharge of approximately 0.5–5.9 km3. To lessen the flood damage, floodways with 2000 m3 s−1 of drainage capacity are proposed by the government. This measure aims to accelerate flood surplus out to the gulf of Thailand and to confine the flooding areas to a maximum value of 4650 km2. A reduction of approximately 3.4 km3 of groundwater storage is estimated if the floodways are implemented. Staple crops in the dry season, especially rice fields outside an irrigation project (rainfed area), cope with water stress. To sustain basin water demand in the dry season, approximately 1820 km2 should be allowed for an area flooded for a month where 0.9 km3 of water volume is harvested annually. Although flood control is important, potential impact on the reduction of groundwater recharge needs to be carefully considered. Therefore, a flood control policy shows the balance of available basin water occasionally supplied by the groundwater while rice water demand is being proposed. Full article
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20 pages, 10939 KiB  
Article
Flash Flood Susceptibility Assessment Based on Morphometric Aspects and Hydrological Approaches in the Pai River Basin, Mae Hong Son, Thailand
by Thapthai Chaithong
Water 2022, 14(19), 3174; https://doi.org/10.3390/w14193174 - 09 Oct 2022
Cited by 2 | Viewed by 2375
Abstract
Flash floods are water-related disasters that cause damage to properties, buildings, and infrastructures in the flow path. Flash floods often occur within a short period of time following intense rainfall in the high, mountainous area of northern Thailand. Therefore, the purpose of this [...] Read more.
Flash floods are water-related disasters that cause damage to properties, buildings, and infrastructures in the flow path. Flash floods often occur within a short period of time following intense rainfall in the high, mountainous area of northern Thailand. Therefore, the purpose of this study is to generate a flash flood susceptibility map using watershed morphometric parameters and hydrological approaches. In this study, the Pai River basin, located in Mae Hong Son in northern Thailand, is divided into 86 subwatersheds, and 23 morphometric parameters of the watershed are extracted from the digital elevation model (DEM). In addition, the soil conservation service curve number (SCS-CN) model is used to estimate the precipitation excess, and Snyder’s synthetic unit hydrograph method is used to estimate the time to peak and time of concentration. With respect to the rainfall dataset, in this study, we combined CHIRPS data (as satellite gridded precipitation data) with rainfall data measured within the study area for the runoff analysis. According to the analysis results, 25 out of 86 subwatersheds are classified as highly susceptible areas to flash floods. The similarities in the morphometric parameters representing watersheds in highly flash flood-susceptible areas indicate that this categorization included areas with high relief, high relief ratios, high ruggedness ratios, high stream frequencies, high texture ratios, high annual runoff, high peak discharge, low elongation ratios, and low lemniscates ratios. Full article
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15 pages, 4906 KiB  
Communication
Guidelines for Analysing Coastal Flood Protection Systems after a Submersion
by Marc Igigabel, Yves Nédélec, Nathalie Bérenger, Nicolas Flouest, Alexis Bernard, Patrick Chassé and Anne-Laure Tiberi-Wadier
Water 2022, 14(1), 15; https://doi.org/10.3390/w14010015 - 22 Dec 2021
Cited by 1 | Viewed by 2460
Abstract
Storm Xynthia, which hit the French Atlantic coast on 28 February 2010, flooded vast territories despite coastal defences. This disaster highlighted the need to further study the behaviour of the coastal flood protection systems at an adapted geographical scale by considering the kinematics [...] Read more.
Storm Xynthia, which hit the French Atlantic coast on 28 February 2010, flooded vast territories despite coastal defences. This disaster highlighted the need to further study the behaviour of the coastal flood protection systems at an adapted geographical scale by considering the kinematics of the events. This objective has been achieved through a combination of conceptual input on the definition of protection systems, significant breakthroughs in the knowledge of the mechanisms governing the flooding, and via the improvement of strategies and methods dedicated to flood analysis and representation. The developed methodology was successfully tested on four sites submerged during Xynthia (Loix, Les Boucholeurs, and Boyardville, located in Charente-Maritime, and Batz-sur-Mer, located in Loire-Atlantique). This work is intended to guide the diagnosis of sites prone to marine flooding from the first investigations until the delivery of study reports. Beyond the usual focus on hydraulic structures, it provides guidelines to better analyse the interactions with the natural environment (sea, soil, dune, wetlands, etc.) and with the built environment (roads and urban networks, ponds used for fish farming, buildings, etc.). This systemic approach, which is applied to a territory considered as a complex adaptive system, is fundamental to understanding the reaction of a territory during a marine submersion event and subsequently developing adaptation or transformation strategies. Full article
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