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Water
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Flood Risk Identification and Management
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Flood Risk Identification and Management

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

Deadline for manuscript submissions: 25 July 2024 | Viewed by 3490

Special Issue Editor

Prof. Dr. Juan Chen

E-Mail Website
Guest Editor
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Interests: reservoir operation; flood control operation; risk analysis; water resources allocation and management

Special Issue Information

Dear Colleagues,

Floods, as one of the most common natural disasters around the world, cause serious economic loss and even human fatalities. Moreover, there are many uncertainties associated with flood forecast and management, which bring risks to flood control decision making. Therefore, risk identification and management are crucial to mitigate flood hazards and disasters in river basins.

The interests of this Special Issue include, but are not limited to the following:

  1. understanding and methodologies for risk identification with respects to flood, flood forecast, flood control operation and decision making;
  2. flood forecast and operation methodologies dealing with uncertainties and risks;
  3. risk analysis methods and models for flood, as well as flood forecast, operation and decision making;
  4. risk management measures and methods to mitigate flood hazards and disasters considering uncertainties.

Prof. Dr. Juan Chen
Guest Editor

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
  • flood management
  • flood control operation
  • risk identification
  • risk assessment
  • risk management
  • uncertainty

Published Papers (4 papers)

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Research

17 pages, 3895 KiB  
Article
Extreme Flood Flow Routing for Panchet and Maithan Reservoirs of India Using Modified Puls Technique
by Mayuree Dasgupta and Subhasish Das
Water 2024, 16(5), 663; https://doi.org/10.3390/w16050663 - 24 Feb 2024
Viewed by 692
Abstract
An important aspect of economic considerations is the routing and safety of hydraulic storage facilities such as dams for extreme probable water flooding. The routing of dam reservoirs requires more attention for determining the magnitude of extreme probable flooding. Apparently, the type of [...] Read more.
An important aspect of economic considerations is the routing and safety of hydraulic storage facilities such as dams for extreme probable water flooding. The routing of dam reservoirs requires more attention for determining the magnitude of extreme probable flooding. Apparently, the type of structure, importance, and economic development of the surrounding area guide the routing criteria for choosing the extreme flood magnitude. The Maithan and Panchet Dams in India have faced several major floods with diversified magnitudes since 1978. The present study aims to estimate the storage and routing of extreme probable floodings for these two dams based on real-time flood data like inflow, outflow, and elevation for the extreme flood years of 1978, 2009, and 2014. Reservoir storages at different elevations are calculated from the initial storage volumes. For both reservoirs, discharge equations are derived and calculated at given elevations during extreme floods. The Modified Puls technique is used for routing extreme floods. At the end of each extreme flood in 1978, 2009, and 2014, the variation in outflow discharges at different elevations and flood hydrographs is predicted. Finally, estimated outflow discharges are compared with the actual outflow discharges for the given inflows during extreme floods. Using this approach, extreme floods that occurred in 1978 are predicted with less than 10% error. Outcomes from this study may help in the future planning and routing of flood-control detention facilities and in predicting the variation in outflow discharges at different elevations. Based on this work, alternative studies and regional drainage planning can also be carried out. Full article
(This article belongs to the Special Issue Flood Risk Identification and Management)
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19 pages, 3741 KiB  
Article
The Influence of Time Domain on Flood Season Segmentation by the Fisher Optimal Partition Method
by Yanbin Li, Yubo Li, Kai Feng, Ke Sun and Zhichao Cheng
Water 2024, 16(4), 580; https://doi.org/10.3390/w16040580 - 16 Feb 2024
Viewed by 560
Abstract
Setting the staged flood limit water level (FLWL) through flood season staging is an important means of fully utilizing reservoir flood resources. The widely-used Fisher optimal partition method requires a certain time domain as the basic unit in determining the optimal staging of [...] Read more.
Setting the staged flood limit water level (FLWL) through flood season staging is an important means of fully utilizing reservoir flood resources. The widely-used Fisher optimal partition method requires a certain time domain as the basic unit in determining the optimal staging of a flood season. Currently, 5 and 10 days matching the month and solar terms are usually used as the time unit. This study aimed to analyze the influence of other time-domain units (7 and 15 days) that meet the relevant requirements on the staging results and to provide a scientific basis for the selection of time-domain units in flood season staging. The rationality of the staging scheme was tested using the improved Cunderlik method, and the influence of specific basic units in the Fisher optimal partition method on the staging results was evaluated. The highest relative superiority of 0.9876 was found for 5 d, indicating that this is a suitable time-domain unit. The optimal staging result was determined as 20 June for the first segmentation point and 20 August for the second. A comparison of the staged FLWL with a single fixed FLWL showed that the water level was raised by 1.56 m in the pre-flood season, 0.65 m in the main flood season, and 1.37 m in the post-flood season. Water storage increased by 12.79 million m3 during the flood season, effectively alleviating the mismatch between water supply and storage. Full article
(This article belongs to the Special Issue Flood Risk Identification and Management)
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19 pages, 4409 KiB  
Article
Investigating Flood Characteristics and Mitigation Measures in Plain-Type River-Connected Lakes: A Case Study of Poyang Lake
by Shupan Deng, Qiuqin Wu, Zhichao Wang, Longhua Wu, Zhiwen Huang and Guangming Zhang
Water 2024, 16(2), 281; https://doi.org/10.3390/w16020281 - 12 Jan 2024
Viewed by 815
Abstract
The flow of plain-type river-connected lakes is affected by both upstream and downstream rivers, and the hydrological conditions are very complex. Poyang Lake, situated in Jiangxi Province, is the largest river-connected lake in the Yangtze River Basin. Its unique geographical features and complex [...] Read more.
The flow of plain-type river-connected lakes is affected by both upstream and downstream rivers, and the hydrological conditions are very complex. Poyang Lake, situated in Jiangxi Province, is the largest river-connected lake in the Yangtze River Basin. Its unique geographical features and complex hydrological conditions have made it a heavy disaster area and a frequent area of floods since ancient times. As typical mitigation measures of Poyang Lake, semi-restoration polder areas and flood storage and detention areas play a crucial role in the flood control of Poyang Lake. Taking Poyang Lake as an example, this article studies the flood characteristics of Poyang Lake based on the measured hydrological data. Furthermore, by using the weir (gate) outflow formula to construct the hydraulic model of semi-restoration polder areas and DHI MIKE to construct the hydrodynamic model of Kangshan flood storage and detention area, the flood diversion capacity of the two, and the flood diversion effect under the super-historical flood in 2020 are analyzed. The results show that compared with the non-use of mitigation measures, the maximum cumulative reduction in Xingzi water level can be reduced by 0.68 m and 0.48 m when semi-restoration polder areas and Kangshan flood storage and detention areas are used alone. Finally, the article puts forward some thoughts and suggestions on the flood control of Poyang Lake. The research results can offer some reference to the flood risk management of plain-type river-connected lakes. Full article
(This article belongs to the Special Issue Flood Risk Identification and Management)
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19 pages, 3515 KiB  
Article
Predicting the Overflowing of Urban Personholes Based on Machine Learning Techniques
by Ya-Hui Chang, Chih-Wei Tseng and Hsien-Chieh Hsu
Water 2023, 15(23), 4100; https://doi.org/10.3390/w15234100 - 26 Nov 2023
Viewed by 914
Abstract
Urban stormwater drainage systems, which include many personholes to collect and discharge precipitation within a city, are extensively constructed to prevent streets and buildings from flooding. This research intends to build a machine learning model to predict whether a personhole will overflow soon, [...] Read more.
Urban stormwater drainage systems, which include many personholes to collect and discharge precipitation within a city, are extensively constructed to prevent streets and buildings from flooding. This research intends to build a machine learning model to predict whether a personhole will overflow soon, which is crucial to alleviate the damage caused by floods. To address the challenges posed by many diverse personholes, we proposed segmenting the personholes into several groups and have designed two methods employing different personhole features. The first, the geography-based method, uses the geographical locations of the personholes for the grouping. The second, the hydrology-based method, uses the characteristics that are directly related to the overflowing situation, such as the depth of the personhole, and the average and the maximum water level of the personholes. We also investigated several machine learning techniques, such as the multilayer perceptron (MLP) model and a fine-tuning architecture. The study area was located in the new Taipei city and the experimental results have shown the impressive predictive ability of the proposed approaches. Particularly, by applying the hydrology-based grouping method, and using a hybrid model combining the machine learning model prediction results with heuristic rules, we can obtain the best prediction result, and the accuracy is over 99%. We have also noticed the influence of the activation function used in the neural network and the number of frozen layers in the fine-tuning architecture. Particularly, using the tanh function with one frozen layer is good in some cases. However, since it is not general enough, we suggest the readers perform empirical studies before choosing the best setting in their own environment. Full article
(This article belongs to the Special Issue Flood Risk Identification and Management)
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