Flood Frequency and Inundation Modelling

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Hydrogeology".

Deadline for manuscript submissions: closed (20 December 2019) | Viewed by 11996

Special Issue Editor


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Guest Editor
CSIRO Land & Water, Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT 2601, Australia
Interests: hydrology; floodplain hydraulics; inundation modelling; water resources assessment; sediment transport; hydrological connectivity and linking hydrology and ecology
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Special Issue Information

Dear Colleagues,

Flood is one of most deadly natural disasters in the earth. Improved knowledge on flood magnitude, frequency, duration and inundation area are pre-requisite for disaster management, infrastructure development and maintaining environmental integrity. The main goal of this Special Issue of Geosciences is to explore and highlight the advances in flood frequency analysis and inundation modelling across a range of river basins around the world. This special issue welcomes the research papers on developing advanced methods for flood frequency analysis and modelling tools for quantifying inundation dynamics under variable flow regimes.

Specifically, this Special Issue aims to provide peer-reviewed studies utilizing probabilistic, hydrological and hydrodynamic modelling techniques for flood frequency and floodplain inundation modelling. This special issue aims to cover, the following research areas:

  • Precipitation modelling: using various probabilities modelling techniques to quantify variability and changes in historical precipitation, climate modelling to assess changes in precipitation under projected future climates;
  • Streamflow assessment: predicting streamflow in ungauged basin and modelling the changes in flow regimes for future climate and infrastructure development;
  • Flood frequency: regional and continental scale flood frequency analysis, variability and trend analysis, uncertainty in flood modelling;
  • Floodplain inundation modelling: advances in modelling techniques, impact of climate and infrastructure development on inundation dynamics and frequency of flooding, coupling of remote sensing and hydrodynamic modelling for inundation mapping;
  • Ecological impact assessment: Quantifying impacts of changes in hydrological flow metrics on flow dependent ecosystem.

This is a great opportunity to publish your research in a peer-reviewed and open access journal. I encourage the submission of original research, case study, review papers based on hydrologic, hydrodynamic and ecological modelling.

Dr. Fazlul Karim
Guest Editor

Manuscript Submission Information

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Keywords

  • River basin
  • Floodplain
  • Rainfall
  • Runoff
  • Flood frequency
  • Global climate model
  • Hydrodynamic modelling
  • Remote sensing
  • Hydrological connectivity
  • Hydrological flow metrics
  • Ecological impact assessment

Published Papers (4 papers)

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Research

15 pages, 2245 KiB  
Article
Regional Flood Frequency Analysis Using an Artificial Neural Network Model
by Sasan Kordrostami, Mohammad A Alim, Fazlul Karim and Ataur Rahman
Geosciences 2020, 10(4), 127; https://doi.org/10.3390/geosciences10040127 - 01 Apr 2020
Cited by 12 | Viewed by 3066
Abstract
This paper presents the results from a study on the application of an artificial neural network (ANN) model for regional flood frequency analysis (RFFA). The study was conducted using stream flow data from 88 gauging stations across New South Wales (NSW) in Australia. [...] Read more.
This paper presents the results from a study on the application of an artificial neural network (ANN) model for regional flood frequency analysis (RFFA). The study was conducted using stream flow data from 88 gauging stations across New South Wales (NSW) in Australia. Five different models consisting of three to eight predictor variables (i.e., annual rainfall, drainage area, fraction forested area, potential evapotranspiration, rainfall intensity, river slope, shape factor and stream density) were tested. The results show that an ANN model with a higher number of predictor variables does not always improve the performance of RFFA models. For example, the model with three predictor variables performs considerably better than the models using a higher number of predictor variables, except for the one which contains all the eight predictor variables. The model with three predictor variables exhibits smaller median relative error values for 2- and 20-year return periods compared to the model containing eight predictor variables. However, for 5-, 10-, 50- and 100-year return periods, the model with eight predictor variables shows smaller median relative error values. The proposed ANN modelling framework can be adapted to other regions in Australia and abroad. Full article
(This article belongs to the Special Issue Flood Frequency and Inundation Modelling)
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11 pages, 1576 KiB  
Article
Using Mixed Probability Distribution Functions for Modelling Non-Zero Sub-Daily Rainfall in Australia
by Md Masud Hasan, Barry F. W. Croke, Shuangzhe Liu, Kunio Shimizu and Fazlul Karim
Geosciences 2020, 10(2), 43; https://doi.org/10.3390/geosciences10020043 - 24 Jan 2020
Cited by 7 | Viewed by 2605
Abstract
Probabilistic models for sub-daily rainfall predictions are important tools for understanding catchment hydrology and estimating essential rainfall inputs for agricultural and ecological studies. This research aimed at achieving theoretical probability distribution to non-zero, sub-daily rainfall using data from 1467 rain gauges across the [...] Read more.
Probabilistic models for sub-daily rainfall predictions are important tools for understanding catchment hydrology and estimating essential rainfall inputs for agricultural and ecological studies. This research aimed at achieving theoretical probability distribution to non-zero, sub-daily rainfall using data from 1467 rain gauges across the Australian continent. A framework was developed for estimating rainfall data at ungauged locations using the fitted model parameters from neighbouring gauges. The Lognormal, Gamma and Weibull distributions, as well as their mixed distributions were fitted to non-zero six-minutes rainfall data. The root mean square error was used to evaluate the goodness of fit for each of these distributions. To generate data at ungauged locations, parameters of well-fit models were interpolated from the four closest neighbours using inverse weighting distance method. Results show that the Gamma and Weibull distributions underestimate and lognormal distributions overestimate the high rainfall events. In general, a mixed model of two distributions was found better compared to the results of an individual model. Among the five models studied, the mixed Gamma and Lognormal (G-L) distribution produced the minimum root mean square error. The G-L model produced the best match to observed data for high rainfall events (e.g., 90th, 95th, 99th, 99.9th and 99.99th percentiles). Full article
(This article belongs to the Special Issue Flood Frequency and Inundation Modelling)
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19 pages, 8715 KiB  
Article
Effect of Communication Regarding Dam Operation on the Evacuation of Residents: A Case Study of the 2018 Inundation of the Hijikawa River in Japan
by Isao Nakamura and Chiho Morioka
Geosciences 2019, 9(10), 444; https://doi.org/10.3390/geosciences9100444 - 18 Oct 2019
Cited by 2 | Viewed by 2851
Abstract
Communication on the operation of a dam is crucial in evacuating residents before downstream flooding occurs. This paper examines the effect of communication regarding dam operation on evacuation, studying the case of the 2018 flooding of the Hijikawa River in Japan. After confirming [...] Read more.
Communication on the operation of a dam is crucial in evacuating residents before downstream flooding occurs. This paper examines the effect of communication regarding dam operation on evacuation, studying the case of the 2018 flooding of the Hijikawa River in Japan. After confirming the communication process and the messages of warning, we conducted a questionnaire survey of affected residents. The findings of the survey are as follows. (1) The discharge warnings issued by dam operators had no effect, because few people heard the warnings and even those who heard them were not inclined to evacuate. (2) Accepting the notifications from dam operators, local governments issued evacuation instructions. These instructions promoted evacuation. The most effective trigger of evacuation was route alerting by the volunteer fire corps. Information from dam operators induced the issuing of evacuation instructions, which activated the route alerting, and the information therefore indirectly promoted evacuation. (3) The Public Warning System operating on mobile phones had a certain effect in disseminating evacuation instructions where the system was used. (4) The messages issued here had insufficient specificity and clarity. A flood simulation considering the discharge flow of a dam needs to be conducted in addressing this issue. Full article
(This article belongs to the Special Issue Flood Frequency and Inundation Modelling)
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15 pages, 2552 KiB  
Article
Changes in the Nature of Long-Term Fluctuations of Water Flow in the Subarctic Region of Yakutia: A Global Warming Perspective
by Raisa Shpakova, Konstantin Kusatov, Sabir Mustafin and Alexander Trifonov
Geosciences 2019, 9(7), 287; https://doi.org/10.3390/geosciences9070287 - 28 Jun 2019
Cited by 5 | Viewed by 3074
Abstract
Global warming has begun to affect Yakutia, an area recognized as the coldest region of the Northern Hemisphere. Previous research has indicated that the effects of global warming will be long-term. When modeling oncoming climatic changes, researchers often forecast the related water flow [...] Read more.
Global warming has begun to affect Yakutia, an area recognized as the coldest region of the Northern Hemisphere. Previous research has indicated that the effects of global warming will be long-term. When modeling oncoming climatic changes, researchers often forecast the related water flow changes in various water bodies as well. However, these evaluations frequently differ from the actual water flow data. Thus, the current study identifies and assesses the trends in long-term flow fluctuations in the current context of global warming. This is particularly relevant in the subarctic region of Yakutia, because the local climate is not significantly influenced by anthropogenic factors. The region has an essentially uniform climate, and the river basins within the subarctic zone flow in the same direction. Thus, the study parameters can be adequately compared. Analysis of changes in the water regimen parameters of the rivers in this region is of particular importance. This study demonstrates that the changes in the long-term river regimen in the region, within approximately equivalent climate zones, have been highly and locally variable indifferent areas and time periods. However, we were unable to detect any specific consistency in these changes. The water content of almost all rivers in Yakutia has increased in the last 30 years (approximately), thus confirming general assumptions based on predictive models of climate changes; however, in most cases, such changes were the result of reaching the high-water stage of established long-term cycles. The nature of long-term fluctuations in the water flow of rivers did not change in about half of the Yakutia rivers. One water body showed a further decrease in the water content from the norm, both in terms of duration and water flow rate. Meanwhile, specific water bodies exhibited extreme long-term fluctuations, which are predicted to be a reaction to global warming. Prior to the onset of significant warming in the region, the trends of long-term water discharge fluctuations were stationary. Then, the trends of certain rivers became non-stationary due to the reasons indicated above. On their own, quantitative characteristics are insufficient to evaluate actual changes in water regimens. Moreover, evaluations obtained in the absence of a trend analysis of specific long-term discharge fluctuations, which can only be performed via graphic visualization, are most likely to be inaccurate. Full article
(This article belongs to the Special Issue Flood Frequency and Inundation Modelling)
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