Special Issue "Hydrological Modeling and Evaluation for Flood Risk Management"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences and Geography".

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 4773

Special Issue Editors

Dr. Agnieszka Indiana Olbert
E-Mail Website
Guest Editor
National University of Ireland Galway, College of Engineering and Informatics and the Ryan Institute for Environmental, Galway, Ireland
Interests: hydrodynamic modeling; flooding; climate change; European continental shelf; extreme events
Dr. Bartosz Kaźmierczak
E-Mail Website
Guest Editor
Department of Water Supply and Sewerage Systems, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, 50-370 Wrocław, Poland
Interests: urban hydrology; stormwater drainage system; climate change; mathematical modeling
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Special Issue Information

Dear Colleagues,

Floods can be considered to be one of the most devastating natural hazards, with severe socioeconomic and environmental impacts on the affected areas. In the future, flood risk will increase as a consequence of several factors including population growth in flood-prone areas, decaying or poorly engineered flood control infrastructure, and climate change that leads to increases in sea level, rainfall, and storm winds. The dynamics of flooding can be very complex, particularly when a flood results from a particular combination of multiple process drivers. Understanding flood mechanisms and predicting extents of inundation and potential damage are important issues in flood risk management. Generation of flood inundation maps for a range of flood scenarios may help us to identify flood-prone areas and as such provide reliable information to the public about the flood risk. This can be achieved by using hydrological modeling methods that incorporate flood dynamics and include multiple drivers in an integrated manner. As such, hydrological modeling is complex and requires an optimal balance between initial/boundary inputs, computational effort, and model efficiency.

Technologies exist for producing and delivering flood assessments, such as LIDAR data and GIS for mapping topography, high-resolution bathymetry data, dense networks of observational data, and a range of modeling frameworks, yet these tools remain rarely integrated in assessment of flood extents. More recently, approaches of varying complexity based on computer models have been used to assess flood inundation and flood risks; they range from the most simplistic static approaches to quite complex dynamic hydraulic models.

This Special Issue welcomes multidisciplinary studies that aim to showcase innovation in numerical techniques for improved prediction of the dynamics and extent of flooding in a reliable and effective manner. In this context, researchers of various disciplines, including coastal and hydraulic engineering, hydrology, meteorology, remote sensing, geography, and geotechnics, are invited to explore advances in analysis of model prediction skill (e.g., uncertainty quantification, sensitivity analysis, data assimilation, machine learning, multi-scale modeling) and/or integration of multiple flood drivers into hydrological modeling.

Dr. Agnieszka Indiana Olbert
Dr. Bartosz Kaźmierczak
Guest Editors

Manuscript Submission Information

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Keywords

  • Hydrological/hydrodynamic modelling
  • Coastal and/or fluvial flood mechanisms
  • Compounds events
  • Extreme event analysis and flood probability
  • Model uncertainty, data assimilation, machine learning
  • Remote sensing
  • Multi-scale and high-resolution modelling
  • Flood risk management

Published Papers (4 papers)

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Research

Article
Evaluation of the Effect of Hamao Detention Pond on Excess Runoff from the Abukuma River in 2019 and Simple Remodeling of the Pond to Increase Its Flood Control Function
Appl. Sci. 2022, 12(2), 729; https://doi.org/10.3390/app12020729 - 12 Jan 2022
Viewed by 225
Abstract
Due to the recent increase in the intensity of rainstorms, the Japanese government has announced a new policy of flexible flood mitigation measures that presupposes the release of water volumes exceeding the river channel capacity onto floodplains. However, due to the limited amount [...] Read more.
Due to the recent increase in the intensity of rainstorms, the Japanese government has announced a new policy of flexible flood mitigation measures that presupposes the release of water volumes exceeding the river channel capacity onto floodplains. However, due to the limited amount of quantitative measurement data on excess runoff, it will take time to formulate planning standards for remodeling and newly constructing flood control facilities reasonable enough under current budgetary constraints. In this study, the capacity shortage of a flood detention pond was evaluated against the excess runoff from a severe 2019 flood event by combining the fragmentary measurement data with a numerical flow simulation. Although the numerical model was a rather simple one commonly used for rough estimation of inundation areas in Japan, the results were overall consistent with the observations. Next, in accordance with the new policy, an inexpensive remodeling of the detention basin, which was designed according to conventional standards, was simulated; the upstream side of the surrounding embankment was removed so that excess water flowed up onto the floodplain gradually. Numerical experiments using the simple model indicated that the proposed remodeling increased the effectiveness of flood control remarkably, even for floods greater than the 2019 flood, without much inundation damage to upstream villages. Full article
(This article belongs to the Special Issue Hydrological Modeling and Evaluation for Flood Risk Management)
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Article
Application of PCSWMM for the 1-D and 1-D–2-D Modeling of Urban Flooding in Damansara Catchment, Malaysia
Appl. Sci. 2021, 11(19), 9300; https://doi.org/10.3390/app11199300 - 07 Oct 2021
Cited by 3 | Viewed by 786
Abstract
Coupled with climate change, the urbanization-driven increase in the frequency and intensity of floods can be seen in both developing and developed countries, and Malaysia is no exemption. As part of flood hazard mitigation, this study aimed to simulate the urban flood scenarios [...] Read more.
Coupled with climate change, the urbanization-driven increase in the frequency and intensity of floods can be seen in both developing and developed countries, and Malaysia is no exemption. As part of flood hazard mitigation, this study aimed to simulate the urban flood scenarios in Malaysia’s urbanized catchments. The flood simulation was performed using the Personal Computer Storm Water Management Model (PCSWMM) modeling of the Damansara catchment as a case study. An integrated hydrologic-hydraulic model was developed for the 1-D river flow modeling and 1-D–2-D drainage overflow modeling. The reliability of the 1-D river flow model was confirmed through the calibration and validation, in which the water level in TTDI Jaya was satisfactorily predicted, supported by the coefficient of determination (R2), Nash–Sutcliffe model efficiency coefficient (NSE), and relative error (RE). The performance of the 1-D–2-D model was further demonstrated based on the flood depth, extent, and risk caused by the drainage overflow. Two scenarios were tested, and the comparison results showed that the current drainage effectively reduced the drainage overflow due to the increased size of drains compared to the historic drainage in 2015. The procedure and findings of this study could serve as references for the application in flood mitigation planning worldwide, especially for developing countries. Full article
(This article belongs to the Special Issue Hydrological Modeling and Evaluation for Flood Risk Management)
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Article
Probabilistic Flood Hazard Maps from Monte Carlo Derived Peak Flow Values—An Application to Flood Risk Management in Zamora City (Spain)
Appl. Sci. 2021, 11(14), 6629; https://doi.org/10.3390/app11146629 - 19 Jul 2021
Viewed by 1127
Abstract
All flood hazard and risk assessment suffer from a certain degree of uncertainty due to multiple factors, such as flood frequency analysis, hydrodynamic model calibration, or flood damage (magnitude–damage functions) models. The uncertainty linked to the flood frequency analysis is one of the [...] Read more.
All flood hazard and risk assessment suffer from a certain degree of uncertainty due to multiple factors, such as flood frequency analysis, hydrodynamic model calibration, or flood damage (magnitude–damage functions) models. The uncertainty linked to the flood frequency analysis is one of the most important factors (previous and present estimation point to 40%). Flood frequency analysis uncertainty has been approached from different points of view, such as the application of complex statistical models, the regionalization processes of peak flows, or the inclusion of non-systematic data. Here, we present an achievable approach to defining the uncertainty linked to flood frequency analysis by using the Monte Carlo method. Using the city of Zamora as the study site, the uncertainty is delimited by confidence intervals of a peak flow quantile of a 500-year return period. Probabilistic maps are derived from hydrodynamic results, and further analysis include flood hazard maps for human loss of stability and vehicle damage. Although the effect of this uncertainty is conditioned by the shape of the terrain, the results obtained may allow managers to achieve more consistent land-use planning. All those Zamora city results point out the probable underestimation of flood hazard (the higher hazard areas increase around 20%) and risk when the uncertainty analysis is not considered, thus limiting the efficiency of flood risk management tasks. Full article
(This article belongs to the Special Issue Hydrological Modeling and Evaluation for Flood Risk Management)
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Article
Hydrological Analysis of Extreme Rain Events in a Medium-Sized Basin
Appl. Sci. 2021, 11(11), 4901; https://doi.org/10.3390/app11114901 - 26 May 2021
Cited by 2 | Viewed by 1124
Abstract
The hydrological response of a medium-sized watershed with both rural and urban characteristics was investigated through event-based modeling. Different meteorological event conditions were examined, such as events of high precipitation intensity, double hydrological peak, and mainly normal to wet antecedent moisture conditions. Analysis [...] Read more.
The hydrological response of a medium-sized watershed with both rural and urban characteristics was investigated through event-based modeling. Different meteorological event conditions were examined, such as events of high precipitation intensity, double hydrological peak, and mainly normal to wet antecedent moisture conditions. Analysis of the hydrometric features of the precipitation events was conducted by comparing the different rainfall time intervals, the total volume of water, and the precedent soil moisture. Parameter model calibration and validation were performed for rainfall events under similar conditions, examined in pairs, in order to verify two hydrological models, the lumped HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System model) and the semi-distributed HBV-light (a recent version of Hydrologiska Byråns Vattenbalansavdelning model), at the exit of six individual gauged sub-basins. Model verification was achieved by using the Nash–Sutcliffe efficiency and volume error index. Different time of concentration (Tc) formulas are better applied to the sub-watersheds with respect to the dominant land uses, classifying the Tc among the most sensitive parameters that influence the time of appearance and the magnitude of the peak modeled flow through the HEC-HMS model. The maximum water content of the soil box (FC) affects most the peak flow via the HBV-light model, whereas the MAXBAS parameter has the greatest effect on the displayed time of peak discharge. The modeling results show that the HBV-light performed better in the events that had less precipitation volume compared to their pairs. The event with the higher total precipitated water produced better results with the HEC-HMS model, whereas the rest of the two high precipitation events performed satisfactorily with both models. April to July is a flood hazard period that will be worsened with the effect of climate change. The suggested calibrated parameters for severe precipitation events can be used for the prediction of future events with similar features. The above results can be used in the water resources management of the basin. Full article
(This article belongs to the Special Issue Hydrological Modeling and Evaluation for Flood Risk Management)
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