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Integration of frequency analysis and HEC-RAS for probabilistic flood hazard mapping.

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Title: Integration of frequency analysis and HEC-RAS for probabilistic flood hazard mapping.
Authors: Shaikh, Mohamedmaroof P (AUTHOR), Kumar, Vijendra (AUTHOR) vijendra.kumar@mitwpu.edu.in, Yadav, Sanjaykumar M (AUTHOR), Manekar, Vivek L (AUTHOR), Mehta, Darshan (AUTHOR), Deshmukh, Arpan (AUTHOR)
Source: Proceedings of ICE: Water Management. Aug2025, Vol. 178 Issue 4, p237-252. 16p.
Subjects: Flood risk, Floods, Frequency-domain analysis, Climate change, Extreme value theory, Risk assessment, Hydraulic models
Geographic Terms: India
Abstract: Climate change is altering flood patterns in India, emphasising accurate flood assessment for effective resource management through flood frequency analysis. This study evaluates three probability distribution methods: log-normal, Gumbel's extreme value (GEV), and log-Pearson type 3 (LP3) using annual maximum discharge data (1973–2018) from the Dhanera gauging station in the Rel River basin. The most suitable model is determined by way of Kolmogorov–Smirnov, Anderson–Darling and chi-squared tests at a 5% significance level, with GEV identified as the best fit. Predicted peak discharge values for return periods of 2, 5, 10, 25, 50, 100 and 200 years were integrated into a two-dimensional hydraulic model, validated against observed flood depths from July 2017. Maximum discharge and averaged digital elevation model data were utilised in the Hydrologic Engineering Center river analysis system (HEC-RAS) model to predict inundation, processed with ArcGIS to create flood inundation maps. The 200 year return period simulation revealed areas also affected by the historic 2017 floods. This research offers crucial insights into flood depths and characteristics, aiding government authorities and stakeholders in making informed decisions for risk-based mitigation post the floods of 2015 and 2017. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of ICE: Water Management is the property of Thomas Telford Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 188672424
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Integration of frequency analysis and HEC-RAS for probabilistic flood hazard mapping.
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  Data: <searchLink fieldCode="DE" term="%22Flood+risk%22">Flood risk</searchLink><br /><searchLink fieldCode="DE" term="%22Floods%22">Floods</searchLink><br /><searchLink fieldCode="DE" term="%22Frequency-domain+analysis%22">Frequency-domain analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Extreme+value+theory%22">Extreme value theory</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Hydraulic+models%22">Hydraulic models</searchLink>
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  Data: Climate change is altering flood patterns in India, emphasising accurate flood assessment for effective resource management through flood frequency analysis. This study evaluates three probability distribution methods: log-normal, Gumbel's extreme value (GEV), and log-Pearson type 3 (LP3) using annual maximum discharge data (1973–2018) from the Dhanera gauging station in the Rel River basin. The most suitable model is determined by way of Kolmogorov–Smirnov, Anderson–Darling and chi-squared tests at a 5% significance level, with GEV identified as the best fit. Predicted peak discharge values for return periods of 2, 5, 10, 25, 50, 100 and 200 years were integrated into a two-dimensional hydraulic model, validated against observed flood depths from July 2017. Maximum discharge and averaged digital elevation model data were utilised in the Hydrologic Engineering Center river analysis system (HEC-RAS) model to predict inundation, processed with ArcGIS to create flood inundation maps. The 200 year return period simulation revealed areas also affected by the historic 2017 floods. This research offers crucial insights into flood depths and characteristics, aiding government authorities and stakeholders in making informed decisions for risk-based mitigation post the floods of 2015 and 2017. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Proceedings of ICE: Water Management is the property of Thomas Telford Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1680/jwama.24.00046
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 16
        StartPage: 237
    Subjects:
      – SubjectFull: Flood risk
        Type: general
      – SubjectFull: Floods
        Type: general
      – SubjectFull: Frequency-domain analysis
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Extreme value theory
        Type: general
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Hydraulic models
        Type: general
      – SubjectFull: India
        Type: general
    Titles:
      – TitleFull: Integration of frequency analysis and HEC-RAS for probabilistic flood hazard mapping.
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            NameFull: Shaikh, Mohamedmaroof P
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            NameFull: Kumar, Vijendra
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            NameFull: Yadav, Sanjaykumar M
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            NameFull: Manekar, Vivek L
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            NameFull: Mehta, Darshan
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            – D: 01
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
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              Value: 178
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