Estimation of Areal Reduction Factors in South Africa, Part 2: Application and validation at catchment level.
Saved in:
| Title: | Estimation of Areal Reduction Factors in South Africa, Part 2: Application and validation at catchment level. |
|---|---|
| Authors: | Pietersen, J. P. J.1 jpietersen@cut.ac.za, Gericke, O. J.2 jgericke@cut.ac.za, Smithers, J. C.3,4 smithers@ukzn.ac.za |
| Source: | Journal of the South African Institution of Civil Engineering. Dec2024, Vol. 66 Issue 4, p37-47. 11p. |
| Subjects: | Rainfall, Computer input design, Empirical research, Runoff, Floods |
| Abstract: | Various empirical methods have evolved over the years in South Africa to estimate either design floods, design rainfall, catchment response time, and/or Areal Reduction Factors (ARFs). The verification of any empirical method requires the use of observed data not used during the calibration process, while observed data is also required for validation purposes. In the case of ARFs, which are used to convert average design point rainfall depths to an areal (catchment) design rainfall depth, all the calibration/verification data sets remain only estimated sample values of design rainfall. Subsequently, this paper presents an independent application and validation of the regional geographically-centred ARF method (Pietersen 2023) against the currently recommended geographically-centred ARF method (Alexander 2001) by incorporating the different ARF estimates into the Rational Method (RM) to highlight the impact thereof on the resulting flood estimates. In applying a ranking-based goodness-of-fit selection procedure, the RM in combination with the newly derived regional geographically-centred ARF method (Pietersen 2023) resulted in the best deterministic flood estimates when compared to the at-site statistical flood peaks. Apart from the ARFs, catchment response time, design rainfall, and weighted runoff coefficients are all regarded as key input parameters for design flood estimation in ungauged catchments. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of the South African Institution of Civil Engineering is the property of South African Institution of Civil Engineering (SAICE) 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 |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 183139685 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Estimation of Areal Reduction Factors in South Africa, Part 2: Application and validation at catchment level. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Pietersen%2C+J%2E+P%2E+J%2E%22">Pietersen, J. P. J.</searchLink><relatesTo>1</relatesTo><i> jpietersen@cut.ac.za</i><br /><searchLink fieldCode="AR" term="%22Gericke%2C+O%2E+J%2E%22">Gericke, O. J.</searchLink><relatesTo>2</relatesTo><i> jgericke@cut.ac.za</i><br /><searchLink fieldCode="AR" term="%22Smithers%2C+J%2E+C%2E%22">Smithers, J. C.</searchLink><relatesTo>3,4</relatesTo><i> smithers@ukzn.ac.za</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+the+South+African+Institution+of+Civil+Engineering%22">Journal of the South African Institution of Civil Engineering</searchLink>. Dec2024, Vol. 66 Issue 4, p37-47. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Rainfall%22">Rainfall</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+input+design%22">Computer input design</searchLink><br /><searchLink fieldCode="DE" term="%22Empirical+research%22">Empirical research</searchLink><br /><searchLink fieldCode="DE" term="%22Runoff%22">Runoff</searchLink><br /><searchLink fieldCode="DE" term="%22Floods%22">Floods</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Various empirical methods have evolved over the years in South Africa to estimate either design floods, design rainfall, catchment response time, and/or Areal Reduction Factors (ARFs). The verification of any empirical method requires the use of observed data not used during the calibration process, while observed data is also required for validation purposes. In the case of ARFs, which are used to convert average design point rainfall depths to an areal (catchment) design rainfall depth, all the calibration/verification data sets remain only estimated sample values of design rainfall. Subsequently, this paper presents an independent application and validation of the regional geographically-centred ARF method (Pietersen 2023) against the currently recommended geographically-centred ARF method (Alexander 2001) by incorporating the different ARF estimates into the Rational Method (RM) to highlight the impact thereof on the resulting flood estimates. In applying a ranking-based goodness-of-fit selection procedure, the RM in combination with the newly derived regional geographically-centred ARF method (Pietersen 2023) resulted in the best deterministic flood estimates when compared to the at-site statistical flood peaks. Apart from the ARFs, catchment response time, design rainfall, and weighted runoff coefficients are all regarded as key input parameters for design flood estimation in ungauged catchments. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of the South African Institution of Civil Engineering is the property of South African Institution of Civil Engineering (SAICE) 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=183139685 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.17159/2309-8775/2024/v66n4a4 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 37 Subjects: – SubjectFull: Rainfall Type: general – SubjectFull: Computer input design Type: general – SubjectFull: Empirical research Type: general – SubjectFull: Runoff Type: general – SubjectFull: Floods Type: general Titles: – TitleFull: Estimation of Areal Reduction Factors in South Africa, Part 2: Application and validation at catchment level. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Pietersen, J. P. J. – PersonEntity: Name: NameFull: Gericke, O. J. – PersonEntity: Name: NameFull: Smithers, J. C. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 10212019 Numbering: – Type: volume Value: 66 – Type: issue Value: 4 Titles: – TitleFull: Journal of the South African Institution of Civil Engineering Type: main |
| ResultId | 1 |
