Skip to main content

Estimating extreme flood magnitude in bedrock-influenced channels using representative reach-based channel resistance data

Buy Article:

$43.00 plus tax (Refund Policy)

Abstract

Extreme flood events are considered by many researchers to be very important in controlling the development of semi-arid bedrock-influenced river systems. Accurate gauging of such events is often impossible, however, as gauges are drowned and often damaged during the event. A methodology for estimating flood discharge for bedrock-influenced channels is presented that reconstructs hydrometric characteristics of the peak flow and relates these to the roughness character of the river channel in question. The method is evaluated using peak water-surface slope data relating to the extreme floods of February 2000 along the Sabie and Letaba rivers, located respectively in the Mpumalanga and Northern Provinces, South Africa. The data, in the form of strandline measurements, were taken at hydraulically relevant points along the long profile of both rivers. The resultant data are utilised together with published high flow channel resistance figures, based on the channel morphology of the Sabie and Letaba rivers, to generate peak flow estimates for a number of locations along both rivers. Comparisons are made between the frictional discharge peak flow estimates, velocity-area and hydrologic estimates of peak flow. These comparisons indicate that the method can produce discharge estimates with an accuracy of ±10% and ± 35% respectively.
No References
No Citations
No Supplementary Data
No Data/Media
No Metrics

Keywords: bedrock channel; channel roughness; flood; peak flow estimation; semi-arid river

Document Type: Research Article

Affiliations: 1: University of Salford, Manchester, UK 2: University of Newcastle, Newcastle upon Tyne, UK 3: University of the Witwatersrand, Johannesburg, South Africa

Publication date: 2003-03-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more