Revised regional sediment yield prediction methodology for ungauged catchments in South Africa
Date
2017-06
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
South African Institution of Civil Engineering
Abstract
ENGLISH ABSTRACT: This paper presents the research on the revision of the regional probabilistic method (Rooseboom et al 1992) for the prediction of catchment sediment yields in South Africa. The determination of sediment yields using probabilistic or empirical methods is suitable for ungauged catchments in the absence of observed data. The prediction of sediment loads is a key component in the quest to deal with reservoir and river sedimentation which is a potential threat to the sustainability of water resources in southern Africa. The revision was necessitated by increased sediment data availability and improved data analysis tools. Ten new sediment yield regions were demarcated in South Africa and Lesotho. Two analytical approaches were developed, namely probabilistic and empirical. The probabilistic approach is applicable in sediment yield Regions 3, 6 and 9. The empirical approach is applicable in sediment yield Regions 1, 2, 4, 5, 7 and 8. The estimation of sediment yields in Region 10 (Lesotho Highlands) needs to be based on direct measurements and locally observed data since no adequate analysis of sediment loads was possible due to limited data. GIS and electronic portable document file (pdf) copies of maps were produced for the retrieval of catchment data.
Description
CITATION: Msadala, V. C. & Basson, G. R. 2017. Revised regional sediment yield prediction methodology for ungauged catchments in South Africa. Journal of the South African Institution of Civil Engineering, 59(2):28-36, doi:10.17159/2309-8775/2017/v59n2a4.
The original publication is available at http://www.scielo.org.za
The original publication is available at http://www.scielo.org.za
Keywords
Sedimentary basins, Catchment basins, Sedimentation analysis
Citation
Msadala, V. C. & Basson, G. R. 2017. Revised regional sediment yield prediction methodology for ungauged catchments in South Africa. Journal of the South African Institution of Civil Engineering, 59(2):28-36, doi:10.17159/2309-8775/2017/v59n2a4