Published Article / Although deterministic models still dominate hydrological modelling, there is a notable paradigm shift in catchment response modelling. An approach to represent the daily rainfall-flow (R-F) relationship using Data-Based Mechanistic (DBM) modelling is presented. DBM modelling is an inductive empirical transfer function (TF) approach relating input to output. The study used secondary data from the Department of Water Affairs and Forestry for the Upper Vaal water management area at station C1H007. The R-F model identification and optimisation was implemented in the CAPTAIN Toolbox in MATLAB. The best estimated R-F model was a 2nd order TF with an input lag of one day and R 2T= 56%. In mechanistic interpretation, three parallel flow pathways were discerned; the fast flow, slow flow and the loss component each constituting 49.8%, 24% and 26.2% of the modelled flow respectively. The study demonstrates that the approach adopted herein produces reasonably satisfactory results with a minimum of the readily available catchment data.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:cut/oai:ir.cut.ac.za:11462/497 |
| Date | January 2008 |
| Creators | Ochieng, G.M., Otieno, F.A.O. |
| Contributors | Central University of Technology, Free State, Bloemfontein |
| Publisher | Journal for New Generation Sciences, Vol 6, Issue 1: Central University of Technology, Free State, Bloemfontein |
| Source Sets | South African National ETD Portal |
| Language | en_US |
| Detected Language | English |
| Type | Article |
| Format | 360 179 bytes, 1 file, Application/PDF |
| Rights | Central University of Technology, Free State, Bloemfontein |
| Relation | Journal for New Generation Sciences;Vol 6, Issue 1 |
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