A linear reservoir cell model is presented which is proposed as a good candidate for real
time flood forecasting applications. The model is designed to be computationally efficient
since it should be able to run on a P.C and must operate online in real time. The model
parameters and forecasts can be easily updated in order to allow for a more accurate
forecast based on real time observations of streamflow and rainfall.
The final model, once calibrated, should be able to operate effectively without requiring
highly skilled and knowledgeable operators. Thus it is hoped to provide a tool which can be
incorporated into an early warning system for mitigation of flood damage, giving water
resources managers the extra lead-time to implement any contingency plans which may be
neccssary to ensure the safety of people and prevent damage to property.
The use of linear models for describing hydrological systems is not new, however the
model presented in this thesis departs from previous implementations. A particular
departure is the novel method used in the conversion of observed to effective rainlfall. The
physical processes that result in the rainfall to runoff conversion are non-linear in nature.
Most of the significant non-linearity results from rainfall losses, which occur largely due to
evaporation and human extraction. The remaining rainfall is converted to runoff. These
losses are particularly significant in the South African climate and in some regions may be
as much as 70-90 % of the total observed rainfall. Loss parameters are an integral part of
the model formulation and allow for losses to be dealt with directly. Thus, input to the
model is observed rainfall and not the "effective" rainfall normally associated with
conceptual catchment models.
The model is formulated in Finite Difference form similar to an Auto Regressive Moving
Average (ARMA) model; it is this formulation which provides the required computational
efficiency. The ARMA equation is a discretely coincident form of the State-Space
equations that govern the response of an arrangement of linear reservoirs. This results in a
functional relationship between the reservoir response constants and the ARMA
coefficients, which guarantees stationarity of the ARMA model. / Thesis (M.Sc.Eng.)-University of Natal, Durban, 2001.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/5395 |
| Date | January 2001 |
| Creators | Sinclair, D S. |
| Contributors | Pegram, G.G.S. |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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