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ABSTRACT
Problems associated with sediments have become major issue for years
as it affects not only the morphology of the rivers but the cause of
flooding in several areas. Knowledge on sediment prediction is
important in solving river engineering problems. In lieu of this, a
study on the transport of sediments in natural rivers was conducted
to observe both the bed sediment load and suspended sediment load
with flow. The objective is to develop a sediment transport equation
using hydraulic and sediment data extracted from 12 rivers. A total
of 346 data were used in the analysis and validation works.
Initially an attempt was made to evaluate the nine most commonly
used equations. However, these equations failed to predict sediment
transport to a desired accuracy. The poor performance resulted from
the difference in sediment availability from the source, composition
of sediments and river configurations. Some of the equations were
physically based and derived using flume data. Naturally the
conditions in the laboratory are not the same as in natural rivers.
Thus, a new sediment transport equation is necessary for use in
Malaysian rivers. Three statistical techniques namely the multiple
linear regression, robust regression and artificial neural network
were used to determine the functional relationship between the
sediment discharge variables. Subsequently a total of 71 equations
were derived. Analysis showed that the proposed equation derived
using multiple linear regression gave the best prediction with an
overall accuracy of 67.35%. Thus the proposed regression equation
for Malaysian rivers under the flow range and sediment properties
can be defined as a function of relative roughness on the bed, ratio
of shear velocity and fall velocity, Froude Number and the ratio of
shear velocity and average velocity. Examples of stable channel
design using the proposed equations are also given.
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