Bedload Transport Of Small Rivers In Malaysia
Bedload transport is an essential component of river dynamics and estimation of bedload transport rate is important for practical computations of river morphological variations because the transport of sediment through river channels has major effects on public safety, water resources manageme...
Saved in:
Main Author: | |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | http://eprints.usm.my/44031/1/Zahra%20Zangeneh%20Sirdari24.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Bedload transport is an essential component of river dynamics and estimation
of bedload transport rate is important for practical computations of river
morphological variations because the transport of sediment through river channels
has major effects on public safety, water resources management and environmental
sustainability. Numerous well-known bedload equations are derived from limited
flume experiments or field conditions. These time-consuming equations, based on
the relationship between the reliability and representativeness of the data utilized in
defining variables and constants, require complex parameters to estimate bedload
transport. Thus, a new simple equation based on a balance between simplicity and
accuracy is necessary for using in small rivers. In this study the easily accessible data
including flow discharge, water depth, slope, and surface grain diameter d50 from the
three small rivers in Malaysia used to predict bedload transport. Genetic
programming (GP) and artificial neural network (ANN) models that are particularly
useful in data interpretation without any restriction to an extensive database are
presented as complementary tools for modelling bed load transport in small streams.
The ability of GP and ANN as precipitation predictive tools showed to be acceptable.
The developed models demonstrate higher performance with an overall accuracy of
97% for ANN and 93% for GP compared with other traditional methods and
empirical equations. |
---|