Interpolating gaps in river suspended sediment records using artificial neural networks

Type of content
Conference Contributions - Published
Publisher's DOI/URI
Thesis discipline
Degree name
Publisher
University of Canterbury. Electrical and Computer Engineering
Journal Title
Journal ISSN
Volume Title
Language
Date
2014
Authors
Gorman, M.
Hicks, M.
Millane, R.P.
Abstract

Sediment transport is important in the management of rivers, catchments and floodplains. Sediment is monitored by measuring the suspended sediment concentration in rivers, but these measurements can be interrupted by various sensor malfunctions, leading to gaps in the record. An artificial neural network is developed for predicting suspended sediment concentration in these gaps, and is trained using high sampling rate contiguous records of quickflow and sediment concentration. The approach is evaluated by application to records from the Motueka River in the South Island of New Zealand.

Description
Citation
Gorman, M., Hicks, M., Millane, R.P. (2014) Interpolating gaps in river suspended sediment records using artificial neural networks. Hamilton, New Zealand: 21st Electronics New Zealand Conference, 20-21 Nov 2014. Proceedings, 78-82.
Keywords
rivers, suspended sediment, artificial neural networks, ANN
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Field of Research::09 - Engineering::0906 - Electrical and Electronic Engineering
Field of Research::05 - Environmental Sciences
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