Testing the accuracy of sediment transport equations using field data

In order to recommend the equations that can accurately predict sediment transport rate in channels, selected sediment transport equations (for estimating bed load and suspended load) are assessed using field data for 10 rivers around the world. The tested bed load equations are Einstein, Bagnold, D...

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Main Authors: Ali, Hydar Lafta, Mohammed, Thamer Ahmed, Yusuf, Badronnisa, Abdul Aziz, Azlan
Format: Article
Language:English
Published: Faculty of Civil Engineering, Universiti Teknologi Malaysia 2016
Online Access:http://psasir.upm.edu.my/id/eprint/48464/1/Testing%20the%20accuracy%20of%20sediment%20transport%20equations%20using%20field%20data.pdf
http://psasir.upm.edu.my/id/eprint/48464/
http://civil.utm.my/mjce/vol-28-special-issue-no-1-2016/
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.484642016-09-15T09:27:59Z http://psasir.upm.edu.my/id/eprint/48464/ Testing the accuracy of sediment transport equations using field data Ali, Hydar Lafta Mohammed, Thamer Ahmed Yusuf, Badronnisa Abdul Aziz, Azlan In order to recommend the equations that can accurately predict sediment transport rate in channels, selected sediment transport equations (for estimating bed load and suspended load) are assessed using field data for 10 rivers around the world. The tested bed load equations are Einstein, Bagnold, Du Boys, Shield, Meyer-Peter, Kalinskie, Meyer-Peter Muller, Schoklitsch, Van Rijin, and Cheng. Assessment show that Einstein and Meyer-Peter Muller equations have the least error in their prediction compared with the other tested equations. Based on the field data, each of Einstein and Meyer-Peter Muller equations gave the most accurate bed load estimations for three rivers while Schoklitsch equation and Du boys equation gave the most accurate bed load estimations for two rivers and one river respectively. The lowest values of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were obtained from the applying Einstein equation for estimating bed load for Oak Creek River and these values were found to be 0.02 and 0.04 respectively. On the other hand, the tested equations for predicting suspended load are Einstein, Bagnold, Lane and Kalinske, Brook, Chang, Simons and Richardson, and Van Rijin. Among the above tested equations, assessment show that Bagnold, Einstein and Van Rijin gave the most accurate estimation for the suspended load. The lowest values of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were obtained from applying Bagnold equation and these values were found to be 0.012 and 0.015 respectively. Faculty of Civil Engineering, Universiti Teknologi Malaysia 2016 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/48464/1/Testing%20the%20accuracy%20of%20sediment%20transport%20equations%20using%20field%20data.pdf Ali, Hydar Lafta and Mohammed, Thamer Ahmed and Yusuf, Badronnisa and Abdul Aziz, Azlan (2016) Testing the accuracy of sediment transport equations using field data. Malaysian Journal of Civil Engineering, 28 (spec.1). pp. 50-64. ISSN 1823-7843 http://civil.utm.my/mjce/vol-28-special-issue-no-1-2016/
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description In order to recommend the equations that can accurately predict sediment transport rate in channels, selected sediment transport equations (for estimating bed load and suspended load) are assessed using field data for 10 rivers around the world. The tested bed load equations are Einstein, Bagnold, Du Boys, Shield, Meyer-Peter, Kalinskie, Meyer-Peter Muller, Schoklitsch, Van Rijin, and Cheng. Assessment show that Einstein and Meyer-Peter Muller equations have the least error in their prediction compared with the other tested equations. Based on the field data, each of Einstein and Meyer-Peter Muller equations gave the most accurate bed load estimations for three rivers while Schoklitsch equation and Du boys equation gave the most accurate bed load estimations for two rivers and one river respectively. The lowest values of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were obtained from the applying Einstein equation for estimating bed load for Oak Creek River and these values were found to be 0.02 and 0.04 respectively. On the other hand, the tested equations for predicting suspended load are Einstein, Bagnold, Lane and Kalinske, Brook, Chang, Simons and Richardson, and Van Rijin. Among the above tested equations, assessment show that Bagnold, Einstein and Van Rijin gave the most accurate estimation for the suspended load. The lowest values of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were obtained from applying Bagnold equation and these values were found to be 0.012 and 0.015 respectively.
format Article
author Ali, Hydar Lafta
Mohammed, Thamer Ahmed
Yusuf, Badronnisa
Abdul Aziz, Azlan
spellingShingle Ali, Hydar Lafta
Mohammed, Thamer Ahmed
Yusuf, Badronnisa
Abdul Aziz, Azlan
Testing the accuracy of sediment transport equations using field data
author_facet Ali, Hydar Lafta
Mohammed, Thamer Ahmed
Yusuf, Badronnisa
Abdul Aziz, Azlan
author_sort Ali, Hydar Lafta
title Testing the accuracy of sediment transport equations using field data
title_short Testing the accuracy of sediment transport equations using field data
title_full Testing the accuracy of sediment transport equations using field data
title_fullStr Testing the accuracy of sediment transport equations using field data
title_full_unstemmed Testing the accuracy of sediment transport equations using field data
title_sort testing the accuracy of sediment transport equations using field data
publisher Faculty of Civil Engineering, Universiti Teknologi Malaysia
publishDate 2016
url http://psasir.upm.edu.my/id/eprint/48464/1/Testing%20the%20accuracy%20of%20sediment%20transport%20equations%20using%20field%20data.pdf
http://psasir.upm.edu.my/id/eprint/48464/
http://civil.utm.my/mjce/vol-28-special-issue-no-1-2016/
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