Version 1
: Received: 5 January 2018 / Approved: 8 January 2018 / Online: 8 January 2018 (04:47:41 CET)
How to cite:
Temiz, T.; Doğan, E.; Öner, A.; Opan, M.; Sönmez, O. Estimation of Suspended Sediment Transport Amount in the Streams Flowing into the Sapanca Lake Basin. Preprints2018, 2018010044. https://doi.org/10.20944/preprints201801.0044.v1
Temiz, T.; Doğan, E.; Öner, A.; Opan, M.; Sönmez, O. Estimation of Suspended Sediment Transport Amount in the Streams Flowing into the Sapanca Lake Basin. Preprints 2018, 2018010044. https://doi.org/10.20944/preprints201801.0044.v1
Temiz, T.; Doğan, E.; Öner, A.; Opan, M.; Sönmez, O. Estimation of Suspended Sediment Transport Amount in the Streams Flowing into the Sapanca Lake Basin. Preprints2018, 2018010044. https://doi.org/10.20944/preprints201801.0044.v1
APA Style
Temiz, T., Doğan, E., Öner, A., Opan, M., & Sönmez, O. (2018). Estimation of Suspended Sediment Transport Amount in the Streams Flowing into the Sapanca Lake Basin. Preprints. https://doi.org/10.20944/preprints201801.0044.v1
Chicago/Turabian Style
Temiz, T., Mücahit Opan and Osman Sönmez. 2018 "Estimation of Suspended Sediment Transport Amount in the Streams Flowing into the Sapanca Lake Basin" Preprints. https://doi.org/10.20944/preprints201801.0044.v1
Abstract
This paper is about to estimate the suspended sediment transport amount in the streams flowing into the Sapanca Lake Basin. There are 12 subsidiary streams flowing into the Sapanca Lake Basin. With the aim of estimating the suspended sediment transport in 2012-204 in these subsidiary streams, measurements belonging the parameters such as level, cross sectioning, flow rate, temperature and suspended sediment were made monthly. Along the measurement period, weather conditions were above seasonal normal and precipitations decreased. In order to estimate the suspended sediment amount by using results of the measurement obtained, Artificial Neuron Network (ANN), Sediment Rating Curve (SRC) and Multiple Linear Regression (MLR) models were used for different scenarios. It was seen that artificial neuron networks yielded the most accurate results among the models.
Keywords
Sapanca Lake Basin; suspended sediment amount; artificial neuron networks; sediment rating curve; multiple linear regression
Subject
Engineering, Civil Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
