SUSPENDED SEDIMENT PREDICTION USING TIME SERIES AND ARTIFICIAL NEURAL NETWORKS MODELS (CASE STUDY: GHAZAGHLY STATION IN GORGANROUD RIVER)

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BARZEGARI FARIBA; DASTORANI MOHAMMAD TAGHI

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Journal: JOURNAL OF WATERSHED MANAGEMENT RESEARCH Year:2016 | Volume:6 | Issue:12 Page(s): 216-225

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Title

SUSPENDED SEDIMENT PREDICTION USING TIME SERIES AND ARTIFICIAL NEURAL NETWORKS MODELS (CASE STUDY: GHAZAGHLY STATION IN GORGANROUD RIVER)

Author(s)

BARZEGARI FARIBA | DASTORANI MOHAMMAD TAGHI | Issue Writer Certificate

Keywords

ARIMAQ2

SUSPENDED SEDIMENTQ2

GHAZAGHLYQ2

MARKOVQ2

MODELINGQ1

Abstract

Accurate estimation of SUSPENDED SEDIMENT in rivers is very important from different aspects including agriculture, soil conservation, shipping, dam construction and aquatic research. There are different methods for SUSPENDED SEDIMENT estimation. In the present study to evaluate the ability of time-series models including MARKOV and ARIMA in predicting SUSPENDED SEDIMENT and to compare their results to Artificial Neural Networks it was tried to use daily suspended data from GHAZAGHLY station of Gorganroud River, as average monthly values in Minitab 16 software and Neurosolutions 5, and finally SUSPENDED SEDIMENT was predicted for 111 months. Calculation of the error measurement indices including RMSE and NMSE based on the results of this study showed a good ability of Artificial Neural Network models in estimating average monthly SUSPENDED SEDIMENT. On the other hand between time series models, MARKOV model has better ability in estimating monthly SUSPENDED SEDIMENT in comparison to the ARIMA model.

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APA: Copy

BARZEGARI, FARIBA, & DASTORANI, MOHAMMAD TAGHI. (2016). SUSPENDED SEDIMENT PREDICTION USING TIME SERIES AND ARTIFICIAL NEURAL NETWORKS MODELS (CASE STUDY: GHAZAGHLY STATION IN GORGANROUD RIVER). JOURNAL OF WATERSHED MANAGEMENT RESEARCH, 6(12), 216-225. SID. https://sid.ir/paper/230340/en

Vancouver: Copy

BARZEGARI FARIBA, DASTORANI MOHAMMAD TAGHI. SUSPENDED SEDIMENT PREDICTION USING TIME SERIES AND ARTIFICIAL NEURAL NETWORKS MODELS (CASE STUDY: GHAZAGHLY STATION IN GORGANROUD RIVER). JOURNAL OF WATERSHED MANAGEMENT RESEARCH[Internet]. 2016;6(12):216-225. Available from: https://sid.ir/paper/230340/en

IEEE: Copy

FARIBA BARZEGARI, and MOHAMMAD TAGHI DASTORANI, “SUSPENDED SEDIMENT PREDICTION USING TIME SERIES AND ARTIFICIAL NEURAL NETWORKS MODELS (CASE STUDY: GHAZAGHLY STATION IN GORGANROUD RIVER),” JOURNAL OF WATERSHED MANAGEMENT RESEARCH, vol. 6, no. 12, pp. 216–225, 2016, [Online]. Available: https://sid.ir/paper/230340/en

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