EFFECTS OF WATER LEVEL AND FLOW DISCHARGE FLUCTUATIONS ON SUSPENDED SEDIMENT LOAD USING ARTIFICIAL NEURAL NETWORKS (CASE STUDY: AHAR CHAY RIVER)

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HOSSEINZADEH DALIR A.; FARSADIZADEH D.; GHORBANI M.A.

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Journal: WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE) Year:2010 | Volume:19.1 | Issue:2 Page(s): 23-34

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Title

EFFECTS OF WATER LEVEL AND FLOW DISCHARGE FLUCTUATIONS ON SUSPENDED SEDIMENT LOAD USING ARTIFICIAL NEURAL NETWORKS (CASE STUDY: AHAR CHAY RIVER)

Author(s)

HOSSEINZADEH DALIR A. | FARSADIZADEH D. | GHORBANI M.A. | Issue Writer Certificate

Keywords

ARTIFICIAL NEURAL NETWORKSQ4

AHAR CHAYQ3

DISCHARGEQ3

SUSPENDED LOADQ4

WATER LEVEL FLACTUATIONSQ4

Abstract

Evaluation of suspended sediments and parameters affecting them is of great importance in river engineering. In this research the effects of water level and flow DISCHARGE fluctuations on suspended sediment load were studied using ARTIFICIAL NEURAL NETWORKS (ANNs). AHAR CHAY river basin, located in north of Iran, with area totaling about 2400 km2 as a sub-basin of Aras river was chosen. Data from Tazeh-Kand, Orang, Casein, Oshdologh and Bermice (upstream of Sattarkhan dam) stations were employed in ANNs method and the suspended sediment were predicted. The results showed that, SUSPENDED LOAD forecasted by water level data had low accuracy than that forecasted by the flow DISCHARGE. The maximum and minimum coefficients of correlation for water level data were 0.69 and 0.08 in Orang and Oshdologh stations, respectively. The corresponding values for flow DISCHARGE were 0.84 in Oshdologh and 0.7 in Bermice. The main reason for the low coefficient of fittness in some stations probably were due to shortage of data, lack of temporal sequence and inaccuracy of water level fluctuations compared to the flow measurements. It appeared that, in this basin, in moving from high to low land with increasing DISCHARGE and sediment rates, the results of ANN became more reliable. Water level fluctuations did not show this trend.

Cites

PERFORMANCE EVALUATION OF M5 TREE MODEL AND SUPPORT VECTOR REGRESSION METHODS IN SUSPENDED SEDIMENT LOAD MODELING

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APA: Copy

HOSSEINZADEH DALIR, A., FARSADIZADEH, D., & GHORBANI, M.A.. (2010). EFFECTS OF WATER LEVEL AND FLOW DISCHARGE FLUCTUATIONS ON SUSPENDED SEDIMENT LOAD USING ARTIFICIAL NEURAL NETWORKS (CASE STUDY: AHAR CHAY RIVER). WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), 19.1(2), 23-34. SID. https://sid.ir/paper/147821/en

Vancouver: Copy

HOSSEINZADEH DALIR A., FARSADIZADEH D., GHORBANI M.A.. EFFECTS OF WATER LEVEL AND FLOW DISCHARGE FLUCTUATIONS ON SUSPENDED SEDIMENT LOAD USING ARTIFICIAL NEURAL NETWORKS (CASE STUDY: AHAR CHAY RIVER). WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE)[Internet]. 2010;19.1(2):23-34. Available from: https://sid.ir/paper/147821/en

IEEE: Copy

A. HOSSEINZADEH DALIR, D. FARSADIZADEH, and M.A. GHORBANI, “EFFECTS OF WATER LEVEL AND FLOW DISCHARGE FLUCTUATIONS ON SUSPENDED SEDIMENT LOAD USING ARTIFICIAL NEURAL NETWORKS (CASE STUDY: AHAR CHAY RIVER),” WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), vol. 19.1, no. 2, pp. 23–34, 2010, [Online]. Available: https://sid.ir/paper/147821/en

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