TECHNICAL NOTE: HOURLY RIVER FLOW FORECAST OF AHARCHAY RIVER USING MACHINE LEARNING METHODS

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SATTARI MOHAMMAD TAGHI; ABDOLLAH POURAZAD MOHAMMADREZA; MIRABBASI NAJAFABADI RASOUL

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Journal: WATERSHED ENGINEERING AND MANAGEMENT Year:2016 | Volume:8 | Issue:1 Page(s): 115-127

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Information Journal Paper

Title

TECHNICAL NOTE: HOURLY RIVER FLOW FORECAST OF AHARCHAY RIVER USING MACHINE LEARNING METHODS

Author(s)

SATTARI MOHAMMAD TAGHI | ABDOLLAH POURAZAD MOHAMMADREZA | MIRABBASI NAJAFABADI RASOUL | Issue Writer Certificate

Keywords

DATA MININGQ1

DISCHARGEQ1

EAST AZERBAIJANQ1

M5 MODEL TREESQ1

SUPPORT VECTOR MACHINE (SVM)Q1

Abstract

Floods are the main natural disasters that produce serious agricultural, environmental, and socioeconomical damages in many parts of the world. Accurate estimation of river flow in streams can have a significant role in water resources management and in protection from possible damages. This study aims to compare the abilities of Support Vector Machine (SVM), M5 MODEL TREES and Linear Regression (LR) methods in forecasting hourly DISCHARGE flow of Aharchay River. The hourly water level-discharge and 14 flood events data of Aharchay River measured at the Tazekand hydrometric station was used for modeling. The results showed that the SVM method gives more accurate results than the M5 model and LR method in forecasting river flow for next one and two hours with the R2=0. 96 and RMSE=0. 0472 (m3s-1) and the R2=0. 90 and RMSE=0. 1596 (m3s-1), respectively. Comparing the performance of SVR and M5 models indicated that, however the SVR approach may present more accurate results than the M5 model tree, but the M5 model provides more understandable, applicable and simple linear relation in forecasting hourly DISCHARGE. Thus, the M5 model tree can be used as an alternative method in forecasting hourly DISCHARGE.

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APA: Copy

SATTARI, MOHAMMAD TAGHI, ABDOLLAH POURAZAD, MOHAMMADREZA, & MIRABBASI NAJAFABADI, RASOUL. (2016). TECHNICAL NOTE: HOURLY RIVER FLOW FORECAST OF AHARCHAY RIVER USING MACHINE LEARNING METHODS. WATERSHED ENGINEERING AND MANAGEMENT, 8(1 ), 115-127. SID. https://sid.ir/paper/234649/en

Vancouver: Copy

SATTARI MOHAMMAD TAGHI, ABDOLLAH POURAZAD MOHAMMADREZA, MIRABBASI NAJAFABADI RASOUL. TECHNICAL NOTE: HOURLY RIVER FLOW FORECAST OF AHARCHAY RIVER USING MACHINE LEARNING METHODS. WATERSHED ENGINEERING AND MANAGEMENT[Internet]. 2016;8(1 ):115-127. Available from: https://sid.ir/paper/234649/en

IEEE: Copy

MOHAMMAD TAGHI SATTARI, MOHAMMADREZA ABDOLLAH POURAZAD, and RASOUL MIRABBASI NAJAFABADI, “TECHNICAL NOTE: HOURLY RIVER FLOW FORECAST OF AHARCHAY RIVER USING MACHINE LEARNING METHODS,” WATERSHED ENGINEERING AND MANAGEMENT, vol. 8, no. 1 , pp. 115–127, 2016, [Online]. Available: https://sid.ir/paper/234649/en

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