PREDICTION OF EVAPORATIVE FLUX FROM SHALLOW WATER TABLES USING REGRESSION AND ARTIFICIAL NEURAL TECHNIQUES

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CHARI M.M.; AFRASYAB P.; PIRI J.; DELBARI M.

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Journal: Journal of Water Resources Engineering Year:2011 | Volume:4 | Issue:8 Page(s): 11-20

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Title

PREDICTION OF EVAPORATIVE FLUX FROM SHALLOW WATER TABLES USING REGRESSION AND ARTIFICIAL NEURAL TECHNIQUES

Author(s)

CHARI M.M. | AFRASYAB P. | PIRI J. | DELBARI M. | Issue Writer Certificate

Keywords

EVAPORATION FROM THE BARE SOILQ2

GAMMA TESTQ2

REGRESSION MODELQ2

NEURAL NETWORKSQ2

Abstract

Knowledge of the relationships between the watertable depth and evaporation rate from the bare soil is of immense importance in arid and semi arid area. The rise in watertable, land inundation, and soil salinization are inevitable aftermath of over-irrigation in such environments. Evaporative flux was measured in 200 mm inside diameter PVC columns filled with the sandy loam, loam and clay loam soils, maintaining the watertable in them at a depth of 40, 60 and 80 cm. Evaporation from both the bare soil and exposed water surface, soil water content, and the maximum and minimum air temperatures were measured daily for 74 consecutive days. The TDR technique was used for the soil water content determination. Several nonlinear models were developed using benefiting from the GAMMA TEST (the Win Gamma program), including the local linear regression, the 2-layer back propagation, conjugate gradient descent, and the BFGS neural network. Validity of these models was ascertained using the root mean square error, the mean absolute error, and the larger coefficient of determination. The models satisfactorily predicted the measured evaporative flux.

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APA: Copy

CHARI, M.M., AFRASYAB, P., PIRI, J., & DELBARI, M.. (2011). PREDICTION OF EVAPORATIVE FLUX FROM SHALLOW WATER TABLES USING REGRESSION AND ARTIFICIAL NEURAL TECHNIQUES. WATER ENGINEERING, 4(8), 11-20. SID. https://sid.ir/paper/169639/en

Vancouver: Copy

CHARI M.M., AFRASYAB P., PIRI J., DELBARI M.. PREDICTION OF EVAPORATIVE FLUX FROM SHALLOW WATER TABLES USING REGRESSION AND ARTIFICIAL NEURAL TECHNIQUES. WATER ENGINEERING[Internet]. 2011;4(8):11-20. Available from: https://sid.ir/paper/169639/en

IEEE: Copy

M.M. CHARI, P. AFRASYAB, J. PIRI, and M. DELBARI, “PREDICTION OF EVAPORATIVE FLUX FROM SHALLOW WATER TABLES USING REGRESSION AND ARTIFICIAL NEURAL TECHNIQUES,” WATER ENGINEERING, vol. 4, no. 8, pp. 11–20, 2011, [Online]. Available: https://sid.ir/paper/169639/en

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