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Information Journal Paper

Title

Modeling of daily soil temperature using synoptic data and neural network

Pages

  285-295

Abstract

 Soil moisture, as the soil hydrologic parameters, can be affected by Soil temperature and controls various hydrological processes. Given the importance of this issue, in this study, the efficiency of Artificial Neural Network was studied to simulate Soil temperature at 5-100 cm depth. Recorded meteorological parameters in the Isfahan synoptic station were used to simulate the Soil temperature at different depths. The structure of the neural network was formed with an input layer, a hidden layer and an output layer and network training was done by Levenberg– Marquardt algorithm. Also test and error was done to determine a number of suitable neurons in hidden layer. The results showed that error in both neural network and ANFIS model increases with depth increase that can be due to the weak correlation between Soil temperature changes in the lower layers and Climatic parameters.

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    APA: Copy

    MESBAHZADEH, TAYYEBEH, SOLAIMANI SAROOD, FARSHAD, Rafiiei sardoo, Elham, & FarzanePei, Fateme. (2018). Modeling of daily soil temperature using synoptic data and neural network. JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 71(1 ), 285-295. SID. https://sid.ir/paper/162587/en

    Vancouver: Copy

    MESBAHZADEH TAYYEBEH, SOLAIMANI SAROOD FARSHAD, Rafiiei sardoo Elham, FarzanePei Fateme. Modeling of daily soil temperature using synoptic data and neural network. JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)[Internet]. 2018;71(1 ):285-295. Available from: https://sid.ir/paper/162587/en

    IEEE: Copy

    TAYYEBEH MESBAHZADEH, FARSHAD SOLAIMANI SAROOD, Elham Rafiiei sardoo, and Fateme FarzanePei, “Modeling of daily soil temperature using synoptic data and neural network,” JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), vol. 71, no. 1 , pp. 285–295, 2018, [Online]. Available: https://sid.ir/paper/162587/en

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