Regional Assessment of Monthly Soil Temperatures in the Aegean Region of Turkey

An artificial neural network (ANN) model was developed to predict monthly soil temperatures in the Aegean Region of Turkey. The model used soil temperature data measured by the Turkish State Meteorological Service between 2000 and 2006 at the Kütahya, Manisa, Uşak, Afyonkarahisar, İzmir, Aydın, Denizli and Muǧla meteorological stations at depths of 5, 10, 20, 50 and 100 cm below the surface. The monthly air temperature, depth and month of the year were used in the input layer of the artificial neural network model, while the monthly soil temperature was the target data in the output layer. A prediction model was developed using the MATLAB program and the results derived from the model were compared with measured values. The mean absolute error (MAE) for the derived results from the different depths at all stations ranged from 0.32–0.82°C, while the corresponding range for the validation data set was 0.27–0.76°C.

[1]  Daniel Hillel,et al.  Introduction to soil physics , 1982 .

[2]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[3]  Ozgur Kisi,et al.  Modelling daily suspended sediment of rivers in Turkey using several data-driven techniques / Modélisation de la charge journalière en matières en suspension dans des rivières turques à l'aide de plusieurs techniques empiriques , 2008 .

[4]  W. Liu,et al.  Simulation of the daily change of soil temperature under different conditions , 2003 .

[5]  S. Lykoudis,et al.  Ground temperature estimations using simplified analytical and semi-empirical approaches , 2009 .

[6]  J. Wen,et al.  An improved force‐restore method for soil temperature prediction , 2008 .

[7]  Ozgur Kisi,et al.  River Flow Modeling Using Artificial Neural Networks , 2004 .

[8]  Mahmud Güngör,et al.  Generalized Regression Neural Networks and Feed Forward Neural Networks for prediction of scour depth around bridge piers , 2009, Adv. Eng. Softw..

[9]  Keryn I. Paul,et al.  Soil temperature under forests: a simple model for predicting soil temperature under a range of forest types , 2004 .

[10]  Sinkyu Kang,et al.  Predicting spatial and temporal patterns of soil temperature based on topography, surface cover and air temperature , 2000 .

[11]  Zhiqiu Gao,et al.  Determination of soil temperature in an arid region , 2007 .

[12]  P. Depecker,et al.  Using artificial neural networks to predict interior velocity coefficients , 1997 .

[13]  Soteris A. Kalogirou,et al.  Artificial neural networks in renewable energy systems applications: a review , 2001 .

[14]  Tuncay Yilmaz,et al.  INFLUENCE OF UPPER LAYER PROPERTIES ON THE GROUND TEMPERATURE DISTRIBUTION , 2009 .

[15]  Isabelle Braud,et al.  Modelling heat and water exchanges of fallow land covered with plant-residue mulch , 1999 .

[16]  Rattan Lal,et al.  Diurnal soil temperature fluctuations for different erosion classes of an oxisol at Mlingano, Tanzania , 1998 .

[17]  Josef Eitzinger,et al.  Nonlinear prediction of near-surface temperature via univariate and multivariate time series embedding , 2004 .

[18]  Mehmet Bilgili,et al.  Prediction of Long-term Monthly Temperature and Rainfall in Turkey , 2009 .

[19]  G. Tayfur.  Artificial neural networks for sheet sediment transport , 2002 .

[20]  Adnan Sözen,et al.  Forecasting based on neural network approach of solar potential in Turkey , 2005 .

[21]  Raju K. George,et al.  Prediction of soil temperature by using artificial neural networks algorithms , 2001 .

[22]  Y. Kerr,et al.  The SMOS Mediterranean Ecosystem L-Band characterisation EXperiment (MELBEX-I) over natural shrubs , 2010 .

[23]  G. Mihalakakou,et al.  On estimating soil surface temperature profiles , 2002 .

[24]  C. J. Butler,et al.  Air temperatures at Armagh Observatory, Northern Ireland, from 1796 to 2002 , 2005 .

[25]  Glenys McGowan,et al.  Soil temperature calculation for burial site analysis. , 2009, Forensic science international.

[26]  Guo H. Huang,et al.  Application of soft computing models to hourly weather analysis in southern Saskatchewan, Canada , 2005, Eng. Appl. Artif. Intell..