SOIL Studies

SOIL Studies

2014, Vol 3, Num, 2     (Pages: 111-123)

Analysis of the Spatial Variability of Soil Properties in Different Physiographic Units

Hasan Sabri ÖZTÜRK 1 ,Gönül AYDIN 2 ,Mustafa SAĞLAM 3 ,Levent ATATANIR 2 ,Alper YORULMAZ 2

1 Univ. of Ankara, Faculty of Agriculture, Dept. of Soil Science and Plant Nutrition, Ankara-Turkey
2 Univ. Of Adnan Menderes, Faculty of Agriculture, Dept. of Soil Science and Plant Nutrition, Aydın-Turkey
3 Univ. Of Ondokuzmayıs, Faculty of Agriculture, Dept. of Soil Science and Plant Nutrition, Samsun-Turkey

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The success of a study in geostatistics depends partially on the intrinsic characteristics of the soil. This study aimed to identify and compare the spatial variability of soil properties in different physiographic units in Great Meandros Plain, Turkey. Soil samples were collected in Yuvaca (the river terrace), Köprü (the bottom of delta on the edge of a lagoon), and Sarıkemer (the back of the delta). Soils were sampled from the soil surface in 10 ha field using a regular grid with a 100 m distance in all fields. The numbers of the soil samples collected are 117 in Yuvaca and Köprü and 118 in Sarıkemer. Volumetric soil moisture content (SMC), EC, and soil texture were used for geostatistical analyzing. The semivariogram parameters and kriged contour maps showed different figures due to different intrinsic characteristics of the soils. Compared with Yuvaca and Sarıkemer, Köprü showed very low nugget values and high range values. For instance sand and silt percentages in Köprü resulted in very low nugget values (0.0001 ve 0.001) and high range values (805 m ve 744 m). Spherical variograms were adapted for all the properties except clay in Köprü. Although the coefficient of variation of the parameters was higher in Köprü than in the other areas, according to geostatistical calculations the lower nugget percentage and greater range indicated that there was strong spatial dependence. Dissimilarity in the fields resulted in statistically different correlations among the variables.


Keywords : Geostatistics, kriging, range, semivariogram models, spatial variability, TDR