Survey and Zoning of Soil Physical and Chemical Properties Using Geostatistical Methods in GIS (Case Study: Miankangi Region in Sistan)

• Main Authors: M. Hashemi, A. Gholamalizadeh Ahangar, Abolfazl Bameri, F. Sarani, A. Hejazizadeh
• Format: Article
• Language: fas
• Published: Ferdowsi University of Mashhad 2017-02-01
• Series: مجله آب و خاک
• Subjects: Correlation; Geostatistical Methods; Miankangi Region; Soil Salinity; Spatial Distribution
• Online Access: http://jsw.um.ac.ir/index.php/jsw/article/view/25950
• ISSN: 2008-4757; 2423-396X

Introduction: In order to provide a database, it is essential having access to accurate information on soil spatial variation for soil sustainable management such as proper application of fertilizers. Spatial variations in soil properties are common but it is important for understanding these changes, particularly in agricultural lands for careful planning and land management. Materials and Methods: To this end, in winter 1391, 189 undisturbed soil samples (0-30 cm depth) in a regular lattice with a spacing of 500 m were gathered from the surface of Miankangi land, Sistan plain, and their physical and chemical properties were studied. The land area of the region is about 4,500 hectares; the average elevation of studied area is 489.2 meters above sea level with different land uses. Soil texture was measured by the hydrometer methods (11), Also EC and pH (39), calcium carbonate equivalent (37) and the saturation percentage of soils were determined. Kriging, Co-Kriging, Inverse Distance Weighting and Local Polynomial Interpolation techniques were evaluated to produce a soil characteristics map of the study area zoning and to select the best geostatistical methods. Cross-validation techniques and Root Mean Square Error (RMSE) were used. Results and Discussion: Normalized test results showed that all of the soil properties except calcium carbonate and soil clay content had normal distribution. In addition, the results of correlation test showed that the soil saturation percentage was positively correlated with silt content (r=0.43 and p