Geostatistical Analysis and Zoning of Soil Primary Particles for optimal land use management.(Case Study: Shabankareh Plain, Bushehr Iran)

Over the last three decades, there has been a general tendency to change methods in research on soil resource management from conventional and mainly qualitative methods to Quantitative ones based on spatial correlation models which are called digital soil mapping (DSM). The present study was carried out in Shabankareh plain with an area of ​​15,000 hectares with different physiographic units that are mainly used as agricultural farms in Bushehr province, Southern Iran. Target sites (172 points) were selected for soil sampling at depths of 0-30 and 30-60 based on hypothetical networking on satellite images and visual differences observed in the study area. Digital soil texture maps were drawn for both old soil texture triangle (include sand, silt and clay particles) and the new one (include Geometric mean particle diameter and geometric standard deviation of soil particle diameter). Soil texture is considered as one of the most important characteristics in determining the type and density of agricultural activities and types of land use. Two geostatistical programs include GS+ and ArcGIS and various methods of data estimators such as inverse distance weighting and ordinary Kriging method were used in this project. The results showed the strongest spatial structure class was observed in geometric standard deviation of the soil particle diameter (0.48) and the weakest in silt (0.73). The highest and lowest effective range among soil texture parameters were related to soil clay particles and geometric standard deviation of soil particle diameter with 684 and 336 meters, respectively. Number of drilled profiles (11 ones) was based on digital uniformity map. The generated digital maps can provide spatial information of important soil properties such as permeability and drainage, water holding capacity, fertility, soil erosion and salinity which increases the accuracy in the optimal management of agricultural lands.