عنوان مقاله [English]
Background and Objectives :Soil saturated hydraulic conductivity is an important parameter for all activities related to water flow in soil, controlling soil water infiltration and superficial runoff, pesticide leaching from farms and transferring pollutants from polluted area to underground water. The spatial distribution of physical and hydraulic properties is effective on the behavior of hydrological, water transfer and sediment to surface and subsurface water therefore the variations of these characteristics is effective on land management. In a study with the aim of analysis of the spatial variability of soil hydraulic conductivity using Geostatistics methods of simple kriging, ordinary kriging and public kriging by Barani et al (2013) in Zydon plain of Khuzestan has been done, the number of 200 Regular grid point with 1 × 1 kilometers Distance the hydraulic conductivity measured by methods well and inverse well, the results showed that between the studied methods, simple kriging had higher estimation accuracy in the study plain and between the variogram models, spherical model is selected (2). This research aims were to study spatial variation of soil hydrauic conductivity and effective factors on it with geostatistic method and selecting the most appropriate on method in the Laaghar plain.
Materials and Methods: Laaghar plain with approximately area of 12986 hectares is located in Khonj city the functions of Fars province that located in geographic range of 28˚ 1ʹ 2ʺ to 28˚ 12ʹ 54ʺ Northern and 53˚ 4ʹ 44ʺ to 53˚ 21ʹ 50ʺ Eastern. For this purpose spatial variation of soil saturated hydraulic conductivity and some other soil parameters like soil particle size percentage (sand, silt and clay), gypsum (CaSo4) and calcium carbonate (CaCo3) percentage were studied using spatial statistics. Interpolating and zoning of these properties were done with IDW, kriging and co-kriging methods, and these estimators accuracy were compared with each other.
Results: Results showed that the parameters of sand, gypsum (CaSO4) and calcium carbonate (CaCO3) percentage with a Nugget variance ratio to threshold by 0.001, 0.246, 0.217 have strong spatial structure, and saturated hydraulic conductivity, silt and clay percentage having Nugget variance ratio to threshold by 0.499 had a moderate spatial structure. Fitnessing theory model on experimental variograms show that the Gaussian model for the sand, silt and clay, gypsum percentage properties, and spherical model for saturated hydraulic conductivity parameter and calcium carbonate percentage having the highest R2 and lowest RSS are best fitness on experimental variograms. Hydraulic conductivity was measured in the field with well and inverse well method. The results showed that the studied parameters had suitable spatial structure, and each one of them had specific spatial pattern.
Conclusion: Kriging estimator had better results and less error for interpolating saturated hydraulic conductivity, gypsum and calcium carbonate percentage parameters compare to IDW method, but the IDW method showed better results in interpolating sand, silt and clay percentage parameters. The cokriging interpolating method were not used to interpolate properties because of the lack correlation between major variable (saturated hydraulic conductivity) and other parameters (as the accessory variable) to interpolate the properties.