Evaluation of spatial variability of some soil chemical and physical properties in Foumanat Plain paddies using geostatistic methods

Since the soil is considered as the most important source of nutrients, understanding the spatial variation and geographical distribution patterns of nutrients is crucial for the proper management and the right application of fertilizers. Nowadays, soil management based on spatial variability of soil properties in crop growth is necessary (Morales et al, 2011; Bijanzadeh et al, 2014). However, accurate estimates of soil properties in all areas are not time and cost effective. Therefore, interpolation is a suitable solution to estimate not sampled areas. There are different techniques for predicting the soil characteristics in not sampled areas such as geostatistics (Mohammadi, 2007). Therefore, this study aimed to evaluate the physical and chemical properties of some soil paddy fields in Foumanat, Guilan province using the geostatistics technique. The present study was performed in Foumanat plain during two cropping seasons of 2013 and 2014. Soil samples were taken from 45 fields and geographic coordinates were recorded. Soil properties including electrical conductivity, cation exchange capacity, organic matter, pH, clay, silt, sand were measured. Interpolating of variables were investigated with kriging (KG) and inverse distance weighting (IDW) methods with power one to five. The best interpolation method was selected using evaluating statistics such as Mean Absolute Error (MAE), Mean Bias Error (MBE) and Root Mean Square Error (RMSE). Results indicated that electrical conductivity, cation exchange capacity, pH and silt fitted by an exponential model while two parameters of organic matter and sand along with clay were fitted by the spherical and Gaussian models, respectively. High determination coefficients for sand, clay and electrical conductivity were 0.95, 0.83 and 0.80, respectively. According to the calculated variograms, electrical conductivity and sand exhibited a medium spatially structured variability whereas highly structured variability was observed for soil CEC, organic matter, pH, clay and silt. Least nugget effect among the studied variables was allocated to CEC, organic matter and sand. The results showed that the IDW method provided more accurate and less error for CEC, organic matter, pH and silt in the study area as compared to the kriging method. Moreover, there were not differences between the two methods of IDW and kriging in terms of electrical conductivity, clay and sand parameters. Overall, the fertility of paddy fields was statistically different. The most coefficient of variation (CV) from 15 to 24 percent, the average variation were found in electrical conductivity, sand and clay while the amount of CV in the cation exchange capacity, organic matter, pH and silt were recorded lower than 15% (low diversity). In the studied characteristics, two types of medium and strong structures were observed. In general, the results of this study can be used to estimate the fertility and physical and chemical characteristics of rice farms. Therefore, these results could help to adopt crop improvement methods including crop choice and site-specific fertilizer recommendations to optimum management of inputs and sustainable production.