《Table 1 Descriptive statistics of soil electrical conductivity (ECa, mS m–1) in 2009, 2010 and 2011

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《Using proximal sensor data for soil salinity management and mapping》

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Semi-variance analyses were carried out to express the spatial dependence of the three ECa datasets.These processes were carried out using geostatistical software，GS+ver.9.0 for Windows（Gamma Design Software，Plainwell，MI）.Based on the regression coefficient of determination（r2），the model with the least sum of squares was chosen as the“best fit.”The semi-variogram models for the ECa across three years demonstrated that the spatial behavior had good continuity in space，and the three datasets can be modeled quite well with exponential models.Fig.3 shows the plot of experimental Semivariances and the fitted semi-variogram models for the ECa between the years 2009–2011.The parameters for the three models are shown in Table 2.The“nugget”（C0）was the random variation that usually results from the inaccuracy of measurements or variations of the properties that cannot be detected in the sample range；the“sill”（C0+C）was the total ECa variation at which the semi-variogram levels for the patterned data；the structure variance（C）was the difference between the sill and nugget；the“range”was the maximum distance over which the measured ECa exhibited significant spatial autocorrelation.Generally，the ratio relating C0 to sill（C+C0），which is an especially important parameter，can be used to characterize the spatial dependency.If the ratio is less than 25%，this implies a strong spatial dependency of the observations；if the ratio is between 25 and 75%，the ratio indicated moderate spatial dependency；if the percentage is greater than 75%，it indicated a weak spatial dependency in the present sampling resolution（?amonil et al.2016）.As presented in Fig.3 and Table 2，C0 decreased from 2009 to2011，indicating that the variations for ECa became smaller.Moreover，the ratio of C0 to（C+C0）also declined sharply，from 17.07%in 2009 to 0.26%in 2011.Following this，we concluded that the autocorrelation of ECa was becoming stronger，which may have been induced by rice cultivation with alternating irrigation and drainage farming.