Spatial Variability of Soil Salinity in the Yellow River Delta and Its Estimation by CoKriging Method
Yang Jinsong
Abstract
Yang Jinsong
Abstract
In this paper,the spatial variability of soil salinity at all depths in some typical fields in the Yellow River Delta is lucubrated by using statistics and geo-statistics.The study area(37°33′~37°34′N,118°47′~118°50′E) is located in Yong'an Town,Kenli County,Shandong Province,and it belongs to the temperate continental monsoon climatic zone,the spatiotemporal distribution of precipitation varies,precipitation occurs mainly during the period from July to August and its proportion occupies 70% of the annual precipitation,and the ratio between annual evaporation and precipitation is about 3.Spatial distribution figures and semi-variograms,which can be used to explicitly explain the random and structural variability of soil salinity,are charted.The results show that there is a moderate spatial variability and a spatial correlation in soil salinity at all depths,and the spatial distribution of soil salinity is jointly affected by structural and random factors.All the spatial distribution figures of soil salinity interpolated by Kriging interpolation show apparently that the distribution of soil salinity in the study area is belt and patch-shaped,and there is a spatial correlation between the distribution figures of soil salinity at different depths in certain extent.The spatial distribution of salinity in topsoil is mainly affected by micro-topography and climatic conditions,and that in deep soil is mainly affected by groundwater properties.The values of salinity in deep soil can be estimated by CoKriging method using the values of salinity in topsoil,thus the estimation precision of salinity in deep soil can be significantly increased,and the estimated variance can be decreased by 167.36% compared with that estimated by Kriging method.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In this paper,the spatial variability of soil salinity at all depths in some typical fields in the Yellow River Delta is lucubrated by using statistics and geo-statistics.The study area(37°33′~37°34′N,118°47′~118°50′E) is located in Yong'an Town,Kenli County,Shandong Province,and it belongs to the temperate continental monsoon climatic zone,the spatiotemporal distribution of precipitation varies,precipitation occurs mainly during the period from July to August and its proportion occupies 70% of the annual precipitation,and the ratio between annual evaporation and precipitation is about 3.Spatial distribution figures and semi-variograms,which can be used to explicitly explain the random and structural variability of soil salinity,are charted.The results show that there is a moderate spatial variability and a spatial correlation in soil salinity at all depths,and the spatial distribution of soil salinity is jointly affected by structural and random factors.All the spatial distribution figures of soil salinity interpolated by Kriging interpolation show apparently that the distribution of soil salinity in the study area is belt and patch-shaped,and there is a spatial correlation between the distribution figures of soil salinity at different depths in certain extent.The spatial distribution of salinity in topsoil is mainly affected by micro-topography and climatic conditions,and that in deep soil is mainly affected by groundwater properties.The values of salinity in deep soil can be estimated by CoKriging method using the values of salinity in topsoil,thus the estimation precision of salinity in deep soil can be significantly increased,and the estimated variance can be decreased by 167.36% compared with that estimated by Kriging method.
Key concepts: Topsoil, Salinity, Soil salinity, Spatial variability, Spatial distribution, Environmental science, Hydrology (agriculture), Soil science