Abstract
Gradual drying of Urmia Lake has left vast saline areas all around it, increasing the risk of salinization of agricultural lands next to the Lake. The current research was aimed to predict soil salinity and distinguish the boundary line between saline and agricultural lands by taking in to account the spatial variability of soil salinity in Bonab Plain, Iran. To do so, soil samples were taken from depth 0-25 cm in 78 points with spatial intervals of 500 m and were analyzed for their electrical conductivity in saturated paste extractions. Data analysis showed that soil salinity mean wasn’t stationary and was varying among dataset. Therefore to build up a variogram, the spatial components of the mean trend were computed and subtracted from laboratory measured ECe values, which resulted in residuals. The semivariogram function was then calculated and modelled based on the residuals. Cross-validation results showed that kriging method along with modified semi-variogram, resulted in better predictions of soil salinity with ME and MSE equal to 0.12 and 0.3. Setting 4 dSm-1 as the limit between saline and non-saline soils in kriging algorithms resulted in a sharp boundary line between saline and non-saline lands in the study area. The presence of highly saline soils next to the agricultural lands in the area can increase the risk of secondary salinization of the Bonab Plain which is one of the important agricultural production centers in the area. Therefore, careful monitoring of lands near salinity boundary in the area should be of high priority. Key Words : Bonab Plain, Kriging, variogram, soil salinity, spatial prediction, Urmia Lake.
Highlights
Population growth along with limited agricultural lands in the world has been one of the most important challenges of food production during few past decades
This phenomenon was observed all over the study are, parallel to Urmia Lake. This has been reported previously by Hamzehpour and Eghbal (2016) in the western shore of Urmia Lake where the maximum spread of Urmia Lake had drawn a narrow boundary between saline soils and agricultural lands
In order to assess the spatial variability of the data, taking into account the mean variation among dataset, the spatial components of the mean trend were computed and subtracted from laboratory measured ECe values, which resulted in residuals
Summary
Population growth along with limited agricultural lands in the world has been one of the most important challenges of food production during few past decades. As of shallow depth of Urmia Lake, its drying has resulted in its total area shrink, remaining vast saline lands around it (Golabian, 2011). In such saline lands, agriculture seems to be impossible and many of the native plant species may not be able to grow. The trend and rate of soil salinity and alkalinity changes in adjacent Plains of Urmia Lake require careful monitoring and management. Samplings at different time instants are required for monitoring the temporal changes of salinity. Performing such an extensive field investigation is costly and time consuming. Kriging methods have widespread use in geostatistical methods and in soil salinity prediction models which have been discussed
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