Taghizadeh-Mehrjardi, R., Sarmadian, F., Omid, M., . Savaghebi, G., Rousta, M., rahimian, M. (2013). Mapping of Soil Salinity Using Geostatistic and Electromagnetic Induction Methods in Ardakan. , 26(4), 369-380. doi: 10.22092/ijsr.2013.126441
R. Taghizadeh-Mehrjardi; F. Sarmadian; Mahmoud Omid; G.R. . Savaghebi; M. J. Rousta; mh rahimian. "Mapping of Soil Salinity Using Geostatistic and Electromagnetic Induction Methods in Ardakan". , 26, 4, 2013, 369-380. doi: 10.22092/ijsr.2013.126441
Taghizadeh-Mehrjardi, R., Sarmadian, F., Omid, M., . Savaghebi, G., Rousta, M., rahimian, M. (2013). 'Mapping of Soil Salinity Using Geostatistic and Electromagnetic Induction Methods in Ardakan', , 26(4), pp. 369-380. doi: 10.22092/ijsr.2013.126441
Taghizadeh-Mehrjardi, R., Sarmadian, F., Omid, M., . Savaghebi, G., Rousta, M., rahimian, M. Mapping of Soil Salinity Using Geostatistic and Electromagnetic Induction Methods in Ardakan. , 2013; 26(4): 369-380. doi: 10.22092/ijsr.2013.126441

Mapping of Soil Salinity Using Geostatistic and Electromagnetic Induction Methods in Ardakan

پژوهش های خاک
Volume 26, Issue 4, March 2022, Pages 369-380    PDF (663.25 K)
Document Type: Research Paper
DOI: 10.22092/ijsr.2013.126441
Authors
R. Taghizadeh-Mehrjardi* 1; F. Sarmadian1; Mahmoud Omid2; G.R. . Savaghebi1; M. J. Rousta3; mh rahimian4
1Department of Soil Science, University College of Agriculture & Natural Resources, University of Tehran
2Department of Agricultural Machinery, University College of Agriculture & Natural Resources, University of Tehran
3Academic Member of National Salinity Center
4Member of National Salinity Center
Abstract
Precise mapping of the spatial distribution of salt-affected soils is prerequisite for effective management of these soils. This study was carried out for mapping soil salinity of 78000 hectares of Ardakan soils (0-30 and 0-100 cm) using 151soil samples which were taken based on hyper cube method. The secondary variables used in co-kriging method were ETM data, terrain analysis and EM38 readings. The best model was selected by means of cross validation and error evaluation methods, such as RMSE and ME methods. Results showed that co-kriging method with EM38 data as a secondary variable was the best method for prediction of soil salinity (69.1, 30.55, 48.8 and 20.41, respectively). Results recommended EM38 as secondary data for mapping soil salinity. Additionally, results showed the largest amount of soil salinity in the north of the area and the smallest values in the areas with more elevation. The concavely shaped plain could help to move soluble salts toward the north of area in which the soils with highest electrical conductivity are found. 
Keywords
Cross validation; Terrain analysis; Interpolation; Remote sensing
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