Interpolation of Soil Salinity and Evaluation of Salinity Risks in Meiankangi Region (Sistan) Using Geostatistical Methods

Document Type : Research Paper

Authors

1 MSC., Irrigation and Drainage

2 Assistant Professor, Water Engineering Department, Zabol University

Abstract

Soil salinity is one of the important soil properties that has a
significant effect on many processes such as plant grows. The objectives of
this paper are to estimate soil salinity and to map the salinity risk in
Meiankangi  located in Sistan plain. Soil
electrical conductivity was measured on soil samples taken from 122 sites
distributed radiometry across to study area. The geostatistical methods of
ordinary kriging and indicator kriging were used for salinity mapping. The
latter was used to map the probability that soil salinity exceeds a critical
threshold. The methods were evaluated using cross-validation. The validation of
used methods were evaluated using root mean square error (RMSE( and mean bias error (MBE).
The results showed that both methods were similar for predict soil salinity.
The probability maps of exceeding 2, 4 and 8 ds/m were generated using
indicator kriging. Given the critical threshold of 2 ds/m, almost all the
regions have a probability of salinity of more than 0.5.  The 
results showed that the salinity is moderate across the study area.
Overall the obtained results indicated that unlike ordinary kriging, indicator
kriging is able to map the salinity risk. These maps are very helpful in
decision such as land classification and management.

Keywords

Files

History

  • Receive Date: 06 February 2011
  • Revise Date: 06 March 2014
  • Accept Date: 10 January 2012
  • Publish Date: 21 May 2012

Share

How to cite

Statistics