*Corresponding author:
Sameh M Shaddad, Soil science department, Zagazig University, EgyptReceived: February 15, 2018; Published: February 23, 2018
DOI: 10.26717/BJSTR.2018.02.000791
To view the Full Article Peer-reviewed Article PDF
Geostatistical techniques allow detecting soil spatial variability and applying site-specific management in a way that traditional methods do not. The study objective was to develop a prescription map for leaching requirements (LR) of a field in Sharkia governorate in Egypt using ordinary kriging as interpolator. 91 soil samples were collected and subjected to electrical conductivity analysis (ECe). All data were randomly divided into two subsets named as calibration and validation. Prediction performance was assessed by calculating two statistics: mean error (ME) and mean standardized squared error (MSSE). Results showed that the ME and MSSE values were 0.09 and 1.27 in validation. LR was calculated for zones having ECe greater than 4 dS.m-1 to reach 2 dS.m-1 and was 3625 and 1149 m3. Results showed that assuming the ECe mean value for 91 soil samples (5.12 dS.m-1) - without geostatistical interpolation - a quantity of 6203 m3 of water should be added to reduce salinity of the whole field to 2 dS.m-1. So 1429 m3 can be saved and then used for irrigation. These results emphasize the importance of geostatistics in detecting within field variability and hence applying site-specific management especially in countries suffering from water scarcity.
Keywords: Soil salinity; Site-specific management; Ordinary kriging
Abbreviations: LR: Leaching Requirements; ECA: Electrical Conductivity Analysis; ME: Mean Error; MSSE: Mean Standardized Squared Error; BLUE: Best Linear Unbiased Estimator
Abstract| Introduction| Material and Methods| Results and Discussion| Conclusion| References|