2768 Research Article Open Access Site-Specific Leaching Map of a Salt Affected Soil in Egypt Sameh M Shaddad* 1 and Mohamed Y Hendawi 2 1 Soil science department, Zagazig University, Egypt 2 Plant protection department, Zagazig University, Egypt Received: February 15, 2018; Published: February 22, 2018 *Corresponding author: Sameh M Shaddad, Soil science department, Zagazig University, Egypt, Email: DOI: 10.26717/BJSTR.2018.02.000791 Sameh M Shaddad. Biomed J Sci & Tech Res Cite this article: Sameh M S, Mohamed Y H. Site-Specific Leaching Map of a Salt Affected Soil in Egypt. Biomed J Sci &Tech Res 2(4)- 2018. BJSTR.MS.ID.000791. DOI: 10.26717/BJSTR.2018.02.000791 Introduction Soil salinity is a crucial problem facing countries in arid and semi arid regions which negatively affects sustainable agriculture Eilers et al. [1]. This problem needs to be accurately quantified and mapped in order to mitigate and control its negative effects Herrero and Pérez-Coveta [2]; Benyamini et al. [3]; Wang [4] especially in irrigated soils Amezketa [5]. Soil salinity cab be solved by leaching soluble salts from the root zone by adding water with good drainage conditions. In Egypt, salt-affected soils are located in the Northern- Central part of the Nile Delta and on its Eastern and Western sides. Also, in Wadi El-Natroun, El-Kebeir, the Oases, many parts of the Nile Delta and Valley and El-Fayoum province are characterized as salt affected soils. In Egyptian irrigated lands, about nine hundred thousand hectares suffer from salinization. These are distributed as follows: 60 % is in Northern Delta, 20 % in Southern Delta and Middle Egypt and 25 % in Upper Egypt FAO [6]. Conventionally, data of soil properties are summarized by averages of collected soil samples with no consideration of the spatial variation either at macro scale or at micro scale (within-field) (Webster and Oliver [7] and Navarro-Pedreño et al. [8]. Geostatistics provides good tools in capturing within field spatial variation of soil variables that is used to delineate management zones and consequently know where and how much farm inputs should be added Oliver and Webster [7]. Geostatistical methods are non-destructive, time saving and cost effective as comparing with traditional methods and provide fine- scale information about soil variables. Spatial distribution of soil properties has been recognized by various researchers Burgess and Webster [9]; Warrick et al. [10]; Odeh et al. [11]; Juang & Lee [12]. Oridinary kriging as a geostatistical interpolation method was the most common used to predict and map soil parameters at unsampled locations Lopez-Granados et al. [13]; Meul & Van Meirvenne [14]; Sumfleth & Duttmann [15]. This study aimed at assessing the spatial distribution and predicting soil salinity over a field in Sharkia governorate using ordinary kriging for the purpose of preparing a prescription map of leaching requirements. Materials and Methods Site Description, Sampling and Laboratory Analysis This study was conducted in 4.6 ha field (30° 51’ 53.31’’ N, 32° 02’ 50.45’’ E), located in Bahrelbaqar, Sharkia governorate. A total of 100 soil samples based on an almost regular 25x25 m grid at 0.20 m depth were collected and transported to the soil laboratory, where they were dried, ground and sieved with a 2 mm sieve and Abstract 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 ISSN: 2574-1241