Geospatial Analysis of Some Soil Chemical Properties at White Nile Sugar Scheme, Sudan
Journal: International Journal of Multidisciplinary Research and Publications (Vol.4, No. 5)Publication Date: 2021-11-15
Authors : Ali Ahmed Ali; Mohamed Salih Dafalla; Hatim Nuh Ummhani Idris Ahmed; Mohammed Salih Adam Abdalla; Elsadig Agabna Elhadi; brahim Saeed Ibrahim;
Page : 58-61
Keywords : ;
Abstract
Agriculture is the backbone of the Sudan's economy. Sudanese agriculture ranges from traditional rain-fed to irrigated one. Sudan experiences sugar production from cane since decades. White Nile Sugar Company, as the most recent sugar company in the Sudan, was used to be the study area. Soil management is a key step for sustainable and feasible use of land for agricultural activity. Soil chemical properties are governing factor in determination of suitability of soil for different crops. Digital soil mapping is widely used in corporation with conventional methods to enhance the productivity and efficiency of production inputs. Geostatistical techniques for soil properties mapping is an important tool for land evaluation, assessment and management. This research aims to study the spatial distribution of some soil parameters in order to improve the management system in the scheme. Chemical and Physical Properties Data from White Nile Sugar Company (2006) executed by Land and Water Research Centre, Wad Medani were used. The total number of collected soil samples were 5174 samples representing 2567 Auger sites at 0- 30cm in depth.2470 soil auger data were used in interpolation. The data was introduced into GIS environment from excel format to one shape file. Five layers were produced to represent the spatial distribution of pH, EC, Ca++, Mg++, Na+ and SAR. 1 The soil of scheme is generally slightly heterogeneous. It is medium alkaline, non-saline, non-sodic with some scatter pockets of salinity and sodicity. The southern part of the scheme is affected by salinity and sodicity. This study concluded that geostatistical tools improve high efficiency in mapping the spatial distribution of soil traits. Therefore, this study recommends application of geostatistical tools in zonal-based management practices for better productivity
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