Top-soil salinity mapping using geostatistical approach in the agricultural landscape of Timuga irrigation scheme, South Tigray, Ethiopia

Long-term irrigation activities in arid and semi-arid areas causes soil salinity problem. Thus, knowing soil salinity status is a prerequisite for designing appropriate irrigation management strategies. This study was therefore conducted to predict top-soil salinity of Timuga irrigation scheme and to map its spatial distribution using geostatistical techniques. An area of 33.5 km(2) was delineated, and regularly spaced grid (cell size: 500 m) of sampling points were generated using fishnet of the ArcGIS 10.2. A total of 106 composite soil samples were collected from each sampling points at a depth of 20 cm and geo-referenced using global positioning system. Soil samples were analyzed for pH, electrical conductivity (ECe), cation exchange capacity, and exchangeable bases (Ca++, Mg++, K+, and Na+) following the standard laboratory procedure. Both descriptive statistics and ordinary kriging interpolation techniques were used to analyze the data. The result showed that electrical conductivity ranged from 0.125 to 12.89 mScm(-1) and the exchangeable sodium percentage ranged from 0.094% to 27.514%. This indicated that soils of the irrigation scheme are characterized by saline and sodic soils with different degree of spatial variability. The total area of 75.3% and 24.7% has classified as low and medium salinity hazards, respectively. However, 3.11%, 76%, and 20.89% of the total area have classified as high, medium, and low sodicity levels, respectively. Therefore, it was concluded that soil salinity hazard is existed and is building up of gradually in parallel with irrigation expansion. Hence, prevention and recovery measures are needed considering a variety of options such as leaching, fertilization, and planting salinity-resistant crop varieties to sustain irrigation productivity.