Remote Sensing Techniques in Mapping Spatial Variability of Salinity in Kano River Irrigation Project (KRIP), Nigeria

Abstract

Salinity has become a major issue in most large scale irrigation schemes, assessing the extent of the spread has become daunting and laborious. Remote sensing techniques were used to map salinity and develop models for extracting and identifying salinity in soils. Sentinel-2B optical imaging satellite with 13 spectral bands and 10 m spatial resolution was used.  SNAP Desktop, ERDAS Imagine, and ArcGIS 10.6 software were used as the main GIS packages for building models and running functions such as input, output, analysis, and processing. Stepwise Multiple Linear Regression (MLR) techniques were carried out for the assessment of the spatial distribution of ECe and to predict salinity level at different locations of the Kano River Irrigation Project (KRIP). Four models were developed, however, due to the lower Variance Inflation Factor (VIF), model 2 which is a combination of salinity Index and band 3 (Green band) was used in delineating the spatial extent of the salinity. Close monitoring of the salt development and application of reversal measures were recommended.