The development of an overlay model to predict soil salinity risks by using remote sensing and GIS techniques: a case study in soils around Idku Lake, Egypt.

Soil salinization is one of the major environmental problems facing agricultural lands in arid and semiarid areas of the world because of its detrimental impacts on agricultural production and on the sustainable development of land resources. Hence, predicting soil salinity is essential to avoiding further soil degradation. The present study is intended to develop a model for predicting soil salinity in soils around Idku Lake by using remote sensing and geographic information system techniques. This lake is a shallow brackish basin located in the western part of the Nile Delta. For this purpose, Landsat 8-OLI images and shuttle radar topography mission 1Arc-Second Digital Elevation Model data were utilized in this research. A total of 91 surface samples were collected across the study area at a depth between 0 and 30 cm and were analyzed via traditional laboratory analysis methods. Five environmental parameters were used in the design of the soil salinity model. A pairwise comparison matrix was used to calculate the factor weight value for each of the layers. A linear regression model was used to plot the relationship between the EC value and raster value of the salinity map derived from the overlay model. According to the results obtained from a pairwise comparison of the factor layers, water table level was the greatest influential factor of soil salinity, followed by landforms. The validation of the model demonstrated a high degree of correlation (R2 = 0.72) between the measured EC values and the salinity values derived from the model. Furthermore, this model could be a useful tool for predicting soil salinity with a suitable validation.