Assessing salt-affected soils using remote sensing, solute modelling, and geophysics

Salinization and alkalinization are the most common land degradation processes, particularly occurring in and and semi-arid regions, where precipitation is too low to maintain a regular percolation of rainwater through the soil. Under such a climatic condition, soluble salts are accumulated in the soil, influencing soil properties and environment which cause lessening of the soil productivity. The consistent identification of the processes is essential for sustainable soil management. Identification, large scale mapping and monitoring of the salt-affected areas have been done using three different data and techniques. Remote sensing has been widely used to detect and map salt-affected areas, since thousands of medium to high-resolution imageries from the earth surface are available. In practice, most of these studies have focused oil severely saline areas and have given less attention to the detection and monitoring of slightly or moderately affected areas. The major constrain is related to the nature of the satellite images, which do not allow extracting information from the third dimension of the 3-D soil body e.g., where salts concentrate in subsoil. Solute transport modelling is another technique which is used to predict the salt distribution in the subsoil. It has the advantage of providing subsoil information on dynamics of the salt movement regimes. This technique provides complementary data on salt movement in the soil profile which can be used in combination with remote sensing data. Since a few years, near-surface geophysics sensors, particularly airborne, are widely used to map and monitor salt-affected areas. This technology has the advantage of effectiveness for cropped land and can efficiently be used to highlight conductive areas where no surface expression of salt is evident. The paper outlines the conceptual framework of a method where the data obtained from optical remote sensing sensors should be integrated with the results of simulation models and geophysical survey in order to predict different levels (low, moderate, severe) of salinization/alkalinization in a cost-attractive and efficient way. In the proposed integrated method, data are combined not only to demarcate the existing salt-affected soils, but also to track down the salinization as a pedogenic process. Such an approach focuses on the integration of the data with different natures and scales, meaning that data fusion and upscaling are strongly involved. (C) 2005 Elsevier B.V. All rights reserved.