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Revista Ingenierías Universidad de Medellín

versión impresa ISSN 1692-3324versión On-line ISSN 2248-4094

Resumen

ECHEVERRI-SANCHEZ, Andrés. METHODOLOGICAL PROPOSAL TO ASSESS THE VULNERABILITY OF SOILS TO SALINIZATION IN FLAT AREA IRRIGATION DISTRICTS. Rev. ing. univ. Medellín [online]. 2022, vol.21, n.40, pp.28-43.  Epub 31-Oct-2022. ISSN 1692-3324.  https://doi.org/10.22395/rium.v21n40a3.

Soil salinization is one of the main constraints for food production. These processes occur mainly in irrigated areas, due to natural conditions and inadequate fertilization and irrigation practices. The objective of this article was to generate a model to identify and spatialize the levels of vulnerability to soluble phase salinization in the irrigation districts of Colombia as a complementary tool for the management of soil salinization risk. Two tools were integrated to achieve the objective. On the one hand, the multi-criteria analysis method called Analytic Hierarchy Process (AHP) was applied to assign weights to the analysis parameters and build the Soil Vulnerability to Salinization Index (SVSS), and on the other hand, geographic information systems (GIS) were applied to spatialize the analysis parameters and the SVSS, as well as to define the homogeneous vulnerability zones. Finally, the model was applied to a case study. The resulting model considered vulnerability parameters. The most important are Aridity Index, Soil Texture and Fertilization Practices. On a second level are Drainage Infrastructure and Depth of the Water Level. Other factors considered were Slope of the land, Irrigation Water Application Efficiency and Irrigation Water Distribution Pattern. In the case study it was found that 71.8 % of the territory presents Medium Vulnerability and 27.9 % High Vulnerability. The determining parameters of these results were the low efficiencies of irrigation water application, inadequate fertilization practices, clayey textures and lack of subsurface drainage systems.

Palabras clave : soil degradation; risk assessment; GIS; multi criteria decision analysis..

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