DOI: 10.11648/j.earth.20261505.12 ISSN: 2328-5982

GIS-Based Mapping and Geodatabase Development for Expansive Soils: A Case Study of Selected Towns in the Wolaita Zone, Southern Ethiopia

Ashenafi Balango, Fitsum Markos, Eyob Shanka
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Expansive soils cause costly damage to infrastructure through seasonal moisture-driven swelling and shrinkage, yet in many developing regions the geotechnical data needed to manage this hazard remains fragmented across paper records and individual project reports. This study addresses that gap by evaluating the engineering properties of expansive soils in three rapidly urbanizing towns in the Wolaita Zone of southern Ethiopia, namely Tebela, Wolaita Sodo, and Boditi, and consolidating the results into a spatially referenced ArcGIS geodatabase to support preliminary engineering design. Fourteen test pits were investigated following ASTM and AASHTO standards, combining ten newly collected field samples with four secondary data sources; index and strength properties, including Atterberg limits, free swell index, swelling pressure, and California Bearing Ratio, were determined in the laboratory, and all test-pit locations were captured by GPS and georeferenced onto rectified imagery in UTM Zone 37N. The results classified the soils at Tebela and Wolaita Sodo as highly plastic clays (CH, AASHTO A-7-5) with high fines contents of 91.8 to 95.1%, free swell indices exceeding 100%, and swelling pressures of 145 to 170 kPa, while the Boditi soils were similarly classified as high-plasticity clays (CH, A-7-6) but showed low California Bearing Ratio values of 2.2 to 2.8%, indicating weak subgrade support. These laboratory results, together with the GPS coordinates, were structured in an ArcGIS file geodatabase organized by town and test pit, with fully searchable laboratory attributes. The resulting system converts scattered paper-based geotechnical records into an interactive, query able geospatial tool and offers an adaptable workflow that can be extended to manage expansive soil risk in other regions facing similar infrastructural and data-management challenges.

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