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Site characterization is a prerequisite for the successful and economic design of engineering structures and earthworks by providing geological information for any proposed project. Until now, no detail study has been carried out on the site characterization and classification using shear wave velocity (Vs) up to the top 30 m depth in Hawassa town. For this study, multichannel analysis of surface waves (MASW) was used to determine the variation of Vs for a proper civil engineering design in the town. In addition, vertical electrical sounding (VES) and standard penetration test (SPT) were employed to characterize the near-surface materials. The Vs30 map was prepared for Hawassa town using the estimated Vs30 values which ranges from 248.9 m/s to 371.3 m/s while the SPT-N values were ranges from 5bpf to 50bpf. The correlation of Vs and SPT-N values has been done by considering both corrected and uncorrected SPT-N values. The VES result showed that groundwater is found at a shallow depth. The correlation of Vs and SPT-N value was validated using regression model. The 1D Vs profile and 2D cross-section showed low Vs at a shallow depth. The near-surface soils of the town are classified based on the Vs30 as site class C (stiff soil and soft rock) and D class (stiff soils) according to the NEHRP (Natural Earthquake hazards Reduction Program) and as subsoil classes B and C according to the Eurocode 8. The geotechnical tests also showed that the soils in the study area are silty sand, sand and silty sand with some gravel. The low Vs values observed at a shallow depth should be given much attention during foundation design for the stability of civil engineering structures. [ABSTRACT FROM AUTHOR]

Landslide risk assessment is an extension of landslide hazard or susceptibility mapping. It is the most critical component of a landslide hazard reduction plan. The present study was carried out in Shafe and Baso catchments which are found in Gamo high land of Southern Ethiopia and are about 437 km south of Addis Ababa. The areal extent of the present study area is about 284 km2. This research was mainly aimed to characterize the landslide risk in the study area for rural population their property and services. In the present research, the landslide risk assessment was made with a major limitation of archived data. In order to overcome the deficiency of landslide data, the danger pixel concept and fuzzy set theory were utilized to evaluate the landslide risk in the study area. In the former approach total number of pixels of different resources that were affected by the landslide hazard in the area was determined. Similarly, the fuzzy set theory, a semi-quantitative method, was used to characterize the risk level of each resource in the study area. This fuzzy linguistic approach has characterized landslide risk in to a matrix form which was further used to determine the landslide risk in the study area. The resource categories that were considered in this research were; settlement, agricultural land, moderate forest, sparse forest, rangeland, bare land, and water body. The risk assessment maps prepared by both methods have delineated different risk zones with more or less similar area coverage. In the landslide risk map, the risk was classified into five classes; very high risk (6.86%), high risk (21.15%), moderate (43.26%), low (10.97%), and very low risk (17.76%). Thus, based on the results, suitable biological and mechanical remedial measures are required to mitigate the landslide hazard in the study area. These measures are particularly required to control the landslide triggering factors such as; gulley erosion, stream erosion, human activities, and groundwater conditions. [ABSTRACT FROM AUTHOR]