Landslide Hazard Evaluation and Zonation in the area Kindo Didaye, South West, Ethiopia
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Date
2016-05
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Addis Ababa Universty
Abstract
In the present study landslide hazard evaluation and zonation (LHZ) was carried out in the area Kindo Didaye Woreda in South western Ethiopia, about 450 km South West of Addis Ababa, the capital city of Ethiopia. The main objective of the present study was to evaluate landslide hazard zonation by using integrated Slope stability Susceptibility Evaluation Parameter (SSEP) expert technique and a raster based Information Value statistical approach.
In the case of Landslide Hazard Zonation carried out by Slope stability Susceptibility Evaluation Parameter (SSEP) the landslide hazard zonation of the study area was carried out through facet wise Evaluated landslide hazard which indicates the net probability of instability. Relative relief, slope morphometry, slope material, structural discontinuity, landuse/landcover, groundwater surface manifestations are intrinsic causative parameters that were considered in this method. The external causative parameters include: rain induced manifestations, seismicity and manmade developmental activities. The area has been classified into 102 facets. The data for above mentioned have been collected and the rating values were given based on SSEP rating scheme for each causative parameters. The Evaluated landslide hazard (ELH) for an individual facet was obtained by adding the ratings of individual parameter obtained from the SSEP rating scheme. Later, landslide hazard zonation has been classified into three classes.
For integrated SSEP and a raster based Information Value method the methodology followed was based on the analysis of seven causative parameters and past landslides in the study area. For the present study seven causative parameters namely; relative relief, slope morphometry, slope material, landuse/landcover, groundwater surface manifestations, rain induced manifestations and manmade developmental activities were considered. Later, Information value was calculated based on relative influences of causative factors on past landslides. The landslide inventory mapping for this study has been prepared using through field investigation and google earth image interpretation. The distribution of landslide over each of each of factor maps have been obtained and analyzed. Weights for each of the classes within these factor maps have been obtained using the information value method. Final landslide susceptibility value for each pixel within the study area has been obtained using by summing up the weight derived for that pixel in all of the factor maps. The resultant landslide susceptibility index map has been classified in to three landslide hazard zonation classes.
The landslide hazard zonation map of the study area through SSEP method shows that moderate hazard zone covers 21 % (18 km2), high hazard Zone covers 63% (54 km2) and very high hazard zone covers 16% (13 km2) of the total study area. In case of the landslide hazard map of the study area through integrated SSEP and raster based statistical information value 24%(20km2) area fall in the moderately hazard zone whereas 41%(35km2 ) and 35%(30km2) and of the area fall high and very high hazard zone , respectively. In the case of landslide hazard zonation map through SSEP method, out of 71 landslides inventory data 2 falls (3%) in moderate hazard zone, 50 falls (71%) in high hazard zone and 19 falls (27%) on very high hazard zone. Whereas, landslide hazard zonation map of the study area through SSEP and raster based Information Value method, out of 71 landslide inventory data 4 (6%) falls in moderate hazard zone, 14 (20%) falls in high hazard zone and 53 (74%) falls on very high hazard zone. The verified landslide hazard zonation maps indicates that 94 % of inventory data fall on high and very high hazard zones in both the approaches. The validation of LHZ map thus, reasonably showed that the adopted methodology produced satisfactory results and the delineated hazard zones may practically be applied for the regional planning and development of infrastructures in the area.
Key words: landslide, landslide hazard zonation, Information Value Model, SSEP, validation
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Keywords
landslide, landslide hazard zonation, Information Value Model, SSEP, Validation