Abstract
Landslides produce large quantities of sediment deposits and reduce reservoir life. This study investigated landslides at the Shihmen Reservoir basin in Taiwan that were induced by Typhoon Sinlaku and Typhoon Jangmi in 2008. We formulate scaling relationships between landslide erosion volume and area and conclude that sediment budget can be estimated based on the easier-todetermine landslide erosion area. The methodologies applied for the investigation were geomorphological analysis through 5 m × 5 m digital terrain models (DTMs) of the basin created before and after the landslide events and spatial analysis through a geographic information system. The erosion area and volume of landslides were measured through the subtraction of DTMs produced before and after the events. Statistical analysis revealed that the landslide erosion frequency–magnitude distribution exhibited power-law behaviors with a scaling exponent of 2.15 for the frequency–area distribution and 1.66 for the frequency–volume distribution. This paper proposes different scaling relationships for different moving depths, and landslide erosion volumes were estimated on the basis of depth; thus, landslides of different scales can be distinguished to avoid errors in volume estimation. Two different scaling exponents are proposed: 1.21 for landslide erosions with depths of less than 2 m and 1.01 for landslide erosions with depths of more than 2 m. The proposed scaling relationships are practical for landslide erosion volume estimation by different depths according to the landslide area, and they can provide preliminary results for sediment budget planning in a reservoir basin.
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Acknowledgements
Great gratitude goes out to Soil and Water Conservation Bureau (SWCB) in Taiwan for providing valuable materials (SWCB-106-054) for this study and to our anonymous reviewers for their useful comments.
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Chen, Sc., Chen, Cy. & Huang, Wy. Exploring landslide erosion volume–area scaling relationships by slip depth using changes in DTMs for basin sediment volume estimation. J. Mt. Sci. 16, 581–594 (2019). https://doi.org/10.1007/s11629-018-4888-3
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DOI: https://doi.org/10.1007/s11629-018-4888-3