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Characteristics of landslides in unwelded pyroclastic flow deposits, southern Kyushu, Japan
Journal article   Open access   Peer reviewed

Characteristics of landslides in unwelded pyroclastic flow deposits, southern Kyushu, Japan

M Yamao, Roy C Sidle, T Gomi and F Imaizumi
Natural Hazards and Earth System Sciences, Vol.16, pp.617-627
2016
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https://doi.org/10.5194/nhess-16-617-2016View
Published Version

Abstract

We investigated 184 landslides that occurred in unwelded pyroclastic flow deposits (Shirasu) on southern Kyushu Island, Japan, that included detailed data on the rainfall characteristics and the timing of slope failure. Localized rainfall intensity, antecedent precipitation index (API), and topography affected the hydrologic processes that triggered landslides. API (adjusted for evapotranspiration losses) for large ( > 200 mm) storms that triggered landslides was much lower than for smaller (≤ 200 mm) storms. Mean storm intensity and 7-day API (API7) thresholds of > 5 mm h-1 and ≤ 30 mm (or API30 ≤ 60 mm), respectively, were useful to identify landslides triggered by rapid pore water pressure response, especially for shorter (< 20 h) duration events. During smaller storms with lower intensity, landslides are likely affected by a combined increase in soil weight and loss of suction when API30 ≥150 mm; simulations indicated that these weight and suction changes due to rainfall accumulation decreased the factor of safety in steep Shirasu slopes, but did not necessarily trigger the landslides. Most of the landslides that were plotted below a general rainfall intensity-duration threshold for landslide initiation occurred during smaller storms with API30 values > 200 mm, indicating that they were highly influenced by the combined effects of the accumulated weight of rainfall and loss of suction. Our findings show that both event rainfall characteristics and API affect the hydrogeomorphic processes that trigger different types of landslides in Shirasu. This knowledge and the thresholds we have identified are useful for predicting the occurrence of different types of landslides in unwelded Shirasu deposits and improving sediment disaster prevention practices, including real-time warning systems.

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