Debris flow initiation in postglacial terrain: Insights from shallow landslide initiation models and geomorphic mapping in Southeast Alaska
Debris flow initiation in postglacial terrain: Insights from shallow landslide initiation models and geomorphic mapping in Southeast Alaska
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冰后地形中的泥石流引发:来自阿拉斯加东南部浅层滑坡引发模型和地貌测绘的见解
DOI:
10.1002/esp.5336
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发表时间:
2022
影响因子:
3.3
通讯作者:
Orland, Elijah
中科院分区:
文献类型:
--
作者:
Patton, Annette I.;Roering, Joshua J.;Orland, Elijah
Debris flows pose persistent hazards and shape high‐relief landscapes in diverse physiographic settings, but predicting the spatiotemporal occurrence of debris flows in postglacial topography remains challenging. To evaluate the debris flow process in high‐relief postglacial terrain, we conducted a geomorphic investigation to characterize geologic, glacial, volcanic, and land use contributions to landslide initiation across Southeast Alaska. To evaluate controls on landslide (esp. debris flow) occurrence in Sitka, we used field observation, geomorphic mapping, landslide characteristics as documented in the Tongass National Forest inventory, and a novel application of the shallow landslide model SHALSTAB to postglacial terrain. A complex geomorphic history of glaciation and volcanic activity provides a template for spatially heterogeneous landslide occurrence. Landslide density across the region is highly variable, but debris flow density is high on south‐ or southeast‐facing hillslopes where volcanic tephra soils are present and/or where timber harvest has occurred since 1900. High landslide density along the western coast of Baranof and Kruzof islands coincides with deposition of glacial sediment and thick tephra and exposure to extreme rainfall from atmospheric rivers on south‐facing aspects but the relative contributions of these controls are unclear. Timber harvest has also been identified as an important control on landslide occurrence in the region. Focusing on a subset of geo‐referenced landslides near Sitka, we used the SHALSTAB shallow landslide initiation model, which has been frequently applied in non‐glacial terrain, to identify areas of high landslide potential in steep, convergent terrain. In a validation against mapped landslide polygons, the model significantly outperformed random guessing, with area under the curve (AUC) = 0.709 on a performance classification curve of true positives vs. false positives. This successful application of SHALSTAB demonstrates practical utility for hazards analysis in postglacial landscapes to mitigate risk to people and infrastructure.
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DOI:
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发表时间:
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期刊:
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