Abstract Landslides, a forest disturbance, mobilize carbon (C) sequestered in vegetation and soils. Mobilized C is deposited either onto hillslopes or into the water, sequestering C from and releasing C to the atmosphere at different time scales. The C‐dense old‐growth temperate forests of SE Alaska are a unique location to quantify C mobilization rate by frequent landslides that often evolve into saturated moving masses known as debris flows. In this study, the amount of C mobilized by debris flows over historic time scales was estimated by combining a landslide inventory with maps of modeled biomass and soil carbon. We analyzed SE Alaskan landslides over a 55‐year period where a total of 4.69 ± 0.21 MtC was mobilized, an average rate of 2.5 tC km−2 yr−1. A single event in August 2015 mobilized 57,651 ± 3,266 tC, an average of 63 tC km−2. Depositional fate was inferred using two methods, a standard stream intersection analysis and a second novel approach using simulated debris flow deposition modeling calibrated to the study area. Approximately 60% of debris flow deposits intersected the stream network (9% into mainstem channels, 91% into small tributaries), consistent with long‐term modeled connectivity, suggesting that debris flows are likely to contribute to globally significant amounts of C buried in local fjord sediments. Our results are consistent with an emerging consensus that landslide disturbances that mobilize organic carbon may play an important role in the global carbon cycle over geologic time, with coastal temperate forests being hotspots of potential carbon sequestration.
more »
« less
Geomorphology and initiation mechanisms of the 2020 Haines, Alaska landslide
Abstract In early December 2020, an atmospheric river (AR) and rain-on-snow (ROS) event impacted the Haines, Alaska area, resulting in record-breaking rainfall and snowmelt that caused flooding and dozens of mass movement events. We consider the AR—a one-in-500-year event—as the trigger for the devastating Beach Road Landslide (BRLS), which destroyed or damaged four residences and took the lives of two people. The BRLS started as a debris avalanche and transitioned into a debris flow, with a total approximate landslide volume of 187,100 m3. Geomorphic analysis using lidar data identified evidence of paleo-landslides and displaced masses of rock, one of which served as the source area for the BRLS. Significant structural features in the weak ultramafic bedrock defined the head scarp area and formed the failure plane. This study illustrates the importance of identifying pre-existing landslide features and source areas likely to produce future landslides. As an increase in ROS events is projected for Southeast Alaska with warmer and wetter winters, we recommend the development of an AR scale coupled with geological information for the region, to enhance warnings to residents in landslide-prone areas.
more »
« less
- Award ID(s):
- 2114015
- PAR ID:
- 10369417
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Landslides
- Volume:
- 19
- Issue:
- 9
- ISSN:
- 1612-510X
- Page Range / eLocation ID:
- p. 2177-2188
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract 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.more » « less
-
Abstract Bedrock landsliding, including the formation of landslide dams, is a predominant geomorphic process in steep landscapes. Clarifying the importance of hydrologic and seismic mechanisms for triggering deep‐seated landslides remains an ongoing effort, and formulation of geomorphic metrics that predict dam preservation is crucial for quantifying secondary landslide hazards. Here, we identify >200 landslide‐dammed lakes in western Oregon and utilize dendrochronology and enhanced14C dating (“wiggle matching”) of “ghost forests” to establish slope failure timing at 20 sites. Our dated landslide dataset reveals bedrock landsliding has been common since the last Cascadia Subduction Zone earthquake in January 1700 AD. Our study does not reveal landslides that date to 1700 AD. Rather, we observe temporal clustering ofat leastfour landslides in the winter of 1889/1890 AD, coincident with a series of atmospheric rivers that generated one of the largest regionally recorded floods. We use topographic and field analyses to assess the relation between dam preservation and topographic characteristics of the impounded valleys. In contrast to previous studies, we do not observe systematic scaling between dam size and upstream drainage area, though dam stability indices for our sites correspond with “stable” dams elsewhere. Notably, we observe that dams are preferentially preserved at drainage areas of ∼1.5 to 13 km2and valley widths of ∼25 to 80 m, which may reflect the reduced downstream influence of debris flows and the accumulation of mature conifer trees upstream from landslide‐dammed lake outlets. We suggest that wood accumulation upstream of landslide dams tempers large stream discharges, thus inhibiting dam incision.more » « less
-
Abstract. We developed a new approach for mapping landslide hazards by combiningprobabilities of landslide impacts derived from a data-driven statisticalapproach and a physically based model of shallow landsliding. Ourstatistical approach integrates the influence of seven site attributes (SAs) onobserved landslides using a frequency ratio (FR) method. Influential attributesand resulting susceptibility maps depend on the observations of landslidesconsidered: all types of landslides, debris avalanches only, or source areasof debris avalanches. These observational datasets reflect the detection ofdifferent landslide processes or components, which relate to differentlandslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical andphysically based probabilities as indices and calculates a joint probabilityof landsliding at the intersections of probability bins. A ratio of thejoint probability and the physically based model bin probability is used asa weight to adjust the original physically based probability at each gridcell given empirical evidence. The resulting integrated probability oflandslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentiallyunstable areas with the proposed integrated model are statisticallyquantified. We provide multiple landslide hazard maps that land managers canuse for planning and decision-making, as well as for educating the publicabout hazards from landslides in this remote high-relief terrain.more » « less
-
Abstract Landslides commonly occur in areas with steep topography and abundant precipitation and pose a significant hazard to local communities. Some of the largest known landslides occur in Alaska, including several that caused local tsunamis. Many landslides may have gone undetected in remote areas due to lack of observations. Here, we develop a semiautomated workflow using both seismic and geodetic observations to detect, locate, validate, and characterize landslides in Alaska. Seismic observations have shown promise in continuously monitoring landslide occurrence, while remote sensing techniques are well suited for verification and high‐resolution imaging of landslides. We validate our procedure using the 28 June 2016, Lamplugh Glacier landslide. We also present observations of a previously unknown landslide occurred on 22 September 2017 in the Wrangell Mountains region. The Wrangell Mountains landslide generated a coherent surface wavefield recorded across Alaska and the contiguous United States. We used Sentinel‐1 Synthetic Aperture Radar and Sentinel‐2 optical imagery to map the respective mass deposit. To investigate the landslide dynamics, we inverted regional seismic surface wave data for a centroid single force failure model. Our model suggests that the Wrangell Mountains landslide lasted for about 140 s and had two subevents involving at least five distinct stages. We estimate that the landslide had displaced 3.1–13.4 million tons of rocks over a distance of ∼2 km. Our results suggest that combining seismic and geodetic observations can vastly improve the detection and characterization of landslides in remote areas in Alaska and elsewhere, providing new insights into the landslide dynamics.more » « less
An official website of the United States government
