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Revision as of 23:38, 21 August 2024 by Sky (talk | contribs) (Created page with "{ "USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70211202", "url": "https://pubs.usgs.gov/publication/702112...")
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   "name": "Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing",
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   "datePublished": "2020",
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   "abstract": "Landslides modify the natural landscape and cause fatalities and property damage worldwide. Quantifying landslide dynamics is challenging due to the stochastic nature of the environment. With its large area of ~1 km2\u00a0and perennial motions at ~10\u201320\u2009mm per day, the Slumgullion landslide in Colorado, USA, represents an ideal natural laboratory to better understand landslide behavior. Here, we use hybrid remote sensing data and methods to recover the four-dimensional surface motions during 2011\u20132018. We refine the boundaries of an area of ~0.35 km2\u00a0below the crest of the prehistoric landslide. We construct a mechanical framework to quantify the rheology, subsurface channel geometry, mass flow rate, and spatiotemporally dependent pore-water pressure feedback through a joint analysis of displacement and hydrometeorological measurements from ground, air and space. Our study demonstrates the importance of remotely characterizing often inaccessible, dangerous slopes to better understand landslides and other quasi-static mass fluxes in natural and industrial environments, which will ultimately help reduce associated hazards.",
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