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A New Approach to Mapping Landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA - Research Data
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Type: | Resource | |
Storage: | The size of this resource is 182.7 MB | |
Created: | Nov 04, 2019 at 4:33 a.m. | |
Last updated: | Nov 07, 2019 at 3:56 p.m. (Metadata update) | |
Published date: | Nov 07, 2019 at 3:56 p.m. | |
DOI: | 10.4211/hs.6d8c3c46f4c8422796f28584eb9bdfaa | |
Citation: | See how to cite this resource |
Sharing Status: | Published |
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Views: | 2479 |
Downloads: | 124 |
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Abstract
https://www.hydroshare.org/resource/6d8c3c46f4c8422796f28584eb9bdfaa/
We developed a new approach for mapping landslide hazard combining probabilities of landslide impact derived from a data-driven statistical approach applied to three different landslide datasets and a physically-based model of shallow landsliding. This data includes the site characteristics used in the empirical approach to derive a susceptibility index (SI) and a probability of failure, and the physically based probability derived from a previous regional study (see Related Resources). These probabilities are integrated into a weighting term that is used to adjust the physical model of landslide initiation to account for empirical evidence not captured by the infinite slope stability model alone. The data and modeling are for a 30 meter grid resolution study domain in the North Cascades National Park Complex, Washington, U.S.A (see Resource Coverage).
The data are provided as Esri ArcGIS shapefiles and rasters, as well as an example ASCII files for one raster and the header for conversion of ASCII to raster. Spatial reference for raster mapping is NAD_1983, Albers conical equal area projection. Elevation was acquired from National Elevation Dataset (NED) at 30 m grid scale; other datasets are matched to scale and location. Curvature, slope (tan theta), and aspect are derived from elevation. A wetness index, divided into five categories, is derived from elevation calculated as the natural log of the ratio of the specific catchment area to the sine of the local slope. Land use and land cover (LULC) data were acquired from USGS National Land Cover Data (NLCD) based on 2011 Landsat satellite data and grouped into eight general categories. Mapped landslides were provided by the National Park Service (NPS) from a landform mapping inventory. Source areas used to define initiation zones were identified as the upper 20% of debris avalanche landslide types. Lithology is provided by Washington State Department of Natural Resources surface geology maps and is grouped into seven categories. Other layers include the boundary of the national park used to demonstrate the model, the area included in the analysis (i.e., excluding high-elevation areas covered by glaciers, permanent snowfields, and exposed bedrock, wetlands and other water surfaces, and slopes less than 17 degrees), the empirical based SI, the calculated weight, and the probabilities of landslide activity for the empirical, physical, and weight-adjusted physical models. Additional data and information that supports this research or facilitates future research is available in Supplementary Information (See Related Resources).
This repository holds the data used in the paper: A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA, published in Natural Hazards and Earth System Sciences 19, 1-19, 2019.
Subject Keywords
Coverage
Spatial
Content
Related Resources
This resource is referenced by | Strauch, R., Istanbulluoglu, E. and Riedel, J. A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades ofWashington, USA, Nat. Hazards Earth Syst. Sci., 19, 1–19, 2019. |
The content of this resource references | Strauch, R., Istanbulluoglu, E., Nudurupati, S. S., Bandaragoda, C., Gasparini, N. M., and Tucker, G. E.: A hydro-climatological approach to predicting regional landslide probability using Landlab, Earth Surf. Dynam., 6, 49–75, https://doi.org/10.5194/esurf- 6-49-2018, 2018. |
Credits
Funding Agencies
This resource was created using funding from the following sources:
Agency Name | Award Title | Award Number |
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US National Science Foundation | CBET | 1336725 |
US National Science Foundation | ICER, PREEVENTS | 1663859 |
US Department of Interior, US Geological Society, Northwest Climate Adaptation Science Center | Graduate Fellowship Award | GS240B-B |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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