Thunder Creek Landlab Landslide Example
|Authors:||Ronda Strauch Erkan Istanbulluoglu Sai Nudurupati Christina Bandaragoda Jon Riedel|
|Storage:||The size of this resource is 113.5 MB|
|Created:||Jun 09, 2016 at 10:34 p.m.|
|Last updated:||Jun 20, 2018 at 4:31 p.m. by Ronda Strauch|
|Citation:||See how to cite this resource|
This example runs the 'landslide' component of Landlab and is designed for undergraduate and graduate students interested in learning more about Landlab and landslide modeling. Landlab is a Python-based landscape modeling environment and the landslide component is one of many components available for users to access and link together to build their own landscape model. For more information about Landlab, see http://landlab.github.io/#/. Data needed for the example are spatial data on landscape characteristics for Thunder Creek watershed in North Cascade mountains of Washington. They include soil, geology, vegetation, topography, and landform data that can be used for earth surface analyses such as landslides and hydrology. Thus, the data can be used for more than this landslide example. Elevation was acquired from STRM at 30 m grid scale; the other datasets are matched to in scale and location. Slope was derived from the elevation file and represents dimensionless "tan theta". Specific contributing area represents the 'upstream' area draining to each cell divided by the cell's width (so minimum value is 30 m). Landform data was developed by Jon Riedel of National Park Service. Landslides were extracted from these data as "mass wasting" events. 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. Washington State Department of Natural Resources (WADNR) provides the source of lithology in its surface geology maps that displays rocks and deposits as geologic map units. These were aggregated into eight classes based on similarities in origin and generally increasing strength by Dr. Riedel. Cohesion represent root cohesion based on the LULC ; soils are assumed to be primarily cohesionless, lacking “true cohesion” because of their low clay content in this mountain terrain. Soil depth comes from NRCS soil survey depth-to-restricted layer (weighted-average aggregation) within each soil map unit. Transmissivity was derived from the soil survey saturated hydraulic conductivity (depth averaged) multiplied by depth-to-restricted layer for each soil map unit. All soils within this watershed are sandy loam or loamy sand; therefore, soil surface texture was used as an indicator of internal angle of friction (phi). A header file is also provided to understand the spatial details of the ASCII files and to facilitate capability with GIS. Projection for raster mapping is NAD_1983_UTM_Zone_10N.
Resource Level Coverage
|Title||Owners||Sharing Status||My Permission|
|Landlab CUAHSI Colloqium 2016 Workshop||Christina Bandaragoda||Public & Shareable||Open Access|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||CBET Environmental Sustainability Program||1336725|
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