Thunder Creek Landlab Landslide Example

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.

本例运行Landlab的'滑坡'组件，旨在为对Landlab及滑坡建模感兴趣的本科生和研究生提供学习资源。Landlab是一款基于Python的景观建模环境，其中滑坡组件是众多可供用户访问和链接以构建自有景观模型的功能组件之一。欲了解更多关于Landlab的信息，请参阅http://landlab.github.io/#/。本例所需数据为华盛顿州北喀斯喀德山脉中Thunder Creek流域的景观特征空间数据，包括土壤、地质、植被、地形和地貌数据，可用于地表分析，如滑坡和水利研究。因此，这些数据可用于本滑坡示例之外的其他用途。高程数据来自STRM，分辨率为30米网格；其他数据集在尺度和位置上与之匹配。坡度由高程文件导出，代表无单位的'tan theta'。特定贡献面积代表每个单元格的'上游'排水区域，除以单元格宽度（最小值为30米）。地貌数据由国家公园管理局的Jon Riedel开发。滑坡从这些数据中提取为'物质流失'事件。土地利用和土地覆盖（LULC）数据基于2011年Landsat卫星数据从美国地质调查局国家土地覆盖数据（NLCD）获取，并分为八个一般类别。华盛顿州自然资源部（WADNR）提供了其地表地质图中的岩性和沉积物来源，这些被根据起源相似性和通常随强度增加的顺序由Riedel博士聚集成八个类别。粘结力代表基于LULC的根粘结力；假定土壤主要为非粘结性，因为在此山地地形中其粘土含量低，缺乏“真正的粘结力”。土壤深度来自NRCS土壤调查的每个土壤图单元的限制层深度（加权平均聚合）。透水性由每个土壤图单元的土壤调查饱和水力传导率（深度平均）乘以限制层深度得出。该流域内的所有土壤均为沙壤土或壤沙土；因此，土壤表面纹理被用作内摩擦角（phi）的指示器。还提供了一个头文件，以了解ASCII文件的空间细节，并便于与GIS的结合。栅格映射的投影为NAD_1983_UTM_Zone_10N。