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.

本示例运行Landlab的滑坡（landslide）组件，专为希望深入了解Landlab与滑坡建模的本科生与研究生打造。Landlab是一款基于Python的景观建模环境，其滑坡组件仅是可供用户调用并相互拼接以构建自定义景观模型的众多组件之一。如需了解Landlab的更多信息，请访问http://landlab.github.io/#/。本示例所需数据为华盛顿州北喀斯喀特山脉雷霆溪（Thunder Creek）流域的景观特征空间数据，涵盖土壤、地质、植被、地形与地貌数据，可用于滑坡、水文等地表过程分析，因此该数据集的应用场景不止于本滑坡示例。高程数据来源于分辨率为30米网格的STRM，其余数据集均在比例尺与空间位置上与之匹配。坡度由高程文件导出，以无量纲的“tanθ”形式表示。比汇水面积指的是汇入每个栅格单元的上游汇水面积除以该单元的宽度，因此其最小值为30米。地貌数据由美国国家公园管理局的Jon Riedel开发，滑坡事件则从上述数据中以“mass wasting（块体运动）”事件的形式提取得到。土地利用与土地覆被（Land use and land cover, LULC）数据来源于基于2011年Landsat卫星影像的美国地质调查局（United States Geological Survey, USGS）国家土地覆被数据（National Land Cover Data, NLCD），并被划分为8个大类。华盛顿州自然资源局（Washington State Department of Natural Resources, WADNR）提供了地表地质图的岩性数据，该类地图以地质填图单元的形式展示岩石与沉积物。Riedel博士根据成因相似性与强度整体递增的原则，将其整合为8类。黏聚力（Cohesion）代表基于土地利用与土地覆被数据的根系黏聚力；由于该山地地形的土壤黏土含量较低，因此默认土壤以无黏聚力为主，不存在“真黏聚力”。土壤深度数据来源于美国自然资源保护局（Natural Resources Conservation Service, NRCS）的土壤调查数据，即每个土壤制图单元内限制性土层深度的加权平均聚合值。导水率（Transmissivity）由土壤调查所得的饱和导水率（深度加权平均值）乘以每个土壤制图单元的限制性土层深度得到。该流域内的所有土壤均为砂壤土或壤质砂土，因此以土壤表层质地作为内摩擦角（φ）的指示指标。本示例还附带了一个头文件，用于阐释ASCII文件的空间细节，并便于与地理信息系统（Geographic Information System, GIS）兼容。栅格制图的投影坐标系为NAD_1983_UTM_Zone_10N。