Calculating Runoff using TOPMODEL (M6)

This resource contains data inputs and an iPython Jupyter Notebook used to simulate semi-distributed variable source area runoff generation in a tributary to the Logan River. This resource is part of the HydroLearn Physical Hydrology learning module available at https://edx.hydrolearn.org/courses/course-v1:Utah_State_University+CEE6400+2019_Fall/about.

In this activity, the student learns how to (1) calculate the topographic wetness index using digital elevation models (DEMs) following up on a previous module on DEMs and GIS in Hydrology; (2) apply TOPMODEL concepts and equations to estimate soil moisture deficit and runoff generation across a watershed given necessary watershed and storm characteristics; and (3) critically assess concepts and assumptions to determine if and why TOPMODEL is an appropriate tool given information about a specific watershed.

Please note that this exercise sets up the data needed to estimate runoff in the Spawn Creek watershed using TOPMODEL. Spawn Creek is a tributary of the Logan River, Utah. This exercise uses some of the same data as the Logan River Exercise in Digital Elevation Models and GIS in Hydrology at https://www.hydroshare.org/resource/9c4a6e2090924d97955a197fea67fd72/. If running the TOPMODEL for other study sites, you need to prepare a DEM TIF file and an outlet shapefile for the area of interest.
- There are several sources to obtain DEM data. In the U.S., the DEM data (with different spatial resolutions) can be obtained from the National Elevation Dataset available from the national map (http://viewer.nationalmap.gov/viewer/). Another DEM data source is the Shuttle Radar Topography Mission (https://www2.jpl.nasa.gov/srtm/), an international research effort that obtained digital elevation models on a near-global scale (search for Digital Elevation at https://www.usgs.gov/centers/eros/science/usgs-eros-archive-products-overview?qt-science_center_objects=0#qt-science_center_objects).
- If not already available, you can generate the outlet shapefile by applying basic terrain analysis steps in geospatial information system models such as ArcGIS or QGIS.

本资源包含用于模拟洛根河（Logan River）支流半分布式变源区产流的数据集输入文件，以及一份IPython Jupyter笔记本。本资源隶属于HydroLearn物理水文学学习模块，该模块可通过https://edx.hydrolearn.org/courses/course-v1:Utah_State_University+CEE6400+2019_Fall/about获取。

在本实践活动中，学习者将掌握以下内容：(1) 结合此前水文学领域数字高程模型（Digital Elevation Model, DEM）与地理信息系统（Geographic Information System, GIS）相关模块的知识，基于数字高程模型计算地形湿度指数（topographic wetness index）；(2) 应用TOPMODEL的概念与公式，结合给定的流域与暴雨特征参数，估算流域内土壤水分亏缺量与产流情况；(3) 批判性评估相关概念与假设，结合特定流域的信息判断TOPMODEL作为研究工具的适用性及其原因。

请注意，本实践活动为使用TOPMODEL估算斯蓬溪（Spawn Creek）流域的产流情况准备了所需数据。斯蓬溪是犹他州洛根河的一条支流。本实践活动使用了与《水文学中的数字高程模型与地理信息系统》课程中洛根河实践项目（https://www.hydroshare.org/resource/9c4a6e2090924d97955a197fea67fd72/）相同的部分数据集。若需将本工具应用于其他研究区域，则需要为目标区域准备DEM TIF文件与流域出口矢量shapefile文件。

- 可通过多种渠道获取DEM数据：在美国境内，不同空间分辨率的DEM数据可从国家高程数据集（National Elevation Dataset）获取，该数据集可通过美国国家地图服务平台（http://viewer.nationalmap.gov/viewer/）下载；另一DEM数据源为航天飞机雷达地形测绘任务（Shuttle Radar Topography Mission, SRTM），这是一项近乎全球尺度的数字高程模型获取国际科研项目，相关数据可在https://www.usgs.gov/centers/eros/science/usgs-eros-archive-products-overview?qt-science_center_objects=0#qt-science_center_objects页面搜索“Digital Elevation”获取。
- 若未获取到现成的流域出口shapefile文件，可通过ArcGIS或QGIS等地理信息系统软件中的基础地形分析步骤生成。