Developing an Interactive Tool for Identifying Flood-Prone Areas Based on the Topographic Wetness Index
Presentation Time: Thu, 05/01/2025 - 11:00
Keywords: Topographic Wetness Index, Flooding, Python Scripting, Raster Analysis, Digital Elevation Model
Determining areas at risk of flooding is critical to minimizing the damage and losses that floods can cause. Geographic Information Systems can map regions of general flood vulnerability through more rapid methods than complex hydrological models. This project aimed to develop an easily operated tool to locate potentially flood-prone landscape areas by applying the Topographic Wetness Index to measure how terrain influences water runoff and accumulation. The result was an interactive Jupyter Notebook that provided detailed steps on using Python code blocks to perform index calculations. Functions of the tool included automating the downloading process for Digital Elevation Models based on user-provided coordinates and performing raster analysis to determine the input parameters of flow directions, accumulated flow, and slope gradients. A set of optional steps could process the index results according to the needs of the user through low-pass filtering, range scaling, and custom symbolization. The project provided an example of how the tool performs by comparing index values from Digital Elevation Models at differing resolutions to descriptions of localized flooding risks in Lake County, Oregon. The Topographic Wetness Index tool effectively demonstrated a practical approach for land use planning purposes that uses minimal inputs to identify areas susceptible to flooding.
