Dae San, SEES Earth System Explorer, 2024 - GLOBE International STEM Network

Our project for SEES 2024 was "Creating a Model to Identify High-Risk Areas for Flash Flooding in Houston, Texas." In this blog, I will discuss how we calculated which areas are "high-risk."

There are many ways to identify the most at-risk points of flooding in a given region. Such points are commonly identified in a flood map, such as the one here:

For our project, we decided to look at elevation data, which is perhaps the most intuitive: water flows downhill and will accumulate in the lowest regions. To get our elevation data, we used opentopography.org, which has free global elevation data with a minimum of 10m accuracy. On the website, we used the "select a region" feature to isolate specific Houston AOIs and download the elevation data in a .TIF file.

The .TIF files contain what is called an "elevation raster." This is a two-dimensional grid made of longitude and latitude coordinates, and it has an elevation value at each point. Here is an example (AOI #3, Houston) where the elevations are represented by color:

We need to convert our raw elevation data into a flood map. To do this, we perform something called D8 flow analysis. This is an algorithm that takes an elevation raster (input) and converts it to a direction raster (output) through the following process:

1. At each point or "cell" within the elevation raster, find the adjacent cell (of 8) with the steepest descent from the original cell (the lowest neighbor).
2. Assign the original cell a new value from 1-255 based on the direction to the lowest neighbor, with 1 being east, 2 being southeast, and going counter-clockwise around doubling each time until we get 128 for northeast.

This new direction raster tells us how water flows at each point. Using the following code, we programmed a third raster that indicates, at each cell, how many other cells contribute flow into the cell:

Finally, we achieved this result for AOI #3:

We can see that water will pool in the streets, which makes sense due to their lower elevation.

For a more detailed explanation, check out ArcGIS's D8 flow accumulation tool: https://pro.arcgis.com/en/pro-app/latest/tool-reference/raster-analysis/flow-direction.htm

Also, here is our GitHub for the full implementation: https://github.com/dsk2025/SEES-2024-Flooding-Model

​​​​​​​About the author, Dae San is a rising senior from the Cleveland, Ohio area. This virtual internship is part of a collaboration between the Institute for Global Environmental Strategies (IGES) and the NASA Texas Space Grant Consortium (TSGC) to extend the TSGC Summer Enhancement in Earth Science (SEES) internship for U.S. high school (http://www.tsgc.utexas.edu/sees-internship/). This guest blog shares the NASA SEES Earth System Explorers virtual internship in 2024.