Being able to accurately estimate extents of different magnitude floods is a critical application in water resources. This information is needed to assess risk for insurance, emergency management, and planning. Lidar is quickly becoming the predominant source of topographic data for floodplain delineation. This is because it's both accurate and cost-effective.
Flood extents are typically estimated by comparing models of water surfaces and ground surfaces. Water surface profiles for a given flood event (for example, 50-year flood) are created by a hydraulic engineer or hydrologist using tools like HEC-GeoRAS. Each profile represents the height of water across the river at a given location. The length of each profile is long enough to capture the largest possible flood extent going out from either side of the river. Profiles are generated at reasonable intervals along the river where the flooding is being modeled.
- Each water profile might simply be assigned one z-value: the height of the water at the center of the river at that location. These profiles can be used to create a water surface TIN. Create a TIN from the water profile lines using the Create TIN geoprocessing tool. Add the water profiles to the TIN as soft breaklines.
- Run the Surface Difference geoprocessing tool using the water surface TIN and a bare earth terrain made from lidar points as inputs. See Creating raster DEMs and DSMs from large lidar point collections to see how to make a bare earth terrain dataset.
Surface difference results
The primary output from the Surface Difference tool is a polygon feature class. Each polygon is classified as either ABOVE, BELOW, or EQUAL so you can tell where the modeled water surface is above the terrain dataset. These areas are potentially flooded.
The actual flooded areas might not be equivalent to all polygons classified as ABOVE. This is because some of these areas might not actually be reachable by the river and its floodwaters because of intervening hills. To identify the ABOVE polygons that are connected to the river, you can use a spatial selection—select those polygons that are intersected by a line representing the river.
The Surface Difference tool provides an option to output a difference raster. Positive cell values in this dataset represent depth, which is another important piece of information in flood studies. More accurate damage estimates can be made if the water depth is known.
