Terry Zien from USACE St. Paul District and James Fallon from USGS Minnesota Water Science Center
Local, state, and federal managers tasked with forecasting flood peaks, predicting the extent of flood inundation, mitigating the risk associated with flooding or levee failure, or responding during flood emergencies require detailed knowledge about levee locations and characteristics. Although some levees are accredited in FEMA’s Flood Insurance Rate Maps and supporting studies and/or included in the USACE National Levee Database, many undocumented, unaccredited, and often unmaintained levees exist, which complicates flood forecasting, risk management, and emergency response.
The Minnesota Silver Jackets team supported a USACE interagency study that assessed two methods of using remote sensing with high-resolution LIDAR topographic data to identify undocumented levees. The methods drew on the topographic characteristics of accredited and any known unaccredited levees to develop search criteria and test methodologies for identifying existing, intentional levee structures near rivers as well as other levee-like structures that may or may not be acting as water barriers. U.S. Geological Survey (USGS) and USACE were the lead technical agencies with LIDAR data provided by the Minnesota Department of Natural Resources and local assessment completed by the cities of Delano and Springfield, MN.
The first method was only applied in Delano. The USACE used Hillshades from ArcMap, a visual GIS-based tool with a digital elevation model that was derived from LIDAR, to visually identify potential levees and then used detailed site visits to assess the validity of the identifications. For the second method, the USGS applied a mathematical wavelet transform to a LIDAR-derived digital elevation model to identify potential levees in both Delano and Springfield. The wavelet method doesn't simply identify elevation breaks; it analyzes the elevation data to find levee-like structures with cross-sectional geometry that is levee-like, making that determination based on user input parameters. The results were also field verified.
Both methods were successful in identifying levees; however, they also identified other features that required interpretation to differentiate from levees, such as constructed barriers, high banks, and bluffs. For future applications, it is recommended that the two methods be used together to eliminate ambiguities in levee identification. A suggested method for future pilot applications might involve a conjunctive method that goes through a three-step process: (1) use of the wavelet-transform method to rapidly identify slope-break features in high-resolution topographic data, (2) further examination of topographic data using Hillshades and aerial photographs to classify features and map potential levees, and (3) a verification check of each identified potential levee with local officials and field visits.
Both pilot communities are known to have levee-like structures, which have since been identified in the pilot survey but are not reflected in either Flood Insurance Rate Maps or the National Levee Database (NLD), and each community relies on those structures for flood risk reduction. Temporary levees were constructed in both communities during flooding in 1969 and have since been modified or raised to continue to reduce flood risk for residents and infrastructure. During the March 2011 flooding, temporary measures were taken to raise levees or construct levees, but the level of flood risk reduction provided by those structures is unknown. In addition to identifying the levee-like structures, some parametric data such as levee prism dimensions, top of structure elevations, toe elevations, and top width are obtained in the analysis and can be output in tabular format. This could be useful in building a database of the structure data, but accuracy tolerances must be investigated.
The published results of this pilot project are available for federal, state, and local communities so that they may apply these methodologies and identify potentially undocumented levees in other areas. Knowing the existence and location of levees especially in developed areas will greatly assist risk communications and emergency responders. Developing a tool or method such as this will move the effort forward.