Evaluation of a GIS-based flood hazard assessment in Rochester, Minnesota

Michael Talbot, Camilla Correll, Sarah Voje and Paul Nation

ABSTRACT

As part of the Comprehensive Surface Water Management Plan (CSWMP) for the City of Rochester, MN, EOR conducted a flood risk assessment to assist in climate change adaptation planning related to projected increases in flood severity and frequency across the Midwestern United States. One key component of this flood risk framework is flood hazard, which is typically estimated using hydrologic and hydraulic (H/H) models or, in the United States, from available Flood Hazard Layers (FHL) submitted to FEMA. Two issues were encountered here: first, the City did not have H/H models built across the planning area, and while a full build-out of their models is planned, the funding and construction of this effort will take place over several years; and second, the available FHL were not complete within the planning area and were often only mapped for the floodplains of major rivers. 

To overcome these issues and provide flood hazard estimates for the planning area to use over the short term, EOR used a GIS-based flood risk framework to estimate flood hazard using terrain analysis techniques and high-resolution topographic data. This process resulted in a continuous raster layer representing relative flood hazard within the planning area, which was then reclassified using high water levels for simulated flood events using a calibrated SWMM model of one subwatershed within the planning area. This reclassified layer was validated against model results at other locations within the planning area to assess the potential robustness of this approach for filling knowledge gaps related to flood hazard where model results are unavailable.

This presentation will discuss the approach used, the results of the comparison, and the potential range of applications for such a framework. We will also discuss how the flood hazard layer fits within the overall flood risk framework, which includes additional GIS workflows for generating estimates of economic and social vulnerability.

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