Assessing resolution and source effects of digital elevation models on automated floodplain delineation: A case study from the Camp Creek Watershed, Missouri Richard Charrier a, b , Yingkui Li c, * a Department of Geography, University of Missouri, Columbia, MO 65211, USA b Center for Applied Research and Environmental Systems, University of Missouri, Columbia, MO 65211, USA c Department of Geography, University of Tennessee, Knoxville, TN 37996, USA Keywords: Digital elevation model (DEM) GIS Automated floodplain delineation Resolution and data source effects Camp Creek Watershed abstract Digital elevation models (DEMs) have been widely used in automated floodplain modeling to determine floodplain boundaries. However, the effects of DEM resolution and data source on floodplain delineation are not well quantified. This paper presents a case study to assess these effects from the Camp Creek Watershed, Missouri, using two sets of DEMs. One is the Light Detection and Ranging (LiDAR) DEMs re- sampled from 1-m to 3, 5, 10, 15, and 30-m resolutions. The other is 5, 10, and 30-m DEMs obtained from the U.S. Geological Survey (USGS). Floodplain boundaries are delineated using a combination of hydro- logical, hydraulic and floodplain delineation models under the Federal Emergency Management Agency’s (FEMA) guideline. Model outputs including stream network, watershed and floodplain boundaries are compared to 1-m LiDAR DEM outputs (as the reference) to assess the uncertainty. Results indicate that re-sampled 3 or 5-m LiDAR DEMs produce similar streams and floodplain boundaries within 10% difference of the reference. In contrast, coarser LiDAR DEMs (such as the 10-m resolution) are more appropriate for watershed boundary delineation because higher DEM resolutions are likely more sensitive to minor topographic changes and may introduce erroneous boundaries. For different data sources, uncertainties introduced by USGS DEMs are much higher than LiDAR DEMs with a distinct relationship between uncertainties and DEM resolutions. Uncertainties of LiDAR DEMs consistently increase with decreasing resolutions, whereas similar levels of uncertainty are observed for different USGS DEM resolutions. This difference is probably due to the inherited difference in their original data source resolutions to make these two types of DEMs. Ó 2011 Elsevier Ltd. All rights reserved. Introduction Water is essential to life on Earth, but it can also cause disasters. Water-related disasters, such as flooding, hurricanes, cyclones, tsunamis, mudslides, and blizzards, account for approximately 60% of all disasters worldwide (Frech, 2006; Ibarra, 2011; Vinet, 2008). Flooding itself is the largest natural disaster (about 40% of all disasters) in the United States with an estimated property damage of about $4 billion and approximate 200 deaths each year (Pielke, Downton, & Miller, 2002). Therefore, understanding the extent of flooding is critical to prevent property damage and life loss. Since the 1970s, the Federal Emergency Management Agency (FEMA) of the United States has conducted considerable effort to map nationwide floodplain areas, especially for the 100 year flooding event (Blanchard-Boehm, Berry, & Showalter, 2001). Early methods to delineate floodplain boundaries are primarily manual and require considerable amount of time and effort (Norman, Nelson, & Zundel, 2001). With the development of numerical modeling, geographic information systems (GIS), and digital elevation models (DEMs), automated techniques and methods become available and have been widely used in floodplain delineation. The automated method significantly reduces the time and improves the accuracy of the floodplain delineation. However, uncertainties still exist. First, automated floodplain modeling usually includes a combination of hydrological, hydraulic, and floodplain delineation models (FEMA, 2005) and each model can have different choices with strengths and weaknesses (Norman et al., 2001). Therefore, uncertainties can be introduced due to different combinations of models and/or parameters (Wheater, 2002; Yang, Townsend, & Daneshfar, 2006). Second, automated floodplain modeling requires a DEM to represent topography, calculate flood elevation, and delineate floodplain boundaries. The * Corresponding author. Tel.: þ1 865 974 0595; fax: þ1 865 974 6025. E-mail address: yli32@utk.edu (Y. Li). Contents lists available at SciVerse ScienceDirect Applied Geography journal homepage: www.elsevier.com/locate/apgeog 0143-6228/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.apgeog.2011.10.012 Applied Geography 34 (2012) 38e46