The natural flood pulse maintains river-floodplain ecosystems through the exchange of freshwater resources between the main-stem and floodplain habitats. Few prior studies have quantified the relationship between flows and floodplain response including estimating inundation area, floodwater volumes, and slough connectivity. Floodplain modeling typically uses the flow-stage height relationship at river gauge stations. In this study, we compared a relative elevation model (REM) and the Hydrologic Engineering Center River Analysis System (HEC-RAS 1D) model using events from 2015 and 2016 covering a range of flows from the 1st to the 99th percentile for the Apalachicola River, Florida. Because digital elevation models (DEM) from LiDAR (light detection and ranging) data lack details of riverbed topography, we compared a LiDAR-alone and LiDAR-sonar combined DEM to assess their differences. Estimates from the REM and HEC-RAS models were compared to maps based on Landsat imagery-derived water and vegetation indices. In this river, we found a non-linear relationship between the inundated area and flow, increasing markedly through the 90th flow percentile after which increases are minimal. Inundated areas from both REM and HEC-RAS models were similar for all selected flow levels except at the 74th percentile (708 m3/s) flow at which the REM produced 11% higher inundated area than HEC-RAS. Near the median flows, major sloughs were fully connected with backswamps and low-lying patches being inundated. At the higher flows, only a few anthropogenic features were exposed. Floodplain inundation estimates from Landsat performed poorly, detecting 9% with the modified normalized difference water index (mNDWI) and 41% with the open water likelihood index (OWL). These estimates were much lower than the HEC-RAS model (96% flooded), largely because the satellite is unable to penetrate dense forests and examine the floodplain surface, and the Landsat pixel size is twice the width of floodplain sloughs. The LiDAR-sonar combined DEM produced a higher floodwater volume estimate with the HEC-RAS model than using LiDAR-alone. The difference of 1,368,000 m3 at the 1st percentile (142 m3/s) and 2,825,000 m3 at the 89th percentile (1133 m3/s) demonstrate the limitation of using a LiDAR-alone DEM, which cannot penetrate the water surface, and the importance of surveying floodplains using sonar. Modeling results under predict historical wetting of the floodplain because Corps dredging made the main channel approximately 13% wider from its historical width in 1941. Further, in the past few decades, droughts and low flows have become more common because of varied upstream water uses, resulting in less inundation than in the past. Frequent high flows are required to maintain river-floodplain connectivity, floodplain forests, and other hydroecological functions in the Apalachicola River floodplain. Our findings present a basis to assess the legacy of past and ongoing disturbances, inform potential policy decisions for water and floodplain management, and provide a baseline for further research.