Floodplain inundation is believed to be the dominant physical driver of an array of ecosystem patterns and processes in the Upper Mississippi River System (UMRS), which comprises the Upper Mississippi and Illinois Rivers. Here, we present a series of related data products supporting floodplain inundation modeling of the UMRS. First, raster files comprise a unique identifier, river mile positioning, and relative elevation for each pixel. Second, csv files comprise time series data of simulated water surface depth for every pixel in the modeling domain. The time series data are for the months of April through September of years since 1940. These months were chosen because it approximates the period during which most biophysical processes such as vegetation metabolism and biogeochemical cycling are likely to be strongest across the longitudinal gradient of the UMRS. We excluded areas permanently wetted (aquatic areas), surfaces in agricultural production, roads, and developed areas. The start and end years of analysis are variable depending on location and are noted in the metadata of individual files. It is possible to map patterns of surface water inundation by joining the csvs of inundation depth to the rasters based on the unique pixel identifier. All data were derived from a geospatial model of surface water inundation developed for the UMRS and described in Van Appledorn et al. (2021; doi: 10.1002/rra.3628). The data also relate to the UMRS Floodplain Inundation Rasters (Van Appledorn et al., 2018; doi: https://doi.org/10.5066/F7VD6XRT). For example, the inundation depths here were analyzed over the time period of 1972 - 2011 to generate the UMRS Floodplain Inundation Rasters (Van Appledorn et al., 2018). The data are intended for use in geospatial analyses of UMRS floodplain ecosystem patterns and processes. Examples of suitable uses include stratifying regional sampling efforts or monitoring programs, providing context for interpreting fine-scale studies of local inundation patterns, or development of floodplain functional classes.