Despite human-induced changes in floodplains over the past century, comprehensive data of long-term land use change within floodplains of large river basins are limited. Data of long-term and large-scale floodplain land use are required to effectively quantify floodplain functions and development trajectories. They also provide a holistic perspective on the future of floodplain management and restoration – and concomitantly flood-risk mitigation. Here, we present the first available dataset that provides spatially explicit estimates of land use change along the floodplains of the Mississippi River Basin (MRB) covering 60 years (1941-2000) at a 250-m resolution. We derived this MRB floodplain land use change dataset from two input data sources: (i) the high-resolution global floodplain extent dataset GFPLAIN250m, and (ii) the annual FOREcasting SCEnarios of Land-use Change (FORE-SCE) dataset for the continental United States. Our results suggest that MRB floodplains have transitioned irreversibly from natural ecosystems to predominantly agricultural land use (e.g., more than 10,000 km2 of wetlands have been lost due to agricultural expansion). Developed land use within the floodplain has also steadily increased. The dataset is publicly available through HydroShare: https://gishub.org/mrb-data as well as an interactive online map interface: https://gishub.org/mrb-floodplain. These products will support MRB resilience and sustainability goals by advancing data-driven decision making on floodplain restoration, buyout, and conservation scenarios.

The increasing availability of surface water inundation data has encouraged modelers and managers to include small yet abundant surface water storage systems (e.g., wetlands and other landscape depressions) in process-based models. Yet, these model applications have been largely limited to small- to meso- watershed scales, with drainage areas ranging from a few hectares to several thousand square kilometers. The conventional practice of overlooking these surface water storage systems in basin-scale (e.g., >10,000 m2) hydrologic modeling may be missing the total picture of flood and drought hazards. To fill this gap, we developed a 30-m resolution topography-based wetland and depression storage (maximum surface area and storage volume) database for the Upper Mississippi, Ohio, and Missouri River Basins ⎼ encompassing the 2.35 million km2 upstream domain of the Mississippi River system. Further, we integrated this depression dataset into a process-based model to simulate sub-catchment and river reach-scale hydrologic fluxes (surface runoff, soil wetness, evapotranspiration) and flows (streamflow). Compared with a “no depression” conventional model constructed for the Missouri and Upper Mississippi River Basins, our exploratory analyses demonstrate that a depression-integrated model (i) significantly alters the spatial patterns and magnitudes of water yields, (ii) improves streamflow simulation accuracy, and (iii) provides realistic spatial distributions of landscape wetness conditions. These emerging findings provide us with new insights into the effects of small surface water storage and stimulates a reassessment of current practices for basin-scale hydrologic modeling and water management.