Recent extreme floods on the Mississippi and Missouri Rivers have motivated expansion of floodplain conservation lands. Within Missouri there are more than 85,000 acres of public conservation lands in large-river floodplains. Floodplain lands are highly dynamic and challenging to manage, particularly as future climatic conditions may be highly variable. These lands have the potential to provide valuable ecosystem services like provision of habitat, nutrient processing, carbon sequestration, and flood-water storage that produce economic values in terms of recreational spending, improved water quality, and decreased flood hazards. However, floodplain managers may need tools to help them understand nonstationary conditions on conservation lands. This project worked with floodplain managers to identify the information most needed to understand nonstationary conditions, and to develop tools they can apply to conservation lands to improve decision making. Our survey revealed that time, funding, and a perceived disconnect between research and management limited the ability of managers to use new information. However, managers were willing to partner with scientists to identify science needs, relevant spatiotemporal scales, and products useful for management decisions. Floodplain managers agreed that metrics of inundation, including depth, extent, frequency, duration, and seasonality are the most useful metrics for management of floodplain conservation lands. We developed an approach to derive digital spatial layers of these metrics of inundation from numeric flood inundation models under baseline and climate change scenarios. We applied this method to the lower 500 miles of the Missouri River, making 45 spatial layers available to aid in current and future management decisions of conservation properties. Patterns of floodplain inundation vary longitudinally, with channel incision acting as the dominant control. Annually, climate change is estimated to increase the duration, frequency, depth, and extent of floodplain inundation. However, these patterns vary seasonally, with inundation increasing in the spring and decreasing in the fall.