Molly Van Appledorn

The hydrologic regime of the upper Mississippi River (UMR) has become wetter, with greater discharges, longer‐lasting high‐flow conditions, and seasonal shifts in these patterns over the past several decades. How these changes are expressed spatially as floodplain inundation area, frequency, depth, duration, and timing is not well understood. It is also unclear to what degree spatial patterns of submergence are represented by examining discharge data alone. We assessed changes in floodplain inundation characteristics from 1940 to 2022 in navigation pools 3–10 of the UMR using a geospatial model to simulate daily inundation depths. Inundation characteristics shifted significantly across pools, but the direction and magnitude of change varied by pool and metric. Characteristics summarized at the pool scale correlated with streamgage‐derived proxies but the strength of the relationship varied. Within pools, variability in inundation trends highlighted the importance of spatially explicit modeling. Our study demonstrates that changes in discharge over 83 years have manifested across the UMR floodplain in ways that may have consequences for ecological patterns and processes. By mapping hydrologically sensitive areas, we can anticipate which areas may be susceptible to additional shifts in river discharge in a climatically uncertain future.

In anticipation for increased funding made possible by the Water Resources Development Act of 2020, the Upper Mississippi River Restoration (UMRR) Program identified a need to conduct river-wide assessments of floodplain vegetation. In January 2025, we assembled a group of subject matter experts to perform the following tasks:Review Upper Mississippi River Restoration’s current floodplain vegetation research portfolio,Identify important features and goals for long-term floodplain vegetation monitoring,Evaluate the suitability of existing datasets for system-wide vegetation assessments, andDiscuss emerging opportunities to learn about floodplain vegetation dynamics from local-scale restoration and management projects.This document is a summarization of what occurred at the meeting and provides suggested next steps toward developing the capacity to conduct routine long-term monitoring and assessment of floodplain vegetation as part of the Upper Mississippi River Restoration Program.

Effects of large‐scale flooding on forest composition and structure are a function of flood duration, depth, timing, and frequency. Throughout the Upper Mississippi River System (UMRS), floods in 1993 and 2019 were record‐setting events followed by high rates of tree mortality. These events generated interest in species adaptations to flood event characteristics and how forest communities have changed in response to large‐scale floods. We investigated associated tree mortality, how the floods differed spatially, and how floodplain forest communities have changed since 1993. Eight UMRS reaches were surveyed in a 1995 study, documenting vegetation species composition, size, and abundance. In 2021, a selection of plots (63%) were revisited and surveyed to quantify 2019 flood effects. For each site, we extracted daily inundation data for flood years and preceding decades from a surface water inundation model. We found post‐flood mortality varied spatially and generally reflected inundation duration patterns. Lower latitude reaches experienced longer inundation durations and greater tree mortality in 1993 than in 2019, while higher latitude reaches experienced similar inundation duration and depth and similar mortality between events. Decadal inundation attributes also differed. During 2009–2018, inundation duration was greater and events occurred later than during 1983–1992 in all reaches. Most forest trajectories were Acer saccharinum ‐dominated and changed relatively little in species composition and structure. The greatest change in composition occurred at plots with high mortality from the 1993 flood, particularly in more flood‐prone locations or where there were many small‐diameter individuals. In plots dominated by either Quercus spp. or Populus deltoides , species importance shifted toward more shade and flood‐tolerant species after 1995 surveys. Self‐replacement of these species may be limited by a change in regeneration conditions resulting from an ongoing inundation regime shift in the case of Quercus spp., or succession to more shade‐tolerant species in the case of Populus communities. Overall, effects on floodplain forests from the two flood events were heterogeneous. In some cases, forest change was likely just as influenced by shifts in flood regime as it was from singular flood events.

Context: Floodplain forests are being transformed by multiple pressures, prompting widespread management and restoration efforts. It is uncertain how disturbances, including hydrologic change, and management actions will interact to influence the ecology of these threatened forests. Objectives: This study examined the effects of alternative management and hydrologic regimes on forest succession at an Upper Mississippi River floodplain site with a restoration project in planning. Methods: We used the spatially explicit forest landscape model, LANDIS-II, to simulate forest succession for 100 years under four hydrogeomorphic management scenarios, three forest management scenarios, and two scenarios of future hydrologic conditions. We evaluated changes in forest biomass and composition over time and assessed the relative importance of management actions and hydrologic change on succession. Results: Forest aboveground biomass decreased in all management-hydrology scenarios, especially in the wetter hydrological scenario. Intensified hydrogeomorphic and forest management scenarios reduced the magnitude and extent of biomass declines; however, they were unable to prevent overall declines in biomass or cause large shifts in tree species composition. Silver maple ( Acer saccharinum ) was projected to decrease in biomass, while increases in biomass were projected for several late-successional species including swamp white oak ( Quercus bicolor ). Among the factors influencing variation in biomass, forest management had the largest influence in the first 50 years of our simulations, but hydrological regime became the most important factor by the end of the century. Conclusions: Our simulations indicate that management actions could play an important role in the conservation of floodplain forests, but their effectiveness will likely be limited if recent upward trends in flooding conditions in this system continue in the future. Thus, our results highlight both the potential benefits and limitations of management actions in the face of hydrologic change.

The hydrology of the Upper Mississippi and Illinois Rivers is a fundamental driver of ecosystem patterns and processes across a large portion of the United States. Quantitative hydrologic data for the main stems of these rivers underlie numerous scientific investigations, statistical models, and decision-making processes for local, State, and Federal agencies involved in the Upper Mississippi River Restoration program. Although historical hydrologic data exist, data representing potential future conditions of the Upper Mississippi and Illinois Rivers lack the resolution necessary to anticipate biotic and abiotic responses to altered hydrology and to determine resilient management actions. A source of future hydrologic scenarios is the readily available LOCA–VIC–mizuRoute hydrologic data products (named for the chain of models the data are produced from—localized constructed analogs, Variable Infiltration Capacity macroscale hydrological model, and the mizuRoute hydrologic routing model—that we shorten further to LVM in this report) that include simulated discharges for historic and future timeframes. The objective of this study is to assess the reliability of the hydrologic data products for their use in Upper Mississippi River Restoration program applications. Key study questions are (1) do the hydrologic data products reproduce characteristics of hydrology necessary to support ecological modeling and restoration decision-making applications within the Upper Mississippi River Restoration program? and (2) are there geographic differences in the reliability of the hydrologic data products?Seven characteristics of river hydrology were selected related to flow magnitude, seasonality, and regime for evaluation. The seven characteristics were calculated using observed and historical simulated hydrologic data at 19 U.S. Geological Survey streamgages throughout the basins of the Upper Mississippi and Illinois Rivers; two streamgages are located on the main stem of the Mississippi River and two streamgages are located on the main stem of the Illinois River. Statistical comparisons between observed and historical simulated characteristics indicated that the hydrologic data products did not reliably represent historical hydrologic conditions in the basin or main stem. The hydrologic data products we evaluated could not reliably capture the overall hydrologic regime or flow magnitudes; the latter is evidenced by substantial underestimates of discharge at most streamgages. Seasonal hydrologic characteristics were captured more reliably than flow magnitude, but overall correspondence was low for most streamgages. A weak latitudinal pattern in seasonal characteristics indicated the hydrologic data products poorly represent streamflow timing in snow-affected regions of the basin. Discrepancies in magnitude, seasonality, and regime indicate the potential for multiple sources of error. Because poor correspondence was present across all 19 streamgages, it was not possible to identify specific drivers of poor performance (that is, drainage area or geography). The modeling chain should be evaluated for biases associated with meteorologic forcing data, as well as hydrologic model formulation and calibration.We conclude that the hydrologic data products we evaluated appear unsuitable for applications tied to habitat and ecosystem restoration and management in the Upper Mississippi and Illinois Rivers. Plans to develop a future hydrology dataset for the Upper Mississippi River Restoration program would benefit from ongoing work to improve global climate model output downscaling methods, to improve hydrologic models, to make use of innovations in machine-learning approaches for projecting hydrology, and other efforts. The framework developed herein to evaluate hydrometeorological outputs generated using global climate models for a specific water resources application is a transferrable approach that could be applied to other data products and river systems.

The Upper Mississippi River Restoration (UMRR) program, a broad partnership of State and Federal agencies administered by the U.S. Army Corps of Engineers, integrates ecosystem monitoring, research, and modeling to rehabilitate habitat and evaluate ecosystem trends over time in the Upper Mississippi River System. Hydrologic data are integral to the UMRR program because they are used in scientific research, decision-making, and restoration project planning. However, a lack of quantitative hydrologic data representing potential future conditions limits the ability to complete informative research on how future conditions may affect river ecology, achieve management goals, and design restoration projects for 50-year horizons.The U.S. Geological Survey and the U.S. Army Corps of Engineers led a series of workshops with UMRR partners to (1) prioritize needs for understanding future hydrology, (2) discuss appropriate datasets that could address these needs, and (3) develop a plan for acquiring and distributing a hydrologic dataset of potential future conditions. Agency priorities for understanding future hydrology were broad, spanning ecologic, geomorphic, resource management, and engineering disciplines, and were identified for a range of spatial (project site, navigation pool, reach, system) and temporal (daily, seasonal, annual) scales. The LOcalized Constructed Analogs-Variable Infiltration Capacity-mizuRoute hydrologic data products were identified as a potential source of off-the-shelf data to meet UMRR priority needs but warranted a robust quantitative evaluation. The final meeting in the series scoped a proposal to evaluate the LOcalized Constructed Analogs-Variable Infiltration Capacity-mizuRoute hydrologic data products for use in UMRR applications, including contingencies if the data were determined to be unreliable.

Reed canarygrass (Phalaris arundinacea L.) is one of the most common invaders of floodplains and wetlands in North America. In the Upper Mississippi River floodplain, invasion by reed canarygrass in forest understories can inhibit forest regeneration when gaps form in the overstory. Understanding the distribution of reed canarygrass in forest understories is essential for effective management and control. We used an ensemble of species distribution models including Bayesian additive regression trees, boosted trees, and random forest algorithms to predict habitat suitability for reed canarygrass in forest understories across the Upper Mississippi River floodplain (~41,000 ha). Data from forest inventory study plots with reed canarygrass presence and absence were combined with 10 hypothesized environmental predictors of reed canarygrass invasion. We applied three approaches to better understand and incorporate the influence of spatial autocorrelation among our predictor variables, including random cross‐validation, spatial cross‐validation, and spatial cross‐validation with Euclidean distance fields. Flood frequency, distance to contiguous floodplain, distance to forest edge, and distance to invaded wet meadow were among the most important environmental predictors across the three algorithms. Generally, the mean probability of reed canarygrass presence decreased with increasing flood depth, distance to contiguous floodplain, distance to invaded wet meadow, forest cover, and forest height, while relationships with other predictors were more variable. The ensemble of the three models (i.e., the average prediction) was used to map and summarize potential reed canary grass habitat suitability across the landscape. The maps generated quantified the habitat suitability for reed canarygrass and areas of agreement among the models in forest understories across the floodplain. This information can be used to better understand the extent of invasion, prioritize restoration efforts, and develop further research.

Large wood (LW) plays important geomorphic and ecological roles in rivers and is widely used as a restoration tool. Changes to floodplain land use and historical removal have altered wood dynamics in fluvial systems globally. We know little about the distribution and dynamics of LW in great rivers (approximately >10⁵ km²) like the Upper Mississippi and Illinois Rivers despite its ecosystem importance and use in restoration projects. We assessed LW occurrence data collected by the fisheries component of the Upper Mississippi River Restoration Program's Long Term Resource Monitoring element. We analysed 25 years of data collected across six reaches of the Upper Mississippi and Illinois Rivers that represented contrasting physiographic settings, and across four aquatic area types comprising gradients of hydrology, connectivity and geomorphology. We tested hypotheses on drivers of LW occurrence using generalised linear mixed effects models, where occurrence was predicted by reach‐ and local‐scale environmental variables. Occurrence varied significantly across reaches and aquatic area types. In general, wood occurred more frequently upriver and in side channels compared to other aquatic areas. Large wood was most strongly predicted systemically by reach identity but not local‐scale variables, underscoring the importance of broad‐scale physiographic gradients in defining hydrogeomorphic processes. Floodplain forests and shoreline revetment were consistently important predictors across reaches. Our findings show that the spatial variability of LW occurrence reflects the physical variability of the Upper Mississippi and Illinois Rivers. They also reveal the value in using geomorphic classifications as frameworks for understanding physical processes like LW dynamics because of their ability to contextualise site‐scale conditions. The baseline understanding of LW abundance across different hydrogeomorphic gradients and scales presented here can give insight into how to more effectively target restoration efforts in great rivers and contribute to a broader understanding of LW dynamics where such studies have been lacking.