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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 901 records · Page 50Linked to original sources
USGS2021

Assessing the feasibility of managed aquifer recharge in California

With aquifers around the world stressed by over-extraction, water managers are increasingly turning to managed aquifer recharge (MAR), directly replenishing groundwater resources through injection wells, recharge basins, or other approaches. While there has been progress in understanding the geological and infrastructure-related considerations to make MAR more effective, critical evaluations of its institutional design and implementation are limited. This study assesses MAR projects, using a case study of projects proposed by groundwater sustainability agencies (GSAs) in California to comply with the state's Sustainable Groundwater Management Act of 2014; these projects will almost double the number of MAR projects in the United States. We draw on content analysis of groundwater sustainability plans that propose these projects. We first assess the types of recharge projects proposed and the stated aims of the projects, to assess when and why agencies are turning to MAR as a solution. We find that recharge basins are by far the most common approach, and that GSAs hope these basins will improve water table levels, reduce subsidence, and improve water quality. We then analyze potential barriers to project implementation and assess the projects' ability to achieve the stated goals. Primary concerns identified include a potential lack of available water, a potentially challenging legal framework, and minimal consideration of funding and cumulative land needs. To conclude, we discuss broader considerations for ensuring that MAR is an effective water management tool.

California↗
USGS2021

Anomalous noble gas solubility in liquid cloud water: Possible implications for noble gas temperatures and cloud physics

The noble gas temperature climate proxy is an established tool that has previously been applied to determine the source of groundwater recharge, however, unanswered questions remain. In fractured media (e.g., volcanic islands) recharge can be so rapid that groundwater is significantly depleted in heavy noble gases, indicating that the water has retained noble gas concentrations from higher elevations. Previous studies of rain samples have confirmed a match to patterns seen in fractured-rock groundwater for heavy noble gases along with a significant helium excess. Snow has been shown to be a credible source for both the helium excess and the observed heavy noble gas pattern. Here, liquid cloud water samples were collected at two mountainous sites and analyzed for noble gas concentrations. A pattern like that of rainwater was found. However, an analysis of diffusive uptake of noble gases into cloud water demonstrates that droplets of 1 mm diameter and smaller should be in constant solubility equilibrium with the atmosphere. To explain this, we present a novel hypothesis that relies on the assumption that liquid water consists of two types of water molecule clusters bounded by hydrogen bonds: a low-density ice-like structure and a high-density condensed structure. In this model, the pressure gradient near the surface of a droplet resulting from surface tension could allow for the formation of a surface layer that is rich in ice-like low density clusters. This can explain both the helium excess and the heavy noble gas depletion seen in the samples.

Puerto Rico↗
USGS2021

Time-fractional flow equations (t-FFEs) to upscale transient groundwater flow characterized by temporally non-darcian flow due to medium heterogeneity

Upscaling groundwater flow is a fundamental challenge in hydrogeology. This study proposed time-fractional flow equations (t-FFEs) for upscaling long-term, transient groundwater flow and propagation of pressure heads in heterogeneous media. Monte Carlo simulations showed that, with increasing variance and correlation of the hydraulic conductivity ( K ), flow dynamics gradually deviated from Darcian flow and exhibit sub-diffusive, time-dependent evolution which can be separated into three major stages. At the early stage, the interconnected high- K zones dominated flow, while at intermediate times, the transverse flow due to mixed high- and low- K zones caused delayed rise of the piezometric head. At late times when flow in the relatively high- K domains reached stability, cells with very low- K continued to block the entry of water and generate “islands” with low piezometric head, significantly extending the temporal evolution of the piezometric head. The elongated water breakthrough curve cannot be quantified by the flow equation with an effective K , the space-fractional flow equation, or the multi-rate mass transfer (MRMT) flow model with a few rates, motivating the development of t-FFEs assuming temporally non-Darcian flow. Model applications showed that both the early and intermediate stages of flow dynamics can be captured by a single-index t-FFE (whose index is the exponent of the power-law probability density function of the random operational time for water parcels), but the overall evolution of flow dynamics, especially the enhanced retention of flow at later times, required a distributed-order t-FFE with variable indexes for different flow phases that can dominate flow dynamics at different stages. Therefore, transient groundwater flow in aquifers with spatially stationary heterogeneity can be temporally non-Darcian and non-stationary, due to the time-sensitive, combined effects of interconnected high- K channels and isolated low- K deposits on flow dynamics (which is the hydrogeological mechanism for the temporally non-Darcian flow and sub-diffusive pressure propagation), whose long-term behavior can be quantified by multi-index stochastic models.

Water Resources Research↗
USGS2021

Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning

Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.

Water Resources Research↗
USGS2021

Accounting for fine-scale forest structure is necessary to model snowpack mass and energy budgets in montane forests

Accurately modeling the effects of variable forest structure and change on snow distribution and persistence is critical to water resource management. The resolution of many snow models is too coarse to represent heterogeneous canopy structure in forests, and therefore, most models simplify forest effects on snowpack mass and energy budgets. To quantify the loss of snowpack prediction from simplifications of forest canopy-mediated processes, we applied a high-resolution energy balance snowpack model at two forested sites at a fine (1 m 2 ) and coarse (100 m 2 ) spatial resolution. Simulating open and forested areas separately, as is done in many land surface models (LSMs), leads to biases between the coarse and fine-scale simulations because there is no representation of areas that are near (e.g., <15 m from) trees but with no overhead canopy, which are common in forests of low to medium tree density. Consistent with previous LSM intercomparisons, the coarser simulations predict greater under-canopy radiation (by 30%–80% at our sites), faster snow ablation (by almost 2×), and earlier snow disappearance (by 1–22 days). Many of these biases are reduced dramatically or eliminated when canopy edge environments are considered in the coarser simulations. Furthermore, remaining disagreement between the 100-m and 1-m models can be partially explained by using a combination of tree height, canopy cover, and canopy edginess (which together can explain 46%–96% of remaining model biases). The lack of information about canopy edges and other fine-scale forest structure characteristics in many current LSMs may limit their reliability for simulating forest disturbance.

California, New Mexico↗
USGS2021

Concentration-discharge relationships of dissolved rhenium in Alpine catchments reveal its use as a tracer of oxidative weathering

Oxidative weathering of sedimentary rocks plays an important role in the global carbon cycle. Rhenium (Re) has been proposed as a tracer of rock organic carbon (OC petro ) oxidation. However, the sources of Re and its mobilization by hydrological processes remain poorly constrained. Here we examine dissolved Re as a function of water discharge, using samples collected from three alpine catchments that drain sedimentary rocks in Switzerland (Erlenbach, Vogelbach) and Colorado, USA (East River). The Swiss catchments reveal a higher Re flux in the catchment with higher erosion rates, but have similar [Re]/[Na + ] and [Re]/[SO 4 2- ] ratios, which indicate a dominance of Re from OC petro . Despite differences in rock type and hydro-climatic setting, the three catchments have a positive correlation between river water [Re]/[Na + ] and [Re]/[SO 4 2- ] and water discharge. We propose that this reflects preferential routing of Re from a near-surface, oxidative weathering zone. The observations support the use of Re as a proxy to trace rock-organic carbon oxidation, and suggest it may be a hydrological tracer of vadose zone processes. We apply the Re proxy, and estimate CO 2 release by OC petro oxidation of 5.7 +6.6 / -2.0 tC km -2 yr -1 for the Erlenbach. The overall weathering intensity was ∼40%, meaning that the corresponding export of un-weathered OC petro in river sediments is large, and the findings call for more measurements of OC petro oxidation in mountains and rivers as thet cross floodplains.

Water Resources Research↗
USGS2022

Reservoir attributes display cascading spatial patterns along river basins

Considering reservoirs as linear fragments in a basin's river network could improve understanding, predictability, and management efficiency. We looked for general cascading spatial patterns across five categories of reservoir attributes: land cover, morphology and hydrology, fish habitat, fish assemblages, and fisheries. Attributes were pulled from various databases for large reservoirs (>100 ha) located in the United States. 16 widely distributed river basins, each including a minimum of 15 large reservoirs, were selected for analysis. Using analysis of covariance with basin as the class variable, we tested each attribute as a linear function of catchment area, which is an index of reservoir position in the basin. The majority of reservoir attributes displayed log-linear patterns as catchment area increased, indicating that reservoirs act as members of a larger network just as river reaches do. Several patterns were detected including attributes with no apparent lengthwise arrangement along the basin; cascading spatial patterns in which attributes increase or decrease from upstream to downstream within a basin; and attributes that increase with catchment area in some basins, decrease in others, or may simply remain constant throughout the basin. We conclude that each pattern may have different implications for management, and that the effectiveness with which most management activities influence reservoirs is likely to increase or decrease along river basins.

Water Resources Research↗
USGS2022

Multi-task deep learning of daily streamflow and water temperature

Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeling two interdependent variables, daily average streamflow and daily average stream water temperature, together using multi-task DL. A multi-task scaling factor controlled the relative contribution of the auxiliary variable's error to the overall loss during training. Our experiments examined the improvement in prediction accuracy of the multi-task approach using paired streamflow and water temperature data from sites across the conterminous United States. Our results showed that for 56 out of 101 sites, the best performing multi-task models performed better overall than the single-task models in terms of Nash-Sutcliffe efficiency for predicting streamflow with single-site models. For 43 sites, the best multi-task, single-site models made no significant difference in predicting streamflow. The multi-task approach had a smaller effect when applied to a model trained with data from 101 sites together, significantly improving performance for only 17 sites. The multi-task scaling factor was consequential in determining to what extent the multi-task approach was beneficial. A naïve selection of this factor led to significantly worse-performing models for 3 of 101 sites when predicting streamflow as the primary variable, and 47 of 53 sites when predicting stream temperature as the primary variable. We conclude that a multi-task approach can make more accurate predictions by leveraging information from interdependent hydrologic variables, but only for some sites, variables, and model configurations.

Water Resources Research↗
USGS2022

Strength and memory of precipitation's control over streamflow across the conterminous United States

How precipitation (P) is translated into streamflow (Q) and over what timescales (i.e., “memory”) is difficult to predict without calibration of site-specific models or using geochemical approaches, posing barriers to prediction in ungauged basins or advancement of general theories. Here, we used a data-driven approach to identify regional patterns and exogenous controls on P–Q interactions. We applied an information flow analysis, which quantifies uncertainty reduction, to a daily time series of P and Q from 671 watersheds across the conterminous United States. We first demonstrated that information transfer from P to Q primarily reflects the quickflow component of water-budgets, based on a watershed model. Readily quantifiable information flows show a functional relationship with model parameters, suggesting utility for model calibration. Second, applied to real watersheds, P–Q information flows exhibit seasonally varying behavior within regions in a manner consistent with dominant runoff generation mechanisms. However, the timing and the magnitude of information flows also reflect considerable subregional heterogeneity, likely attributable to differences in watershed size, baseflow contributions, and variation in aerial coverage of preferential flow paths. A regression analysis showed that a combination of climate and watershed characteristics are predictive of P–Q information flows. Though information flows cannot, in most cases, uniquely determine dominant runoff mechanisms, they provide a means to quantify the heterogeneous outcomes of those mechanisms within regions, thereby serving as a benchmarking tool for models developed at the regional scale. Last, information flows characterize regionally specific ways in which catchment connectivity changes from the wet to dry season.

conterminous United States↗
USGS2021

Long-term Mississippi River trends expose shifts in the river load response to watershed nutrient balances between 1975 and 2017

Excess nutrients transported by the Mississippi River (MR) contribute to hypoxia in the Gulf of Mexico. Nutrient balances are key drivers to river nutrient loads and represent inputs (fertilizer, manure, deposition, wastewater, N-fixation, and weathering) minus outputs (nutrient uptake and removal in harvest, and N emissions). Here, we quantified annual changes in nitrogen (N) and phosphorus (P) river loads and nutrient balances at the MR Outlet and documented that the river load response to watershed nutrient balances shifted between 1975 and 2017. Annual nutrient balances and river loads were positively correlated between 1975 and 1985, but after, a disconnect between both the N and P balances and river loads emerged, and the subsequent river load patterns were different for N versus P. We evaluated the relative impacts of legacy nutrients and other latent factors, for which data were not available, on river nutrient load trends. Our analysis showed that in the case of N, latent factors were potentially just as important in explaining changes in river nutrient loads over time as N balances, and in the case of P, they were even more important. We hypothesized that these factors included implementation of best management practices, changes in watershed buffering capacity, the effects of tile drainage, or increased precipitation. Our analytical approach shows promise for the investigation of drivers of water quality trends that are not well-represented in typical national scale geospatial datasets.

Mississippi River↗
USGS2021

Post-drought groundwater storage recovery in California’s Central Valley

Groundwater depletion is a major threat to agricultural and municipal water supply in California's Central Valley. Recent droughts during 2007–2009 and 2012–2016 exacerbated chronic groundwater depletion. However, it is unclear how much groundwater storage recovered from drought-related overdrafts during post-drought years, and how climatic conditions and water management affected recovery times. We estimated groundwater storage change in the Central Valley for April 2002 through September 2019 using four methods: GRACE satellite data, a water balance approach, a hydrologic simulation model, and monitoring wells. We also evaluated the sensitivity of drought recovery to different climate scenarios (recent climate ± droughts and future climate change scenarios: 20 GCMs and 2 RCPs) using water balance method and statistical sampling of historical climate data. Estimated Central Valley groundwater loss during the two droughts ranged from 19 km 3 (2007–2009) to 28 km 3 (2012–2016) (median of four methods). Median aquifer storage recovery was 34% and 19% of the overdraft during the 2010–2011 and 2017–2019 post-drought years, respectively. Numerical experiments show that recovery times are sensitive to climate forcing, with longer recovery times for a future climate scenario that replicate historical climatology relative to historical forcing with no droughts. Overdraft recovery times decrease by ∼2× with implementation of pumping restrictions (30th to 50th percentiles of historical groundwater depletion) to constrain groundwater depletion relative to no restrictions with a no-drought future climatology. This study highlights the importance of considering water management implications for future drought recoveries within the context of climate change scenarios.

California↗
USGS2022

How does precipitation variability control bedload response across a mountainous channel network in a maritime climate?

Modeled stream discharge is often used to drive sediment transport models across channel networks. Because sediment transport varies non-linearly with flow rates, discharge modeled from daily total precipitation distributed evenly over 24-hrs may significantly underestimate actual bedload transport capacity. In this study, we assume bedload transport capacity determined from a hydrograph resulting from the use of hourly (1-h) precipitation is a close approximation of actual transport capacity and quantify the error introduced into a network-scale bedload transport model driven by daily precipitation at channel network locations varying from lowland pool-riffle channels to upland colluvial channels in a watershed where snow accumulation and melt can affect runoff processes. Transport capacity is determined using effective stresses and the Wilcock and Crowe (2003) equations and expressed in terms of transport capacity normalized by the bankfull value. We find that, depending on channel network location, cumulative error can range from 10 - 20% to more than two orders of magnitude. Surprisingly, variation in flow rates due to differences in hillslope and channel runoff do not seem to dictate the network locations where the largest errors in predicted bedload transport capacity occur. Rather, spatial variability of the magnitude of the effective-bankfull-excess shear stress and changes in runoff due to snow accumulation and melt exert the greatest influence. These findings have implications for flood-hazard and aquatic habitat models that rely on modeled sediment transport driven by coarse-temporal-resolution climate data.

Washington↗
USGS2022

Application of recursive estimation to heat tracing for groundwater/surface-water exchange

We present and demonstrate a recursive-estimation framework to infer groundwater/surface-water exchange based on temperature time series collected at different vertical depths below the sediment/water interface. We formulate the heat-transport problem as a state-space model (SSM), in which the spatial derivatives in the convection/conduction equation are approximated using finite differences. The SSM is calibrated to estimate time-varying specific discharge using the Extended Kalman Filter (EKF) and Extended Rauch-Tung-Striebel Smoother (ERTSS). Whereas the EKF is suited to real-time (“online”) applications and uses only the past and current measurements for estimation (filtering), the ERTSS is intended for near-real time or batch-processing (“offline”) applications and uses a window of data for batch estimation (smoothing). The two algorithms are demonstrated with synthetic and field-experimental data and are shown to be efficient and rapid for the estimation of time-varying flux over seasonal periods; further, the recursive approaches are effective in the presence of rapidly changing flux and (or) nonperiodic thermal boundary conditions, both of which are problematic for existing approaches to heat tracing of time-varying groundwater/surface-water exchange.

Water Resources Research↗
USGS2022

The occurrence of large floods in the United States in the modern hydroclimate regime: Seasonality, trends, and large-scale climate associations

Many studies investigate river floods by analyzing annual maximum series that record the largest flow of each year, including many within-bank events inconsequential for human communities. Fewer focus on larger floods, especially at the continental scale. Using 473 streamgages across the conterminous United States with near-natural flow from 1966 to 2015, we characterized the seasonality, occurrence, and climatic associations of the 10 largest and 2 largest floods at each site. These are often overbank events that have ecosystem functions and pose risks to humans. We grouped sites into 14 clusters corresponding to climatic and physiographic regions and characterized their flood seasonality at a monthly resolution using a probabilistic method. We then evaluated annual occurrence regionally and nationally, and seasonal occurrence regionally, by complementing a traditional approach to trend analyses with a novel method based on expected occurrence. Relationships between flood occurrence and climate indices were also investigated. Large floods have strong seasonality in some regions, but in areas with numerous flood-generating mechanisms, seasonality is more complex. There is little evidence nationally that large riverine floods are more or less frequent than expected in recent years and only two regions show significant trends in annual counts; few show seasonal trends. We found some regional relationships between flood counts and climate indices, annually and seasonally; nationally the Pacific North American pattern is related to annual counts of the 2 largest floods. Large-flood occurrence was generally stable across the United States in the last five decades; this may or may not continue with projected warming.

Water Resources Research↗
USGS2021

Evaluating streamwater dissolved organic carbon dynamics in context of variable flowpath contributions with a tracer-based mixing model

This study focuses on characterizing the contributions of key terrestrial pathways that deliver dissolved organic carbon (DOC) to streams during hydrological events and on elucidating factors governing variation in water and DOC fluxes from these pathways. We made high-frequency measurements of discharge, specific conductance (SC), and fluorescent dissolved organic matter (FDOM) during 221 events recorded over 2 years within four Vermont (USA) watersheds that range in area from 0.4 to 139 km 2 . Using the SC measurements, together with statistical information on discharge, we separated the event hydrographs into contributions from three terrestrial pathways, which we refer to as riparian quickflow, subsurface quickflow, and slow-flow groundwater. The pathway discharges were used as input to a mixing model that closely approximated sub-hourly streamwater DOC concentrations as measured with the FDOM sensors. Subsurface quickflow, comprised of pre-event water, was the leading contributor to streamwater DOC fluxes, while riparian quickflow, comprised of event water, was the second-leading contributor to streamwater DOC fluxes, despite comprising the smallest proportion of streamflow yield among the three end-member pathways. Fixed-effects regression analysis revealed that the relationship between DOC fluxes from the end-member pathways and event magnitude was consistent across the four watersheds. This analysis also showed that DOC fluxes from the quickflow pathways increased significantly with temperature and varied inversely, but weakly, with catchment antecedent wetness. We believe that our approach, which leverages in-stream sensors that enable high-frequency measurements over extended periods, may be applicable for evaluating controls on DOC export from other watersheds within and beyond our study region.

New Hampshire, Vermont↗
USGS2022

Hydrologic connectivity and residence time affect the sediment trapping efficiency and dissolved oxygen concentrations of the Atchafalaya River Basin

Little is known about water movement, volume, or residence time (RT), and how those characteristics affect sediment trapping efficiency (TE) and dissolved oxygen concentrations (DO) in the United States' largest remaining bottomland hardwood swamp, the Atchafalaya River Basin. To better understand these dynamics, this study used bathymetry, lidar, and stage records to determine volumes in the Basin's hydrologically distinct water management units (WMUs). Discharge measurements determined flow distribution and RT. Residence time was compared with DO to identify conditions that coincided with DO increases or decreases. Suspended sediment concentrations (SSC) were used to determine TE relative to calculated and measured discharge and RT. Discharge through units (85–2,200 m 3 /s) and RT (0.37–231 d) depended on connectivity and river stage. At high stages, with water temperatures >20°C, DO in the largest WMU declined by −0.21 mg/l/day. DO trends indicated less well-connected areas of the WMU contributed hypoxic waters as the flood wave lengthened and stages fell. In the two WMUs examined for TE, TE (−266% to 99% and up to 38 Gg/day) correlated with hydrologic connectivity, SSC, RT, water volume, and, in one WMU, discharge losses. Long RT and high TE indicated a high potential to process nutrients. These relationships varied among WMUs. Large volumes of sediment-laden water moving over the floodplain combined with long RT, high TE, and hypoxia indicate that this ecosystem has continental-scale importance in reducing nutrient loads to the northern Gulf of Mexico. Reports from other systems suggest similar processes may be operating on other large river floodplains globally.

Louisiana↗
USGS2022

Using ensemble data assimilation to estimate transient hydrologic exchange flow under highly dynamic flow conditions

Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high-frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady-state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub-daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation-based approach to estimate the sub-daily flux under highly dynamic flow conditions using multi-depth temperature observations at a 5-min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi-depth temperature data at 1- or 2-hr time intervals assuming one-dimensional flow and heat transport governing equation. By comparing estimated fluxes with model-generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation-based flux estimation method was able to capture the vertical sub-daily fluxes using multi-depth high-resolution temperature data alone, even in the presence of multi-dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1-D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.

Washington↗
USGS2022

Geomorphic controls on floodplain connectivity, ecosystem services, and sensitivity to climate change: An example from the lower Missouri River

Floodplains of large rivers are exploited for agricultural production, industrial and municipal development, and transportation infrastructure. Recently, increased frequency of costly floods has prompted consideration of whether offsetting benefits might accrue from management of floodplains for ecosystem services. We employed a simple inundation model for 800 km of the Lower Missouri River, USA, to evaluate spatial and temporal distributions of ecological floodplain inundation metrics and how those distributions might vary with levee removal and climatic change. The model evaluates inundation at 30 × 30 m resolution on a daily basis over 82 years of record. We quantified provisioning of waterfowl habitat and potential denitrification. Spatial variability is affected by ongoing geomorphic adjustments that affect floodplain connectivity. Statistical models indicate that available floodplain area and recent aggradation are predictive of most inundation metrics. Connectivity is sensitive to climate-change scenarios that predict increased floodplain inundation during spring waterfowl migrations; the greatest sensitivity to future climate exists where channel-floodplain geomorphology presently enhances floodplain connectivity. Evaluation of floodplain denitrification indicates that on average, the nonleveed part of the floodplain could denitrify 0.05%–1.7% of the mean annual nitrogen load of the river. Levee removal could increase this rate to only 3.6% of the nitrogen load. The capacity of floodplain connectivity to influence certain ecosystem services is highly variable in space along the Lower Missouri River and may be appreciably influenced by climate change. Hence, decisions to optimize management of large-river floodplains are likely to be highly location dependent.

Illinois, Iowa, Kansas, Missouri, Nebraska, South ↗