Ground-water resources of the south--a frontier of the Nation's water supply
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Red Fleet Reservoir in Uintah County, Utah, is an approximately 26,000 acre-foot (acre-ft) on-channel reservoir in the Big Brush Creek drainage on the south slopes of the Uinta Mountains. It is operated primarily for irrigation needs while providing a supplemental drinking-water supply to the Vernal, Utah area. Red Fleet Reservoir, which was operated by the Bureau of Reclamation and the Uintah Water Conservancy District through 2015, began storing water in May 1980. The reservoir is on southward dipping Mesozoic lithologies ranging from Jurassic to Cretaceous in age. The Nugget and Frontier Sandstone aquifers are the targeted units in this investigation, which is to characterize groundwater conditions that exist in each sandstone aquifer and how they interact with Red Fleet Reservoir. Groundwater levels were measured in six wells and one spring in the Nugget Sandstone and the Frontier Sandstone aquifers. Water levels in the Nugget Sandstone aquifer were 35–70 feet above the maximum stage of Red Fleet Reservoir on the west and east banks. Water levels in the Frontier Sandstone aquifer were 15–30 feet below the observed stage of Red Fleet Reservoir on the west bank during the study period. A water budget was calculated for Red Fleet Reservoir between May 1980 and December 2015. During this period, 1,050,000 acre-ft of water from Big Brush Creek discharged into the reservoir, while 993,000 acre-ft of water was released downstream of Red Fleet Dam. Total evaporation from May 1980 through December 2015 was about 52,000 acre-ft, while total precipitation over the same period was about 12,000 acre-ft. From May 1980 through December 2015, the total pumped volume of water from the Tyzack Pump Station, at the base of Red Fleet Dam, was about 42,000 acre-ft. Total groundwater discharge to Red Fleet Reservoir from 1980 through 2015 was about 40,000 acre-ft. Water was sampled from four wells and from the inflow arm of Red Fleet Reservoir, and analyzed for major-ion chemistry, select trace metals, nutrients, and environmental tracers. Water sampled from the Nugget Sandstone aquifer yielded good-quality water with dissolved-solids concentrations of less than 200 milligram per liter, and no trace elements above the Environmental Protection Agency drinking-water standards. Water sampled from the Frontier Sandstone aquifer yielded poor-quality water with dissolved-solids concentrations of about 2,150 milligrams per liter with trace elements approaching drinking-water standards for arsenic. Dissolved noble gases used to identify recharge elevations and temperatures for groundwater indicate that water in the Nugget Sandstone aquifer likely recharged at a high altitude and low temperature, and not locally because of interaction with Red Fleet Reservoir. The Frontier Sandstone aquifer is likely recharged at low elevation and at temperatures similar to those observed at Red Fleet Reservoir.
The implementation of environmental flow regimes offers a promising means to protect and restore riverine, wetland and estuarine ecosystems, their critical environmental services and cultural/societal values. This Special Issue expands the scope of environmental flows and water science in theory and practice, offering 20 papers from academics, agency researchers and non‐governmental organisations, each with fresh perspectives on the science and management of environmental water allocations. Contributions confront the grand challenge for environmental flows and water management in the Anthropocene—the urgent need for innovations that will help to sustain the innate resilience of social–ecological systems under dynamic and uncertain environmental and societal futures. Basin‐scale and regional assessments of flow requirements mark a necessary advance in environmental water science in the face of rapid changes in water‐resource management activities worldwide (e.g. increases in dams, diversions, retention and reuse). Techniques for regional‐scale hydrological and ecohydrological modelling support ecological risk assessment and identification of priority flow management and river restoration actions. Changing flood–drought cycles, long‐term climatic shifts and associated effects on hydrological, thermal and water quality regimes add enormous uncertainty to the prediction of future ecological outcomes, regardless of environmental water allocations. An improved capacity to predict the trajectories of ecological change in rivers degraded by legacies of past impact interacting with current conditions and future climate change is essential. Otherwise, we risk unrealistic expectations from restoration of river and estuarine flow regimes. A more robust, dynamic and predictive approach to environmental water science is emerging. It encourages the measurement of process rates (e.g. birth rate, colonisation rate) and species traits (e.g. physiological requirements, morphological adaptations) as well as ecosystem states (e.g. species richness, assemblage structure), as the variables representing ecological responses to flow variability and environmental water allocations. Another necessary development is the incorporation of other environmental variables such as water temperature and sedimentary processes in flow–ecological response models. Based on contributions to this Special Issue, several recent compilations and the wider literature, we identify six major scientific challenges for further exploration, and seven themes for advancing the management of environmental water. We see the emerging frontier of environmental flows and water science as urgent and challenging, with numerous opportunities for reinvigorated science and methodological innovation in the expanding enterprise of environmental water linked to ecological sustainability and social well‐being.
During April 1999, the U.S. Geological Survey (USGS) conducted a 13-day cruise in the Garden Banks and Green Canyon regions of the Gulf of Mexico. The R/V Gyre, owned by Texas A&M University, was chartered for the cruise. The general objectives were (1) to acquire very high resolution seismic-reflection data and side-scan sonar images of the upper and middle continental slope (200-1200-m water depths), (2) to study the acoustic character and features of the sea floor for evidence of sea-floor hazards, and (3) to look for evidence of subsurface gas hydrates and their effects. The Gulf of Mexico is well known for hydrocarbon resources, with emphasis now on frontier deep-water areas. For water depths greater than about 250 m, the pressure-termperature conditions are correct for the development of shallow-subsurface gas hydrate formation (Anderson et al., 1992). Gas hydrates are ice-like mixtures of gas and water (Kvenvolden, 1993). They are known to be present from extensive previous sampling in sea-floor cores and from mound-like features observed on the sea floor in many parts of the northern Gulf, including the Green Canyon and Garden Banks areas (e.g., Roberts, 1995). Seismic-reflection data are extensive in the Gulf of Mexico, but few very-high-resolution data like those needed for gas-hydrate studies exist in the public domain. The occurrence and mechanisms of gas hydrate formation and dissociation are important to understand, because of their perceived economic potential for methane gas, their potential controls on local and regional sea-floor stability, and their possible effects on earth climates due to massive release of methane greenhouse gas into the atmosphere. Three high-resolution seismic-reflection systems and one side-scan sonar system were used on the cruise to map the surface reflectance and features of the sea floor and the acoustic geometries and character of the shallow sub-surface. The cruise was designed to acquire regional and detailed local information. The regional survey covered an area about 3400 km2 in the Green Canyon and Garden Banks regions. Data recorded included 15 cu. in. water gun multichannel seismic-reflection and Huntec boomer information. Detailed surveys were planned in two parts of the study area, but due to a winch failure only one detailed survey was done in the Green Canyon area. The detailed survey included collection of 15 cu. in. water gun multichannel seismic-reflection, chirp seismic-reflection, and side-scan data.
Sediment connectivity is a conceptualization for the transfer and storage of sediment among different geomorphic compartments across upland landscapes and channel networks. Sediment connectivity and dysconnectivity are linked to the water cycle and hydrologic systems with the associated multiscale interactions with climate, soil, topography, ecology, and landuse/landcover under natural variability and human intervention. We review current sediment connectivity and modeling approaches evaluating and quantifying water and sediment transfer in catchment systems. Many studies highlight the interaction between sediment and water in defining landscape connectivity, but many efforts to quantify and/or simulate sediment connectivity rely on the topographic/structural controls on sediment erosion and delivery. More recent modeling efforts integrate functional and structural connectivity to capture hydrologic properties influencing sediment delivery. Though the recent modeling development is encouraging, a comprehensive sediment connectivity framework, which integrates geomorphic and hydrologic processes across spatiotemporal scales, has not yet been accomplished. Such an effort requires understanding the hydrologic and geomorphic processes that control sediment source, storage, and transport at different spatiotemporal scales and across various geophysical conditions. We propose a path for developing this new understanding through an integrated hydrologic and sediment connectivity conceptual model that broadly categorizes dominant processes and patterns relevant to understanding sediment flux dynamics. The conceptual model describes hydrologic–sediment connectivity regimes through spatial-temporal feedback between hydrologic processes and geomorphic drivers. We propose that in combining hydrologic and sediment connectivity into a single conceptual model, patterns emerge such that catchments will exist in a single characteristic behavior at a particular instance, which would shift with space and time, and with landscape disturbances. Using the conceptual model as a “thinking” tool, we extract case studies from a multidisciplinary literature review—from hydrology, geomorphology, biogeochemistry, and watershed modeling to remote-sensing technology—that correspond to each of the dominant hydrologic–sediment connectivity regimes. Sediment and water interactions in real-world examples through various observational and modeling techniques illustrate the advancements in the spatial and temporal scales of landscape connectivity observations and simulations. The conceptual model and case studies provide a foundation for advancing the understanding and predictive capability of watershed sediment processes at multiple spatiotemporal scales. Plain language summary: Soil erosion and movement across the landscape are closely linked to rain events and flow pathways. Landscape connectivity is a way to consider how soil erosion from different parts of the landscape is connected to the streams. We explore where soil erosion occurs and how eroded soil moves across the landscape through the interaction with rainfall and drainage. The comprehensive understanding of sediment connectivity and its dependence on rainfall characteristics and watershed hydrology may help to inform the effective distribution of conservation funds and management actions to address water pollution from excess sediment.
Internal water storage within trees can be a critical reservoir that helps trees overcome both short- and long-duration environmental stresses. We monitored changes in internal tree water storage in a ponderosa pine on daily and seasonal scales using moisture probes, a dendrometer, and time-lapse electrical resistivity imaging (ERI). These data were used to investigate how patterns of in-tree water storage are affected by changes in sapflow rates, soil moisture, and meteorologic factors such as vapor pressure deficit. Measurements of xylem fluid electrical conductivity were constant in the early growing season while inverted sapwood electrical conductivity steadily increased, suggesting that increases in sapwood electrical conductivity did not result from an increase in xylem fluid electrical conductivity. Seasonal increases in stem electrical conductivity corresponded with seasonal increases in trunk diameter, suggesting that increased electrical conductivity may result from new growth. On the daily scale, changes in inverted sapwood electrical conductivity correspond to changes in sapwood moisture. Wavelet analyses indicated that lag times between inverted electrical conductivity and sapflow increased after storm events, suggesting that as soils wetted, reliance on internal water storage decreased, as did the time required to refill daily deficits in internal water storage. We found short time lags between sapflow and inverted electrical conductivity with dry conditions, when ponderosa pine are known to reduce stomatal conductance to avoid xylem cavitation. A decrease in diel amplitudes of inverted sapwood electrical conductivity during dry periods suggest that the ponderosa pine relied on internal water storage to supplement transpiration demands, but as drought conditions progressed, tree water storage contributions to transpiration decreased. Time-lapse ERI- and wavelet-analysis results highlight the important role internal tree water storage plays in supporting transpiration throughout a day and during periods of declining subsurface moisture.
Introduction: Rangeland ponds are vital to the livelihoods of pastoral and agropastoral communities in Africa, providing an important source of water for livestock. However, sparse instrumentation across much of Africa makes it extremely challenging to monitor surface water availability in these areas. Model estimates of surface water, for example, as used by the Famine Early Warning Systems Network (FEWS NET) Water Point Viewer, are one of the few operational tools available to monitor surface water stress across pastoral areas of the Sahel and East Africa. Methods: Water availability data from these models are difficult to validate. New methods using satellite data to classify surface water provide an opportunity to assess the performance of these tools. This study compares water availability estimates derived from Landsat and Sentinel 1 satellite imagery to in situ observations and model simulations of water availability in 22 ephemeral ponds located in the Ferlo region of Senegal. Results and discussion: The Active-Passive Water Classification (APWC) algorithm detected surface water at each location. Over 2022 and 2023, water was detected in pond locations annually at a frequency of 68.2% for all ponds and at a frequency of 43.8% for ponds with a surface area <10,000 square meters (m 2 ). The APWC results outperform global and continental surface water datasets in the Ferlo region. Seasonal water availability was captured in 12 ponds over the 2022 and 2023 seasons. The 12 locations can function as sentinel ponds to monitor local water availability. Study results demonstrate the viability of satellite methods to assess water availability in the region, as well as the challenges to using satellite-based methods to estimate water availability in small ponds.
River corridors supply a substantial proportion of the fresh water for societal and ecological needs. Individual functions of flowing (lotic) streams and rivers and ponded (lentic) waterbodies such as lakes and reservoirs are well-studied, but their collective functions are not as well understood. Here we bring together nationally consistent river corridor datasets to characterize the contributions of lotic and lentic features and to estimate changes over the past centuries. High-resolution datasets describing waterbodies across 10 million kilometers of the conterminous U.S. (CONUS) river network were classified by waterbody type and origin (historic vs. human-made or intensively managed), surface areal coverage, and degree of connectivity as estimated by a change in water residence timescale in river corridors. Four centuries of human disturbance drove large swings in river corridor makeup, with a transition toward more lotic systems caused by beaver extirpation and abandonment of waterwheel mill ponds by end of the nineteenth century. The twentieth century saw a vast expansion (49%) in river corridor areal coverage resulting from construction and management of small ponds and reservoirs for drinking water, hydropower, irrigation and livestock watering, and stormwater control. Water residence timescale in river corridors doubled or quadrupled over large areas, and more in specific locations, during the twentieth century as a result of the increased coverage of reservoirs and managed small ponds. Although reservoirs and lakes now dominate river corridor surface areas, we found that the growing number of small ponds impacts a greater proportion of network length through their influence on headwater streams where most water and chemical runoff enters the river corridor. We close with an agenda for integrated modeling of the physical, biogeochemical, and ecological drivers of river corridor functions, trajectories of change, and management opportunities.
Wildfires pose a risk to water supplies in the western U.S. and many other parts of the world, due to the potential for degradation of water quality. However, a lack of adequate data hinders prediction and assessment of post-wildfire impacts and recovery. The dearth of such data is related to lack of funding for monitoring extreme events and the challenge of measuring the outsized hydrologic and erosive response after wildfire. Assessment and prediction of post-wildfire surface water quality would be strengthened by the strategic monitoring of key parameters, and the selection of sampling locations based on the following criteria: (1) streamgage with pre-wildfire data; (2) ability to install equipment that can measure water quality at high temporal resolution, with a focus on storm sampling; (3) minimum of 10% drainage area burned at moderate to high severity; (4) lack of major water management; (5) high-frequency precipitation; and (6) availability of pre-wildfire water-quality data and (or) water-quality data from a comparable unburned basin. Water-quality data focused on parameters that are critical to human and (or) ecosystem health, relevant to water-treatment processes and drinking-water quality, and (or) inform the role of precipitation and discharge on flow paths and water quality are most useful. We discuss strategic post-wildfire water-quality monitoring and identify opportunities for advancing assessment and prediction. Improved estimates of the magnitude, timing, and duration of post-wildfire effects on water quality would aid the water resources community prepare for and mitigate against impacts to water supplies.
Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution ( in-situ ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.
Riverbeds are hotspots for microbially-mediated reactions that exhibit pronounced variability in space and time. It is challenging to resolve biogeochemical mechanisms in natural riverbeds, as uncontrolled settings complicate data collection and interpretation. To overcome these challenges, laboratory flumes are often used as proxies for natural riverbed systems. Flumes capture spatiotemporal variability and thus allow for controlled investigations of riverbed biogeochemistry. These investigations implicitly rely on the assumption that the flume microbiome is similar to the microbiome of natural riverbeds. However, this assumption has not been tested and it is unknown how the microbiome of a flume compares to natural aquatic settings, including riverbeds. To evaluate the fundamental assumption that a flume hosts a microbiome similar to natural riverbed systems, we used 16s rRNA gene sequencing and publicly available data to compare the sediment microbiome of a single large laboratory flume to a wide variety of natural ecosystems including lake and marine sediments, river, lake, hyporheic, soil, and marine water, and bank and wetland soils. Richness and Shannon diversity metrics, analyses of variance, Bray-Curtis dissimilarity, and analysis of the common microbiomes between flume and river sediment all indicated that the flume microbiome more closely resembled natural riverbed sediments than other ecosystems, supporting the use of flume experiments for investigating natural microbially-mediated biogeochemical processes in riverbeds.
Wildland–urban interface fires (WUI fires) can pose a significant threat to water resources, including drinking water supplies, water treatment infrastructure, ecosystem function, and agricultural irrigation. Wildfires, especially WUI fires, are expected to increase in frequency and severity. Despite the need for effective mitigation and response strategies for wildfires, rapid research co-production to support decision-making for water incident response and water management is generally limited. This manuscript draws on five U.S. wildfire case studies to highlight how research co-production between scientists, water agencies, and managers supports more effective decision-making for water resilience and recovery. The case studies demonstrate the importance of rapid response activities, coordinating collaborative response, pre-wildfire preparation, and knowledge co-production among agencies, researchers, and managers in addressing the impacts of wildfires on water supply and quality. The lessons learned emphasize opportunities to pivot wildfire-water research and operations from reactive to proactive, focusing on mutually beneficial activities such as understanding watershed health, fostering collaboration, embracing new discoveries and tools, and enabling pre-wildfire research through table-top activities, workshops, pre-fire data collection and analysis, and appointing a central water response lead. These outcomes inform the development of a research-to-operations and operations-to-research (R2O2R) co-production framework and future opportunities to guide proactive response and management efforts before, during, and after wildfire.
Creating sustainable, resilient, and livable cities calls for integrative approaches and collaborative practices across temporal and spatial scales. However, practicability is challenged by institutional, social, and technical complexities and the need to build collective understanding of integrated approaches. Rapid urbanization along the United States-Mexico border, fueled by industrialization, trade, and migration, has resulted in cities confronted with recurrent flooding risk, extended drought, water pollution, habitat destruction and systemic vulnerabilities. The international border, which separates natural and built ecosystems, is both a challenge and an opportunity, making a unique social and institutional setting ideal for testing the integration of urban planning and water management. Our research focuses on fusing multi-functional and multi-scalar green infrastructure to restore ecosystem services through a strategic binational planning process. This paper describes this planning process, including the development and application of both a land suitability analysis and a hydrological model to optimally site green infrastructure in the Nogales, Arizona, United States—Nogales, Sonora, Mexico, cross border region. We draw lessons from this process and stakeholder feedback focused on the potential for urban green infrastructure, to allow for adaptation and even transformation in the face of current and future challenges such as limited resources, underdeveloped governance, bordering, and climate change. In sum, a cross border network of green infrastructure can provide a backbone to connect this transboundary watershed while providing both hydrological and social benefits.
Conventional, field-based streamflow monitoring in remote, inaccessible locations such as Alaska poses logistical challenges. Safety concerns, financial considerations, and a desire to expand water-observing networks make remote sensing an appealing alternative means of collecting hydrologic data. In an ongoing effort to develop non-contact methods for measuring river discharge, we evaluated the potential to estimate surface flow velocities from satellite video of a large, sediment-laden river in Alaska via particle image velocimetry (PIV). In this setting, naturally occurring sediment boil vortices produced distinct water surface features that could be tracked from frame to frame as they were advected by the flow, obviating the need to introduce artificial tracer particles. In this study, we refined an end-to-end workflow that involved stabilization and geo-referencing, image preprocessing, PIV analysis with an ensemble correlation algorithm, and post-processing of PIV output to filter outliers and scale and geo-reference velocity vectors. Applying these procedures to image sequences extracted from satellite video allowed us to produce high resolution surface velocity fields; field measurements of depth-averaged flow velocity were used to assess accuracy. Our results confirmed the importance of preprocessing images to enhance contrast and indicated that lower frame rates (e.g., 0.25 Hz) lead to more reliable velocity estimates because longer capture intervals allow more time for water surface features to translate several pixels between frames, given the relatively coarse spatial resolution of the satellite data. Although agreement between PIV-derived velocity estimates and field measurements was weak ( R 2 = 0.39) on a point-by-point basis, correspondence improved when the PIV output was aggregated to the cross-sectional scale. For example, the correspondence between cross-sectional maximum velocities inferred via remote sensing and measured in the field was much stronger ( R 2 = 0.76), suggesting that satellite video could play a role in measuring river discharge. Examining correlation matrices produced as an intermediate output of the PIV algorithm yielded insight on the interactions between image frame rate and sensor spatial resolution, which must be considered in tandem. Although further research and technological development are needed, measuring surface flow velocities from satellite video could become a viable tool for streamflow monitoring in certain fluvial environments.
Headwater streams account for more than 89% of global river networks and provide numerous ecosystem services that benefit downstream ecosystems and human water uses. It has been established that changes in climate have shifted the timing and magnitude of observed precipitation, which, at specific gages, have been directly linked to long-term reductions in large river discharge. However, climate impacts on ungaged headwater streams, where ecosystem function is tightly coupled to flow permanence along the river corridor, remain unknown due to the lack of data sets and ability to model and predict flow permanence. We analyzed a network of 10 gages with 38–69 years of records across a 5th-order river basin in the U.S. Pacific Northwest, finding increasing frequency of lower low-flow conditions across the basin. Next, we simulated river network expansion and contraction for a 65-year period of record, revealing 24% and 9% declines in flowing and contiguous network length, respectively, during the driest months of the year. This study is the first to mechanistically simulate network expansion and contraction at the scale of a large river basin, informing if and how climate change is altering connectivity along river networks. While the heuristic model presented here yields basin-specific conclusions, this approach is generalizable and transferable to the study of other large river basins. Finally, we interpret our model results in the context of regulations based on flow permanence, demonstrating the complications of static regulatory definitions in the face of non-stationary climate.
Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent observations from other sites to inform focal sites. In this paper, we evaluate two different DL model structures, a long short-term memory neural network (LSTM) and a recurrent graph convolutional neural network (RGCN), both with and without data assimilation for forecasting daily maximum stream temperature 7 days into the future at monitored and unmonitored locations in a 70-segment stream network. All our DL models performed well when forecasting stream temperature as the root mean squared error (RMSE) across all models ranged from 2.03 to 2.11°C for 1-day lead times in the validation period, with substantially better performance at gaged locations (RMSE = 1.45–1.52°C) compared to ungaged locations (RMSE = 3.18–3.27°C). Forecast uncertainty characterization was near-perfect for gaged locations but all DL models were overconfident (i.e., uncertainty bounds too narrow) for ungaged locations. Our results show that the RGCN with data assimilation performed best for ungaged locations and especially at higher temperatures (>18°C) which is important for management decisions in our study location. This indicates that the networked model structure and data assimilation techniques may help borrow information from nearby monitored sites to improve forecasts at unmonitored locations. Results from this study can help guide DL modeling decisions when forecasting other important environmental variables.
Retention, processing, and transport of solutes and particulates in stream corridors are influenced by the travel time of streamflow through stream channels, which varies dynamically with discharge. The effects of streamflow variability across sites and over time cannot be addressed by time-averaged models if parameters are based solely on the characteristics of mean streamflow. We develop methods to account for the effects of streamflow variability on travel time and compare our estimates to flow-weighted (“effective”) travel time at 100 streams in the southeastern United States. Velocity time series were generated for each stream from multiple-year (median 15.5 years), high-frequency (15 min interval) records of instantaneous streamflow and field measurements of velocity and inverted to produce time series of specific travel time [T/L]. The effective travel times for streams are 60–90% of the specific travel time of mean streamflow because a large fraction of the total streamflow volume is discharged during higher flows with higher velocities. We find that adjusting the specific travel time of mean streamflow at a site by a factor of 0.81 generally accounts for the effect of a skewed streamflow distribution, but at-site estimates of the coefficient of variation of streamflow are necessary to resolve differences in streamflow variability between streams or changes in variability over time. For example, the effective travel time of urban streams is less than the effective travel of forested streams in the southeastern United States as a result of increased streamflow variability in urban streams. Effective travel time accounts for both the variation in velocity with streamflow and the large fraction of streamflow discharged during high flows in most streams and provides time-averaged models with limited capability to account for effects of streamflow variability that otherwise they lack. This capability is needed for continental-scale modeling where streamflow variability is not uniform because of heterogeneous surficial geology, hydro-climatology, and vegetation and for applications where streamflow variability is not stationary as a response to climate change or hydrologic alteration.
Spilled oil in inland waterways can aggregate with mineral and organic particles to form oil-particle aggregates (OPAs). OPAs can be transported in suspension or deposited to the bed. Modeling the fate and transport of OPAs can provide useful information for making mitigation decisions. A novel open-source tool, FluOil, is developed to predict where OPAs may deposit and when they arrive in affected river/lake reaches by implementing the random walk particle tracking algorithm to represent the advection, diffusion, deposition, and resuspension of OPAs. The usability of FluOil is demonstrated with the 2010 Kalamazoo River oil spill case study. An unsteady hydrodynamic model simulates the river hydraulics and provides hydraulic data for use in FluOil. Settling velocity and critical shear stress for resuspension are the most important OPA properties concerning the transport and deposition of OPAs. Settling velocity determines the vertical distribution of OPAs and, thus, the travel speed, whereas critical shear stress determines where and when OPAs are deposited and resuspended.