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At least 19 recordsLinked to original sources
USGS2016

Application of SPARROW modeling to understanding contaminant fate and transport from uplands to streams

Understanding spatial variability in contaminant fate and transport is critical to efficient regional water-quality restoration. An approach to capitalize on previously calibrated spatially referenced regression (SPARROW) models to improve the understanding of contaminant fate and transport was developed and applied to the case of nitrogen in the 166,000 km 2 Chesapeake Bay watershed. A continuous function of four hydrogeologic, soil, and other landscape properties significant ( α = 0.10) to nitrogen transport from uplands to streams was evaluated and compared among each of the more than 80,000 individual catchments (mean area, 2.1 km 2 ) in the watershed. Budgets (including inputs, losses or net change in storage in uplands and stream corridors, and delivery to tidal waters) were also estimated for nitrogen applied to these catchments from selected upland sources. Most (81%) of such inputs are removed, retained, or otherwise processed in uplands rather than transported to surface waters. Combining SPARROW results with previous budget estimates suggests 55% of this processing is attributable to denitrification, 23% to crop or timber harvest, and 6% to volatilization. Remaining upland inputs represent a net annual increase in landscape storage in soils or biomass exceeding 10 kg per hectare in some areas. Such insights are important for planning watershed restoration and for improving future watershed models.

JAWRA↗
USGS2016

NHDPlusHR: A national geospatial framework for surface-water information

The U.S. Geological Survey is developing a new geospatial hydrographic framework for the United States, called the National Hydrography Dataset Plus High Resolution (NHDPlusHR), that integrates a diversity of the best-available information, robustly supports ongoing dataset improvements, enables hydrographic generalization to derive alternate representations of the network while maintaining feature identity, and supports modern scientific computing and Internet accessibility needs. This framework is based on the High Resolution National Hydrography Dataset, the Watershed Boundaries Dataset, and elevation from the 3-D Elevation Program, and will provide an authoritative, high precision, and attribute-rich geospatial framework for surface-water information for the United States. Using this common geospatial framework will provide a consistent basis for indexing water information in the United States, eliminate redundancy, and harmonize access to, and exchange of water information.

JAWRA↗
USGS2016

Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA

We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree-ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree-ring chronologies where high snowpack limits growth, which better represent the contribution of cool-season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high-intensity, long-duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s-1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm-season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late-19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands

Pacific Northwest↗
USGS2018

Estimating lag to peak between rainfall and peak streamflow with a mixed-effects model

We test the use of a mixed-effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km2). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed-effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15-min rainfall depth for individual storms as explanatory features. Based on a remove-one-site cross-validation analysis, the prediction errors of this model ranged from 42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfallrunoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.

Maine↗
USGS2018

Streamflow, sediment transport, and geomorphic change during the 2011 flood on the Missouri River near Bismarck-Mandan, ND

Geomorphic change from extreme events in large managed rivers has implications for river management. A steady-state, quasi-three-dimensional hydrodynamic model was applied to a 29-km reach of the Missouri River using 2011 flood data. Model results for an extreme flow (500-year recurrence interval [RI]) and an elevated managed flow (75-year RI) were used to assess sediment mobility through examination of the spatial distribution of boundary or bed shear stress ( τ b ) and longitudinal patterns of average τ b , velocity, and kurtosis of τ b . Kurtosis of τ b was used as an indicator of planform channel complexity and can be applied to other river systems. From differences in longitudinal patterns of sediment mobility for the two flows we can infer: (1) under extreme flow, the channel behaves as a single-thread channel controlled primarily by flow, which enhances the meander pattern; (2) under elevated managed flows, the channel behaves as multithread channel controlled by the interaction of flow with bed and channel topography, resulting in a more complex channel; and (3) for both flows, the model reach lacks a consistent pattern of deposition or erosion, which indicates migration of areas of erosion and deposition within the reach. Despite caveats and limitations, the analysis provides useful information about geomorphic change under extreme flow and potential implications for river management. Although a 500-year RI is rare, extreme hydrologic events such as this are predicted to increase in frequency.

North Dakota↗
USGS2019

Modeling connectivity of non‐floodplain wetlands: Insights, approaches, and recommendations

Representing hydrologic connectivity of non‐floodplain wetlands (NFWs) to downstream waters in process‐based models is an emerging challenge relevant to many research, regulatory, and management activities. We review four case studies that utilize process‐based models developed to simulate NFW hydrology. Models range from a simple, lumped parameter model to a highly complex, fully distributed model. Across case studies, we highlight appropriate application of each model, emphasizing spatial scale, computational demands, process representation, and model limitations. We end with a synthesis of recommended “best modeling practices” to guide model application. These recommendations include: (1) clearly articulate modeling objectives, and revisit and adjust those objectives regularly; (2) develop a conceptualization of NFW connectivity using qualitative observations, empirical data, and process‐based modeling; (3) select a model to represent NFW connectivity by balancing both modeling objectives and available resources; (4) use innovative techniques and data sources to validate and calibrate NFW connectivity simulations; and (5) clearly articulate the limits of the resulting NFW connectivity representation. Our review and synthesis of these case studies highlights modeling approaches that incorporate NFW connectivity, demonstrates tradeoffs in model selection, and ultimately provides actionable guidance for future model application and development.

Journal of the American Water Resources Associatio↗
USGS2020

Thermal diversity of salmon streams in the Matanuska-Susitna Basin, Alaska

We present the first description of summer stream thermal regimes in Alaska using metrics that represent the magnitude, variability, frequency, duration, and timing of temperature events related to salmon life histories. We used cluster analysis to characterize thermal regimes present in the Matanuska-Susitna (Mat-Su) Basin based on 10 nonredundant temperature metrics and identified the most important drivers of our thermal regimes using random forests. Our results indicated four distinct thermal regimes among the 248 site-years in the Mat-Su Basin. Over 41% of site-years had cold-stable temperatures. An additional 22% of site-years had cold-variable temperatures and the latest timing of maximum stream temperatures. Twenty-eight percent of site-years had warm-variable temperatures that remained above 13°C for approximately two months. The remaining 9% of site-years had the warmest and most variable daily maximum temperatures, exceeding 18°C for almost one month, indicating potential impacts to spawning and rearing salmon. Climate and landscape drivers differentiating thermal regimes included spring and summer air temperatures, spring snowpack, summer precipitation, wetlands, and lakes. Climate change projections for 2050–2069 indicated a future shift toward warm thermal regimes and a reduced portfolio of thermal diversity. These results portend negative impacts to some salmon populations and stress the importance of prioritizing actions that maintain thermal regime diversity.

Alaska↗
USGS2022

Effect of restoration on plant greenness and water use in relation to drought in the riparian corridor of the Colorado River delta

Revitalization of the Colorado River delta riparian corridor and increasing riparian plant greenness and water use may be accomplished by added water and restoration efforts to offset declines measured since 2000 by Landsat. We use the two-band Enhanced Vegetation Index (EVI2; a proxy for greenness) and evapotranspiration (ET, mm/day) using EVI2 and potential ET(ETo) from Yuma Valley. We assess if restoration with only 7.5% landcover had an impact on the unrestored reach-level landcover by measuring these two metrics, EVI2 and ET(EVI2) by comparing restored and unrestored areas. A key finding is that over 21-years EVI2 in the unrestored corridor decreased by 23.6% and ET(EVI2) decreased by 32% (0.87 mm/day). Since 2011, the unrestored reaches lost EVI2 (11%) and −0.73 mm/day ET(EVI2) (28%), but restored sites increased in EVI2 (36%) and 0.58 mm/day ET(EVI2) (20%). Water delivered to restored sites increased EVI2 by 33.6% and 1.29 mm/day ET(EVI2) (58%). EVI2 and ET(EVI2) as a function of the Standardized Precipitation Evapotranspiration Index for drought periods highlight that restored and unrestored sites respond differently. Unrestored reaches are in decline; restored sites show increases in EVI2 and ET(EVI2). Restored sites do not have a significant impact on unrestored adjacent area, but smaller surface flows, a greater reliance on directed agricultural return flows, and deliveries of water to active restoration sites have revitalized habitat and increased ecosystem services in the delta.

Colorado River delta↗
USGS2022

Stakeholder engagement to guide decision-relevant water data delivery

Water resources management and policy making require access to reliable scientific data. However, water managers may need to overcome various obstacles to accessing data. For example, insufficient technological infrastructures, low data literacy, and data format complexities often inhibit data user access. Thus, it is imperative to include stakeholders in the design of data delivery systems. The United States Geological Survey's Water Resources Mission Area is currently developing Integrated Water Availability Assessments (IWAAs) — multi-extent, stakeholder driven, near real-time water availability census and prediction for human and ecological uses. To provide appropriate user accessibility to data delivery systems developed for IWAAs, a user-centered design process including stakeholder focus groups was used to determine potential water data user needs and preferences. Focus groups identified five types of potential users: Public sector water resources managers, Public sector water resources manager data analysts, Industry and private companies, Tribal Nations, and Nonprofit organizations. Different water data user types depended on diverse spatial and temporal scale data. Public sector water resources managers benefitted most from data synthesized into user-friendly platforms and Public sector water resources data analysts preferred easy access to raw data. These findings can support the development of a water data delivery platform that meets a variety of user needs.

Journal of the American Water Resources Associatio↗
USGS2023

Integrated water resources trend assessments: State of the science, challenges, and opportunities for advancement

Water is vital to human life and healthy ecosystems. Here we outline the current state of national-scale water resources trend assessments, identify key gaps, and suggest advancements to better address critical issues related to changes in water resources that may threaten human development or the environment. Questions like, “Do we have less suitable drinking water now than we had 20 years ago?” or “Are flood events more common now than they were in the past?” prompted improvements in data, trend estimation methods, and modeling frameworks to track changes in, and better understand how land use and climate influence four water resources domains: surface and groundwater quantity and quality. However, continued advancement in trend assessments to better address issues related to changes in water availability is needed. Areas of need include more timely and efficient delivery of water resources trend results and improved capacity to estimate trends at unmonitored locations. Additional integration pieces include increased understanding of groundwater–surface water interactions, incorporation of both quantity and quality trends into water availability estimates, and the refinement of trend metrics to account for the competing needs of society and ecological integrity. Coupled with improved driver attribution studies, these components will better inform current and future water resources management.

Journal of the American Water Resource Association↗
USGS2023

A survey of non-USGS continuous streamflow gaging networks in the Pacific Northwest

Extensive streamflow data sources exist beyond the largest streamflow data provider in the United States, the U.S. Geological Survey. We developed and distributed a survey to about 300 individuals and organizations that collect streamflow data across the Pacific Northwest (Idaho, Oregon, Washington). We received 100 responses with 56% of those sufficiently complete to include in the analysis. From these responses, there are about 2000 streamflow monitoring locations in the region beyond the USGS monitoring network. The duration of record for gages is related to the size of the streamflow gaging network, with small and large networks generally operating monitoring locations for less than 5 years and more than 10 years, respectively. Quality assurance and quality control are variable across organizations, with 41% of respondents having at least two review steps and 13% that audit their data for long-term consistency. Results of this survey begin to establish the differing capabilities of large and small stream gaging networks and highlight how supporting the overall quality streamflow data collection and management within the water resources community will improve our ability to harmonize these datasets in the future.

Idaho, Montana, Nevada, Oregon, Washington, Wyomin↗
USGS2025

Hydroclimate projections and effects on runoff at National Wildlife Refuges in the semi-arid western U.S.

This study evaluated hydroclimate projections and effects on runoff at National Wildlife Refuges in a semiarid region of the western United States (U.S. Fish and Wildlife Service Region 6) using mean air temperature (TAVE) and precipitation (PPT) inputs and runoff (RO) output from a national application of a Monthly Water Balance Model (MWBM). An ensemble of statistically downscaled global circulation models for two future emissions scenarios from Coupled Model Intercomparison Project 3 and 5 (CMIP3 and 5) were assessed at the refuges for the years 1950–2099. TAVE, PPT, and RO and departures from mean baseline conditions were analyzed from MWBM hydrologic response units within refuge boundaries. Seasonal results were evaluated across four periods: historical (1951–1969), baseline (1981–1999), 2050 (2041–2059), and 2080 (2071–2089). Projected TAVE increases for all refuges and time periods, whereas PPT and RO are much more variable across ecoregions. Using the high emission scenario, summer mean monthly TAVE increases range from 4.8°C to 5.5°C by 2080. Summer mean monthly PPT departures vary from −5.7 to 3.9 mm (up to 14% decrease), with decreases at 41% of refuges. Summer RO departures range from −16.7 to 0.2 mm (up to 60% decrease), with decreases at 71% of refuges. Under the same emission scenario, winter PPT and RO increase at most refuges by 2080. These variable departures will create substantial challenges for future conservation management in the region.

JAWRA Journal of the American Water Resources Asso↗
USGS2025

Leveraging high-frequency sensor data and U.S. National Water Model output to forecast turbidity in a drinking water supply basin

As high-frequency sensor networks increasingly enhance data-driven models of water quality, process-based models like the U.S. National Water Model (NWM) are generating accessible forecasts of streamflow at increasingly dense scales. There is now an opportunity to combine these products to construct actionable water quality forecasts. To that end, we couple streamflow forecasts from the NWM to a gradient-boosted decision tree algorithm (LightGBM) trained on 5+ years of high-frequency monitoring data to forecast in-stream turbidity levels in the Catskill Mountains, NY, USA. Results indicate LightGBM models are capable of relatively skillful predictions, which enable robust forecasts for 1–3 days lead times. LightGBM models offer improvements over a simplified linear model across the entire forecast horizon, and more spatially complex models are more resilient to error at shorter lead times (1–3 days). Moreover, interpretation of model features emphasizes high flows as a driver of turbidity in the region. Results suggest that interpretable, flexible, and efficient machine learning algorithms can produce capable water quality forecasts from streamflow forecasts and expand understanding of process dynamics. The use case illustrated here—to our knowledge the first NWM-based water quality forecast—underscores the potential to employ the NWM to expand national water quality forecasting capacity and can overall serve as a guide for similar efforts in basins across the country.

New York↗
USGS2025

The nonpoint source challenge: Obstacles and opportunities for meeting nutrient reduction goals in the Chesapeake Bay watershed

This document examines the Chesapeake Bay watershed response to nutrient and sediment reduction efforts under the Clean Water Act's total maximum daily load (TMDL) regulation. As the 2025 Chesapeake Bay TMDL deadline approaches, water quality goals remain unmet, primarily because of nonpoint source pollution, the largest remaining source of nutrients and sediment, and the primary obstacle to meeting the TMDL. We focus on the factors influencing the gap between the expected effect of management to reduce nonpoint source loads reaching the Bay and empirical evidence suggesting that decades of effort have not produced the expected improvement. This gap may be caused by both insufficient scale and type of implemented water quality management practices and by an overestimation of practice effectiveness. Reasons water quality goals remain unmet include legacy nutrients and lag times masking or delaying the effects of management efforts, areas with large nutrient mass imbalances contributing disproportionate loads, and the difficulty of incentivizing behavior change in voluntary nonpoint source programs. Closing the response gap may require fundamental changes to nonpoint source programs. Apart from seeking additional funding, nonpoint source programs could develop policies to more effectively incentivize behavior change, identify and target treatment of high loading areas with appropriate management actions, and address nutrient mass imbalances.

Chesapeake Bay watershed↗
USGS2025

Harmonization of a water withdrawal dataset for the conterminous United States

The U.S. Geological Survey is developing nationally consistent water-use modeling approaches to replace previous methods relying on locally specific reported and estimated data. These national assessments require datasets that incorporate water withdrawal variability across the United States and over long periods. However, source data often have unclear definitions, missing or varied units, differing temporal resolutions, varied data quality, and inconsistent formats, which hinder automation and require individualized processing. The public-supply datasets described in this paper were used in machine learning models to estimate annual and monthly public-supply water use for 2000–2020 for the conterminous United States (CONUS) and in a model to estimate public-supply deliveries. Public-supply withdrawal data were acquired for the CONUS and the District of Columbia; however, 11 states had annual data for only 1 year, and 10 states had no monthly data. Annual withdrawal data were acquired for 81% of public-supply water service areas, and monthly withdrawal data were acquired for 47% for at least 1 year from 2000 to 2020. These datasets and methods provide the most comprehensive collection of reported public-supply withdrawals to date and can be used by water-use managers, the scientific community, and the broader public. The extensive data processing described herein can be applicable to datasets representing other categories of water use.

conterminous United States↗