Daily mean streamflow was estimated for all the nontidal parts of the Chesapeake Bay riverine system with the Unit Flows in Networks of Channels computer application using measured streamflow at the most downstream gage of selected rivers. The streamflows estimated by the Unit Flows in Networks of Channels computer application were aggregated at the 12-digit Hydrologic Unit Code level, after which base flow was estimated by two hydrograph-separation methods. Based on six sites selected for comparison, modeled streamflows are typically within an order of magnitude of measured streamflows, and monthly mean streamflows are in better agreement than daily streamflows. For the six selected sites, the base-flow values calculated by the two hydrograph-separation methods were compared. The monthly base-flow values also were in better agreement than the daily base-flow values. The modeled data were animated to better visualize spatial and temporal variability of streamflow and base-flow index.
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Wetland conservation increasingly must account for climate change and legacies of previous land-use practices. Playa wetlands provide critical wildlife habitat, but may be impacted by intensifying droughts and previous hydrologic modifications. To inform playa restoration planning, we asked: (1) what are the trends in playa inundation? (2) what are the factors influencing inundation? (3) how is playa inundation affected by increasingly severe drought? (4) do certain playas provide hydrologic refugia during droughts, and (5) if so, how are refugia patterns related to historical modifications? Using remotely sensed surface-water data, we evaluated a 30-year time series (1985–2015) of inundation for 153 playas of the Great Basin, USA. Inundation likelihood and duration increased with wetter weather conditions and were greater in modified playas. Inundation probability was projected to decrease from 22% under average conditions to 11% under extreme drought, with respective annual inundation decreasing from 1.7 to 0.9 months. Only 4% of playas were inundated for at least 2 months in each of the 5 driest years, suggesting their potential as drought refugia. Refugial playas were larger and more likely to have been modified, possibly because previous land managers selected refugial playas for modification. These inundation patterns can inform efforts to restore wetland functions and to conserve playa habitats as climate conditions change.
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Each guidebook chapter was created using a standardized template to summarize a spatial dataset or a group of closely related datasets. Datasets were selected according to standardized criteria based on input through a collaborative process involving researchers and natural-resource managers throughout the Pacific Northwest region. In each chapter, basic spatial and temporal information is provided for the dataset, along with a conceptual overview, glossary of key terms, links to download data and supporting documentation, a brief methods summary describing how the dataset was created, guidelines for dataset interpretation, assessment of uncertainties along with evaluation of caveats and simplifying assumptions, and information about potential and actual conservation applications of the dataset. Collectively, this information provides natural-resource managers with “snapshots” of a variety of datasets representing diverse processes and conditions, including climate projections, changes in hydrologic conditions, vegetation and fire-regime shifts, animal habitat changes, species movements, and topographic and soil conditions relevant to climate change. Along with other types of data and site-specific information, the datasets described in this guidebook have the potential to inform management of valued natural resources throughout the Pacific Northwest region in the context of adaptation to changing climate conditions.","language":"English","publisher":"Department of Interior Northwest Climate Adaptation Science Center","usgsCitation":"Cartwright, J.M., Belote, T., Blasch, K.W., Campbell, S., Chambers, J.C., Davis, R.J., Dobrowski, S., Dunham, J., Gergel, D., Isaak, D., Jaeger, K., Krosby, M., Langdon, J., Lawler, J.J., Littlefield, C.E., Luce, C.H., Maestas, J.D., Martinez, A., Meddens, A.J., Michalak, J., Parks, S.A., Peterman, W., Popper, K., Ringo, C., Sando, R., Schindel, M., Stralberg, D., Theobald, D.M., Walker, N., Wilsey, C., Yang, Z., and Yost, A., 2020, A guidebook to spatial datasets for conservation planning under climate change in the Pacific Northwest, 212 p.","productDescription":"212 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That requirement prompted the initiation of the assessment of three existing watershed models that were developed to simulate those processes. Three existing rainfall-runoff modeling software packages—Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) (using two sets of methods), Program for Predicting Polluting Particle Passage Through Pits, Puddles, and Ponds (P8), and Arid-Lands Hydrologic Model (AHYMO)—were compared to determine which provided the best balance of accuracy and usability for simulating storm runoff in small watersheds in the urbanized area of Albuquerque, New Mexico. Additionally, results of this study could help inform model users who have interest in simulating storm runoff in similar urban areas throughout the United States. Each model was used to simulate storm runoff in the Hahn Arroyo watershed, an urbanized watershed with concrete-lined arroyo channels in the northeastern quadrant of Albuquerque that exhibits flashy, monsoonal-driven storm runoff. Model results were compared to observed discharge data, according to literature-recommended performance measures and performance evaluation criteria. The HEC-HMS model using the Soil Conservation Service (SCS) curve number (CN) and SCS unit hydrograph methods ranked the highest when averaging the individual performance measures (Nash-Sutcliffe Efficiency, percent bias, and coefficient of determination) rankings together across the hourly calibration and validation periods, followed by P8, which was tied with the HEC-HMS initial and constant approach. For daily rankings using the same rank-averaging approach, the HEC-HMS CN-based model and P8 were tied for the highest ranking, followed by the HEC-HMS initial and constant approach. Alternatively, rating performance using validation period results as an indication of the expected confidence in forecasted results for future conditions, the P8 model performed best for both hourly and daily time-steps, followed by the HEC-HMS CN-based model and the HEC-HMS initial and constant-based model. However, based on the literature performance evaluation criteria, the HEC-HMS and P8 models overall had marginally satisfactory performance only for operation at the daily time-step. Direct comparison of the HEC-HMS and P8 models to the AHYMO is difficult, given the different performance assessment criteria used to assess these models separately in this study, as recommended by the literature. The AHYMO results generally lacked precision, given the wide range in the performance assessment values across events in percent error in peak discharge, difference in timing of peak discharge, percent error in total runoff volume, and difference in duration of event relative to observed data. For some events, however, the AHYMO results were fairly accurate, and AHYMO was likely a good predictor of the timing of storm runoff and the shape of the hydrograph. This study did not assess the results for all potential applications of the models in the Albuquerque urbanized area. Further study may be required to assess the model performance capabilities in other modeling applications.
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Brianna is a hydrologist in the Hydrologic Investigations (Studies) Unit. She received a bachelor of science degree in chemical engineering and a master’s degree in civil engineering from the University of Kansas.
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Observational networks enhance real‐time situational awareness for emergency and water resource management during extreme weather events. We present examples of how a diverse, multitiered observational network in California provided insights into hydrometeorological processes and impacts during a 3‐day atmospheric river storm centered on 14 February 2019. This network, which has been developed over the past two decades, aims to improve understanding and mitigation of effects from extreme storms influencing water resources and natural hazards. We combine atmospheric reanalysis output and additional observations to show how the network allows: (1) the validation of record cool season precipitable water observations over southern California; (2) the identification of phenomena that produce natural hazards and present difficulties for short‐term weather forecast models, such as extreme precipitation amounts and snow level variability; (3) the use of soil moisture data to improve hydrologic model forecast skill in northern California's Russian River basin; and (4) the combination of meteorological data with seismic observations to identify when a large avalanche occurred on Mount Shasta. This case study highlights the value of investments in diverse observational assets and the importance of continued support and synthesis of these networks to characterize climatological context and advance understanding of processes modulating extreme weather.
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Perennial streamflow is limited and only exists in higher-altitude reaches of small mountain streams in both basins. Groundwater is in unconsolidated basin-fill aquifers and bedrock mountain aquifers. Groundwater in Pine and Wah Wah Valleys is being targeted for large-scale groundwater extraction and export to provide municipal supply to the growing population in Iron County, Utah. Concern about declining groundwater levels and spring flows from proposed groundwater withdrawals has increased interest in an improved understanding of the groundwater system. Previous studies have indicated that an average of 28,000 acre-feet per year of recharge occurs mostly as infiltration of precipitation in high-altitude regions in the two basins. Groundwater discharge in the mountain hydrologic systems was estimated to average 8,500 acre-feet per year and is assumed to be consumed before subsequently recharging the valley basin-fill aquifers. Subsurface groundwater outflow moves from basin-fill aquifers in Pine and Wah Wah Valleys northward to adjacent regional basins and was estimated to average 19,500 acre-feet per year.
An updated water-level map for the basin-fill aquifers in Pine and Wah Wah Valleys indicates that groundwater moves northward along the lengths of both valleys toward adjacent basins. Measured depths to water range from about 210 to 750 feet below land surface in Wah Wah Valley, and from about 300 to 620 feet below land surface in Pine Valley. Long-term water levels at seven wells completed in the basin-fill aquifers of Pine and Wah Wah Valleys with records spanning more than 40 years are generally stable with observed fluctuations of less than 5 feet. Observed discharge from two springs monitored between 2013 and 2016 also is generally stable.
Groundwater leaving Pine and Wah Wah Valleys through the subsurface moves northward, converges with regional groundwater flow, and discharges by evapotranspiration at regional groundwater discharge areas, likely Tule Valley, Utah. In this study, basin-scale groundwater discharge was estimated by (1) mapping the groundwater discharge areas in each valley; (2) evaluating the 2005–11 summer multispectral satellite images against the Basin and Range carbonate-rock aquifer system study evapotranspiration measurements to select scenes broadly representative of average conditions in the study area and partitioning the groundwater discharge areas into evapotranspiration units using the selected satellite images and field reconnaissance; and (3) scaling evapotranspiration to the evapotranspiration units using evapotranspiration-rate estimates from several studies in the Great Basin. The resulting updated estimates of average annual groundwater evapotranspiration in the Tule Valley and Sevier Lake groundwater discharge areas were 35,000 and 10,500 acre-feet per year, respectively, with a likely uncertainty of plus or minus 35 percent.
Groundwater samples from 13 sites in Pine Valley and 11 sites in Wah Wah Valley were analyzed for major ions and nutrients, to characterize geochemistry and water quality. Groundwater samples also were analyzed for the stable isotopes of oxygen, hydrogen, and carbon, the radioactive isotopes of carbon and hydrogen, and dissolved noble gases including helium-3, helium-4, neon, argon, krypton and xenon. Groundwater sampling sites included 12 wells and 12 springs. Carbon-14 and tritium/helium groundwater age dating indicate that groundwater in the basin-fill aquifers is typically thousands to tens of thousands of years older than groundwater in the shallow mountain aquifers. Dissolved-solids concentrations are lower and noble-gas temperatures are warmer in the valley wells compared to almost all groundwater sampled from wells and springs in the surrounding mountains. These results indicate a hydraulic discontinuity between the mountain and valley aquifers throughout much of the study area, and that much of the valley recharge is not derived from direct infiltration of precipitation in the mountains.
Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000
The U.S. Geological Survey Kansas Water Science Center, in cooperation with Federal, State, and local agencies, maintains a long-term network of hydrologic monitoring stations in the State of Kansas. These include a network of 217 real-time streamgages and 12 real-time reservoir-level monitoring stations in water year 2019. The data and associated analyses from the streamgages and monitoring stations provide a unique overview of hydrologic conditions and help improve the understanding of Kansas’ water resources. Annual assessments of hydrologic conditions are made by comparing statistical analyses of current and past water year data for the period of record. Long-term monitoring of hydrologic conditions in Kansas provides imperative information for many uses including managing water resources and protecting human life and property and promoting agricultural practices, industrial activities, operation of reservoirs, development of infrastructure, ecological assessments, and recreational purposes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203029","usgsCitation":"Davis, C., 2020, Hydrologic conditions in Kansas, Water year 2019: U.S. Geological Survey Fact Sheet 2020–3029, 6 p., https://doi.org/10.3133/fs20203029.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-117275","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":376376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3029/fs20203029.pdf","text":"Report","size":"5.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"fs 2020–3029"},{"id":376375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3029/coverthb2.jpg"}],"country":"United 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\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Dr.
Lawrence, Kansas 66049
Urban development has been observed to lead to variable magnitudes of change for stormflow volume and directions of baseflow change across cities. This work examines temporal streamflow trends across the flow duration curve in 53 watersheds during periods of peak urban development, which ranged from 1939 to 2016. We used U.S. Geological Survey streamgage records combined with pre‐development and urbanization characteristics to identify 20 years for analysis in each urbanizing watershed. Each urbanizing gage was paired with a nearby reference gage representing climatic trends over the same time period. Results indicated that urbanization, as measured by housing density, did not homogeneously alter the flow duration curve. Urbanization led to widely variable trends in low flow, where half of the urbanizing gages had increasing flow at the 10th non‐exceedance percentile, and the other half had declining low flow. High flows generally increased in streams as the area urbanized. The largest increases in high flows were in streams in semi‐arid and arid areas. The largest urban flow changes had transformations in wastewater infrastructure, water supply infrastructure, and flood control facilities. Isolating flow changes due to urbanization from those of reference sites will serve to better identify and manage synergistic effects of urban development and climate change on flooding and water availability.
Predictions of post‐wildfire flooding and debris flows are needed, typically with short lead times. Measurements of soil‐hydraulic properties necessary for model parameterization are, however, seldom available. This study quantified soil‐hydraulic properties, soil‐water retention, and selected soil physical properties within the perimeter of the 2017 Thomas Fire in California. The Thomas Fire burn scar produced catastrophic debris flows in January 2018, highlighting the need for improved prediction capability. Soil‐hydraulic properties were also indirectly estimated using relations tied to soil‐water retention. These measurements and estimates are examined in the context of parameterizing post‐wildfire hydrologic models. Tension infiltrometer measurements showed significant decreases (p < .05) in field‐saturated hydraulic conductivity (Kfs) and sorptivity (S) in burned areas relative to unburned areas. Wildfire effects on soil water‐retention were dominated by significant decreases in saturated soil‐water content (θS). The van Genuchten parameters α, N, and residual water content did not show significant wildfire effects. The impacts of the wildfire on hydraulic and physical soil properties were greatest in the top 1 cm, emphasizing that measurements of post‐fire soil properties should focus on the near‐surface. Reductions in Kfs, θs, and soil‐water retention in burned soils were attributed to fire‐induced decreases in soil structure evidenced by increases in dry bulk density. Sorptivity reductions in burned soils were attributed to increases in soil‐water repellency. Rapid post‐fire assessments of flash flood and debris flow hazards using physically‐based hydrologic models are facilitated by similarities between Kfs, S, and the Green–Ampt wetting front potential (ψf) with measurements at other southern CA burned sites. We suggest that ratios of burned to unburned Kfs (0.37), S (0.36), and ψf (0.66) could be used to scale unburned values for model parameterization. Alternatively, typical burned values (Kfs = 20 mm hr−1; S = 6 mm hr−0.5; ψf = 1.6 mm) could be used for model parameterization.
The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, investigated the effects of stormwater runoff from bridge decks on stream water quality conditions in South Carolina. The investigation assessed 5 bridges in 3 physiographic provinces in South Carolina (Piedmont, Upper Coastal Plain, and Lower Coast Plain) that had a range of bridge, traffic, and hydrologic characteristics. The five selected South Carolina bridge sites (coincident with U.S. Geological Survey stations) and corresponding highways were Lynches River at Effingham (station 02132000; U.S. Highway 52), North Fork Edisto River at Orangeburg (station 02173500; U.S. Highway 301), Turkey Creek above Huger (station 02172035; South Carolina Highway 41), South Fork Edisto River near Denmark (station 02173000; U.S. Highway 321), and Fishing Creek at Highway 5 below York (station 021473415; South Carolina Highway 5). Bridge decks at the selected sites used open chutes, scuppers, and downspouts to drain stormwater directly into the receiving water at evenly spaced intervals.
Stream water, sediment, and biological samples were collected and analyzed for a variety of constituents to evaluate the stream conditions for this study. Five to six stream samples were collected at transects upstream and downstream from each selected bridge site using the equal-width-increment technique during observable stormwater runoff. Routine samples of the receiving waters were collected 12 to 14 times at the upstream transect during nonstorm conditions. Samples were analyzed for physical properties, suspended sediment, nutrients, major ions, trace metals, polycyclic aromatic hydrocarbons, and Escherichia coli. Bridge-deck sediment and streambed sediment at upstream and downstream transects were collected once at each bridge site and analyzed for metals and semivolatile organic compounds that include polycyclic aromatic hydrocarbons. Benthic macroinvertebrate community surveys were conducted once using Hester-Dendy multiplate artificial substrate samplers deployed at multiple upstream and downstream transects concurrently.
Statistical analysis of the water-quality data determined that stormwater runoff from bridges did not significantly degrade physical properties, nor nutrient, trace-metal, Escherichia coli, and suspended-sediment concentrations at the selected sites beyond the variability at the upstream transect (no bridge influence) during the study period. During storm sampling at the bridge sites, water-quality conditions were statistically similar upstream and downstream from each bridge, except for greater turbidity, total nitrogen, and total organic nitrogen plus ammonia concentrations found downstream from the bridge site on Fishing Creek; higher total chromium concentrations detected downstream from the bridge site on Turkey Creek; and increased Escherichia coli concentrations found downstream from the bridge site on the North Fork Edisto River. Total recoverable lead, cadmium, and copper concentrations were the only trace metals that periodically exceeded the South Carolina Department of Health and Environmental Control freshwater aquatic-life criteria at some bridge sites (lead, copper, and cadmium in Turkey Creek; cadmium and lead in Fishing Creek; lead in the South Fork Edisto River and Lynches River), but the exceedances occurred more frequently during routine sampling upstream from the bridge sites than during storm sampling at upstream and downstream transects. In general, stormwater runoff from the bridge decks did not seem to be the major source of metal enrichment in receiving waters during the study period. North Fork and South Fork Edisto Rivers and Turkey Creek had only one storm sample that exceeded South Carolina Department of Health and Environmental Control recreational criterion for Escherichia coli at both the upstream and downstream locations, while Fishing Creek had more frequent exceedances. Polycyclic aromatic hydrocarbons were detected infrequently in the stream samples.
In general, sediment trace-metal concentrations were below the threshold and probable effect concentration at all bridge sites, except for the chromium concentration (45.1 milligrams per kilogram) detected upstream from the bridge site on Fishing Creek that exceeded the threshold effect concentration of 43.4 milligrams per kilogram. Based on enrichment ratios less than 1.5, bridge-deck runoff did not seem to be affecting trace-metal accumulation in the streambed sediment downstream from the bridge sites, except for lead at the bridge site on the Lynches River and manganese at the bridge site on Fishing Creek.
Individual polycyclic aromatic compound concentrations and the sum of 18 compounds did not exceed any threshold and probable effect concentrations, indicating polycyclic aromatic hydrocarbon concentrations in the streambed sediment at downstream and upstream transects were not likely to affect the health of benthic macroinvertebrate communities. Although the cumulative polycyclic aromatic hydrocarbon concentrations in downstream sediment at the sites on Turkey and Fishing Creeks were well below the threshold effect concentration of 1,610 micrograms per kilogram, the 3- to 100-fold increase in downstream concentrations indicated a strong probability of a bridge-deck runoff source.
Overall, benthic macroinvertebrate community health downstream from the bridge sites did not seem to be affected by bridge-deck runoff based on several multivariate analyses that indicated statistically similar benthic macroinvertebrate communities at upstream and downstream transects. Of the five bridge sites in this study, the site on Turkey Creek seemed to have the least healthy benthic macroinvertebrate communities because of the lowest Ephemeroptera, Plecoptera, and Trichoptera spp. (mayflies, stoneflies, and caddisflies, respectively) taxa, species richness, and diversity; and the highest biotic indices, indicative of poorer ecological health, at upstream and downstream transects. This ecological finding was not unexpected because of seasonal periods of negligible flow when dissolved-oxygen concentrations fell below 4 milligrams per liter during the study period. Of the five bridge sites in this study, the site on the South Fork Edisto River seemed to have healthier benthic macroinvertebrate communities because of the greater mean Ephemeroptera, Plecoptera, and Trichoptera spp. taxa; and lower mean biotic indices at upstream and downstream transects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205046","collaboration":"Prepared in cooperation with South Carolina Department of Transportation","usgsCitation":"Journey, C.A., Petkewich, M.D., Conlon, K.J., Caldwell, A.W., Clark, J.M., Riley, J.W., and Bradley, P.M., 2020, Effects of stormwater runoff from selected bridge decks on conditions of water, sediment, and biological quality in receiving waters in South Carolina, 2013 to 2018: U.S. Geological Survey Scientific Investigations Report 2020–5046, 101 p., https://doi.org/10.3133/sir20205046.","productDescription":"xii, 101 p.","numberOfPages":"101","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-099513","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":376048,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5046/sir20205046_appendixes.xlsx","text":"Appendixes 1-3","size":"312 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":376047,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5046/sir20205046.pdf","text":"Report","size":"5.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5046"},{"id":376046,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FXSV2Y","text":"USGS data release","linkHelpText":"Water-, Sediment-, and Biological-Quality Data for Waters Receiving Runoff from Five Bridges in South Carolina, 2013 to 2018"},{"id":376045,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5046/coverthb.jpg"},{"id":376051,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5046/sir20205046_appendixes_csv.zip","text":"Appendixes 1-3 (CSV)","size":"34.5 KB","linkFileType":{"id":6,"text":"zip"}}],"contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
While the physical processes governing groundwater flow are well understood, and the computational resources now exist for solving the governing equations in three dimensions over continental-scale domains, there remains substantial uncertainty about the subsurface distribution of the properties that control groundwater flow and transport for much of the contiguous United States (CONUS). The transmissivity of the shallow subsurface is a key parameter for the simulation of water table position, shallow groundwater flow, and base-flow discharge, but is not well-characterized at large regional to continental scales. We used a process-based inversion of CONUS-extent groundwater information to generate national data sets of (a) the transmissivity of the shallow groundwater system, (b) the depth to the water table, (c) groundwater discharge as base-flow, and (d) long-term average water content in the unsaturated zone. CONUS-extent coverage was developed in the form of 75 subdomain models, with the spatial distribution of long-term average transmissivity for each subdomain model calibrated against water-levels derived from U.S. Geological Survey (USGS) observation wells, NHDPlusV2 first-order perennial streams, and National Wetlands Inventory (NWI) freshwater wetlands. Estimated transmissivities were lower in the western CONUS than the eastern CONUS, and across the CONUS both transmissivity and depth to water correlate with recharge, elevation, and topographic slope. These generated data sets provide spatially distributed, long-term average estimates of subsurface properties and hydrological states that we anticipate will complement other environmental modeling efforts as explanatory variables, boundary conditions, or transport pathways.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019WR026724","usgsCitation":"Zell, W.O., and Sanford, W.E., 2020, Calibrated simulation of the long-term average surficial groundwater system and derived spatial distributions of its characteristics for the contiguous United States: Water Resources Research, v. 56, no. 8, e2019WR026724, 16 p.; Data Release, https://doi.org/10.1029/2019WR026724.","productDescription":"e2019WR026724, 16 p.; Data Release","ipdsId":"IP-117925","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":436888,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91LFFN1","text":"USGS data release","linkHelpText":"MODFLOW 6 models used to simulate the long-term average surficial groundwater system for the contiguous United 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0000-0002-8782-6627","orcid":"https://orcid.org/0000-0002-8782-6627","contributorId":339721,"corporation":false,"usgs":true,"family":"Zell","given":"Wesley","email":"","middleInitial":"O.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":904936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70212531,"text":"70212531 - 2020 - Deep Learning as a tool to forecast hydrologic response for landslide-prone hillslopes","interactions":[],"lastModifiedDate":"2020-08-19T13:25:09.670826","indexId":"70212531","displayToPublicDate":"2020-07-08T08:19:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Deep Learning as a tool to forecast hydrologic response for landslide-prone hillslopes","docAbstract":"Empirical thresholds for landslide warning systems have benefitted from the incorporation of soil‐hydrologic monitoring data, but the mechanistic basis for their predictive capabilities is limited. Although physically based hydrologic models can accurately simulate changes in soil moisture and pore pressure that promote landslides, their utility is restricted by high computational costs and nonunique parameterization issues. We construct a deep learning model using soil moisture, pore pressure, and rainfall monitoring data acquired from landslide‐prone hillslopes in Oregon, USA, to predict the timing and magnitude of hydrologic response at multiple soil depths for 36‐hr intervals. We find that observation records as short as 6 months are sufficient for accurate predictions, and our model captures hydrologic response for high‐intensity rainfall events even when those storm types are excluded from model training. We conclude that machine learning can provide an accurate and computationally efficient alternative to empirical methods or physical modeling for landslide hazard warning.
Assessments of groundwater and surface water budgets at a large scale, such as the contiguous United States, often separately analyze the complex dynamics linking the surface and subsurface categories of water resources. These dynamics include recharge and groundwater contributions to streamflow. The time-varying simulation of these complex hydrologic dynamics, across large spatial and temporal scales, remains a scientific challenge due to the complexity of the processes and data availability. In this study, groundwater fluxes and surface hydrologic processes are simulated across the contiguous US for 1950-2010. The simulation estimates the monthly water budget components, such as groundwater recharge, surface runoff, and evapotranspiration; streamflow in major rivers is routed while accounting for groundwater exchange. Human impacts are included through groundwater pumping, and climate variability is included, including variability in precipitation, temperature and potential evapotranspiration. The simulated groundwater level and river discharge have strong correlation with USGS observation wells and streamflow gages, with R2 values of 0.992 and 0.946, respectively. The simulated evapotranspiration is compared with three other published estimation methods, showing that it is able to capture the magnitude and seasonality of evapotranspiration over the Mississippi River basin. As such, the model is able to reasonably simulate the surface and groundwater budgets over the US, allowing for questions of the relative importance of climate and human impacts to be explored in the future.
Coastal wetlands are among the most productive habitats on Earth and sequester globally significant amounts of atmospheric carbon (C). Extreme rates of soil C accumulation are widely assumed to reflect efficient C storage. Yet the fraction of wetland C lost via hydrologic export has not been directly quantified, since comprehensive budgets including direct estimates of lateral C loss are lacking. We present a complete net ecosystem C budget (NECB), demonstrating that lateral losses of C are a major component of the NECB for the largest stable brackish tidal marsh on the U.S. Pacific coast. Mean annual net ecosystem exchange of CO2 with the atmosphere (NEE = −185 g C m2 year−1, negative NEE denoting ecosystem uptake) was compared to long-term soil C burial (87–110 g C m2 year−1), suggesting only 47–59% of fixed atmospheric C accumulates in soils. Consistently, direct monitoring in 2017–2018 showed NEE of −255 g C m−2 year−1, and hydrologic export of 105 g C m−2 year−1 (59% of NEE remaining on site). Despite their high C sequestration capacity, lateral losses from coastal wetlands are typically a larger fraction of the NECB when compared to other terrestrial ecosystems. Loss of inorganic C (the least measured NECB term) was 91% of hydrologic export and may be the most important term limiting C sequestration. The high productivity of coastal wetlands thus serves a dual function of C burial and estuarine export, and the multiple fates of fixed C must be considered when evaluating wetland capacity for C sequestration.
There are many ways to quantify fish movement through shallow‐water habitats, but most noninvasive methods (e.g., visual counts) are not effective in turbid coastal wetland waters of the Great Lakes. Dual‐frequency identification sonar (DIDSON) technology (Sound Metrics) offers a noninvasive, hydroacoustic‐based approach to characterize fish movement in wetlands and other habitats by collecting highly detailed fish movement data regardless of light and water quality conditions. High‐resolution data can be analyzed to estimate fish movement in areas where visual observations are difficult. However, enumerating a complex mix of fish sizes by manually counting fish visible in echogram files requires training and is very time consuming. Therefore, four counting techniques were tested to estimate fish abundance from DIDSON echograms that were collected at a hydrologically reconnected coastal wetland in the Great Lakes. Briefly, the four counting methods were (1) manually viewing the entire length of the echogram (full‐hour manual count), (2) manually viewing subsections of the echogram before generating fish estimates by per‐minute average (subsample manual count), (3) using Echoview automated software to generate automated estimates, and (4) using DIDSON viewer software to generate automated estimates. Over 800 echogram‐hours were recorded over a 9‐month period at an open‐flow water control structure connecting a coastal wetland to a tributary to Lake Erie. Commercial fish tracking software (Echoview) and custom software scripts from Milne Technologies were used to semi‐automate fish count estimates for a small subset of data. Semi‐automated software counts were compared to manual counts of identical data files to assess differences in accuracy, cost, processing time, and counter effort. Semi‐automated fish count estimates using Echoview and custom pre‐ and postprocessing software scripts did not differ from baseline manual counts, suggesting that the semi‐automated count process could be a reliable tool to increase efficiency when processing large DIDSON data sets.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10451","usgsCitation":"Eggleston, M., Milne, S.W., Ramsay, M., and Kowalski, K., 2020, Improved fish counting method accurately quantifies high‐density fish movement in dual‐frequency identification sonar data files from a coastal wetland environment: North American Journal of Fisheries Management, v. 40, no. 4, p. 883-892, https://doi.org/10.1002/nafm.10451.","productDescription":"10 p.","startPage":"883","endPage":"892","ipdsId":"IP-108651","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":436893,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CMU62C","text":"USGS data release","linkHelpText":"DIDSON video collection of Coastal Lake Erie Wetland, Lucas Co, Ohio in 2011"},{"id":382918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.59277343749999,\n 40.78054143186033\n ],\n [\n -75.6298828125,\n 40.78054143186033\n ],\n [\n -75.6298828125,\n 49.55372551347579\n ],\n [\n -92.59277343749999,\n 49.55372551347579\n ],\n [\n -92.59277343749999,\n 40.78054143186033\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Eggleston, Michael R. 0000-0003-1068-3290","orcid":"https://orcid.org/0000-0003-1068-3290","contributorId":248759,"corporation":false,"usgs":true,"family":"Eggleston","given":"Michael R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milne, Scott W.","contributorId":248760,"corporation":false,"usgs":false,"family":"Milne","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":40886,"text":"Milne Technologies","active":true,"usgs":false}],"preferred":false,"id":809798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsay, Maxwell","contributorId":248761,"corporation":false,"usgs":false,"family":"Ramsay","given":"Maxwell","email":"","affiliations":[],"preferred":false,"id":809799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809800,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211541,"text":"70211541 - 2020 - Hydrologic modeling to examine the influence of the forestry reclamation approach and climate change on mineland hydrology","interactions":[],"lastModifiedDate":"2020-07-30T15:25:29.367702","indexId":"70211541","displayToPublicDate":"2020-07-05T10:18:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic modeling to examine the influence of the forestry reclamation approach and climate change on mineland hydrology","docAbstract":"Forests in the Appalachian region of the U.S. are threatened by a variety of short- and long-term pressures, including climate change, invasive species, and resource extraction. Surface mining for coal is one of the most important drivers of land-use change in the region, reducing native forest cover, causing forest fragmentation, eliminating intact soil, and affecting water resources. The Forestry Reclamation Approach (FRA) has been demonstrated as a successful best practice for restoring forests on mine-impacted landscapes, but little information exists on how the practice will affect hydrologic processes. A study was initiated to examine soil-water movement, as in-situ saturated hydraulic conductivity (Ksat), combined with soil porosity to quantify the potential influence on streamflow of reclaimed mines relative to an unmined, forested control site in eastern Kentucky. We compared different reclamation techniques and time since reclamation to determine the extent to which hydrologic function can be restored. We also simulated evapotranspiration at the watershed scale as a function of reclamation technique for both historical and projected (2050) climate. Results indicate that conventional grassland reclamation critically changes how soil water transitions to streamflow, primarily due to Ksat variability that exceeds that measured for intact and FRA soils. Sites reclaimed using FRA exhibited a soil-water environment that was more similar to the unmined control. However, all reclaimed mine soils were thinner, retained and stored less soil water, and thus could provide less plant-available water during the growing season. The plant-available water stored in reclaimed landscapes may not be sufficient to support forest health and this is exacerbated by projected climate conditions. However, soil development under a combination of FRA techniques has the potential to mitigate this limitation.
The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation’s greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize candidate basins for this monitoring investment to ensure that, as a group, the 10 basins will support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC04) with some of the smaller HUC04s being combined; median candidate-basin area is 46,600 km2. Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Ten geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were selected to rank candidate basins within each of the 18 hydrologic regions. The two highest ranking candidate basins in each of the 18 regions were identified as finalists for selection as “Integrated Water Science Basins”; final selection will consider input from a variety of stakeholders. The regional framework, with only one basin selected per region, ensures that as a group, the basins represent the range in major drivers of the hydrologic cycle. Ranking within each region, primarily based on anthropogenic stressors of water resources, ensures that settings representing important water-resource challenges for the nation will be studied.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-020-08403-1","usgsCitation":"Van Metre, P.C., Qi, S.L., Deacon, J.R., Dieter, C., Driscoll, J.M., Fienen, M.N., Kenney, T.A., Lambert, P.M., Lesmes, D.P., Mason, C., Mueller-Solger, A., Musgrove, M., Painter, J.A., Rosenberry, D.O., Sprague, L.A., Tesoriero, A.J., Windham-Myers, L., and Wolock, D.M., 2020, Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey: Environmental Modeling & Assessment, v. 192, 458, 17 p., https://doi.org/10.1007/s10661-020-08403-1.","productDescription":"458, 17 p.","ipdsId":"IP-114496","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456145,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-020-08403-1","text":"Publisher Index Page"},{"id":436898,"rank":0,"type":{"id":30,"text":"Data 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We evaluated measures of invertebrate species richness, water quality, and contaminant uptake by salamanders to determine how springs and their inhabitants were being affected by urban growth and changing land-use patterns. The number of environmental contaminants present and concentrations of contaminants increased in both water and salamander tissues with increasing age of the developments (i.e., years postconstruction) and increasing levels of impervious cover (e.g., roads) in urban watersheds compared with nondeveloped sites. We conclude that urbanization and associated increases in pollutant loading in watersheds can result in a loss of spring biodiversity and the accumulation of persistent and potentially toxic pollutants in salamanders. Although we detected generally low levels of pollutants, the altered water quality and invertebrate composition observed at springs, coupled with the changing hydrology and chronic contaminant exposure inherent in urban landscapes, is cause for concern, with potential implications for the long-term health, survival, and recovery of salamanders.
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A wildfire near Boulder, Colorado that burned a forested watershed recovering from mining disturbance that occurred 80-160 years ago allowed us to 1) assess arsenic and metal contamination in streams draining the burned area for a five-year period after the wildfire and 2) determine the fire-affected hydrologic drivers that convey arsenic and metals to surface water. Most metal concentrations were low in the circumneutral waters draining the burned area. Water and sediment collected from streams downstream of the burned area had elevated arsenic concentrations during and after post-fire storms. Mining-related deposits were the main source of arsenic to streams. An increased proportion of overland flow relative to infiltration after the fire mobilized arsenic- and metal- rich surface deposits and wildfire ash into streams within and downstream of the burned area. The deposition of this sediment into stream channels resulted in the remobilization of arsenic for the five-year post-fire study period. It is also possible that enhanced subsurface flow after the fire increased contact of water with arsenic-bearing minerals exposed in underground mine workings. Other studies have reported that wildfire ash can be an important source of arsenic and metals to surface waters, but wildfire ash was not an important source of arsenic in this study. Predicted increases in frequency, size, and intensity of wildfires in the western U.S., a region with widely dispersed historical mines, suggest that the intersection of legacy mining and post-wildfire hydrologic response poses an increasing risk for water supplies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.140635","usgsCitation":"Murphy, S.F., McCleskey, R., Martin, D.A., Holloway, J.M., and Writer, J., 2020, Wildfire-driven changes in hydrology mobilize arsenic and metals from legacy mine waste: Science of the Total Environment, v. 743, 140635, 15 p., https://doi.org/10.1016/j.scitotenv.2020.140635.","productDescription":"140635, 15 p.","ipdsId":"IP-118726","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456160,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.140635","text":"Publisher Index Page"},{"id":436899,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P941BIYS","text":"USGS data release","linkHelpText":"Chemistry of water, stream sediment, wildfire ash, soil, dust, and mine waste for Fourmile Creek Watershed, Colorado, 2010-2019"},{"id":376298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Boulder","otherGeospatial":"Four Mile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.45948028564453,\n 39.98211859887411\n ],\n [\n -105.33416748046875,\n 39.98211859887411\n ],\n [\n -105.33416748046875,\n 40.04049503186035\n ],\n [\n -105.45948028564453,\n 40.04049503186035\n ],\n [\n -105.45948028564453,\n 39.98211859887411\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"743","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":792586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. 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