Opportunities for growth and survival of aquatic organisms are spatially and temporally variable as habitat conditions across watersheds respond to interacting climatic, geomorphic, and hydrologic conditions. As conservation efforts often focus on identifying and protecting critical habitats, it is important to understand how this spatial and temporal variation in habitat quality affects the production dynamics of populations. Here, we use microchemical records preserved in otoliths to reconstruct juvenile habitat‐use by sockeye salmon that survived to spawn in a single population on the Alaska Peninsula. Successful individuals demonstrated a diverse array of juvenile behavioral strategies both within and among years. Importantly, the dominant juvenile behavioral strategy used by successful individuals changed among years, suggesting shifts in the relative benefits of different rearing habitats. The growth benefits of remaining in a more productive rearing lake were greatest in warm years indicating environmental influence on relative habitat quality. However, we found no strong relationship between the amount of growth accumulated in the productive rearing lake and overall population productivity across years. These results highlight the dynamic nature of habitat conditions and the beneficial effect of maintaining connectivity between diverse habitats for population productivity. When short‐term studies are used to demonstrate the relative values of different habitats to species of conservation concern, there is a distinct risk of under‐valuing habitats that may be critically important under alternative environmental conditions. In particular, land‐use decisions that reduce the range of habitat options available to species may erode a population’s ability to withstand environmental change over the long term.
Soil respiration is a primary component of the terrestrial carbon cycle. However, predicting the response of soil respiration to climate change remains a challenge due to the complex interactions between environmental drivers, especially plant phenology, temperature, and soil moisture. In this study, we use a 1‐D diffusion‐reaction model to calculate depth‐resolved CO2 production rates from soil CO2 concentrations and surface efflux observations in a subalpine meadow in the East River watershed, CO. Modeled rates are compared to in situ soil temperature and moisture conditions and MODIS satellite enhanced vegetation index (EVI) representing plant phenology across three hydrologically distinct growing seasons from 2016–2018. While soil respiration correlated with temperature on diel timescales (p < 0.05), seasonal variability was dominated by soil moisture and plant phenology (p < 0.05). We observed significant respiration increases in response to precipitation events; however, magnitude and duration were significantly higher in 2017 than 2016 despite similar wetting characteristics. Based on MODIS EVI, we suggest that the respiration response to rainfall is controlled by plant phenology, which in turn reflects the capacity of plants to respond to precipitation via increased photosynthesis and autotrophic respiration, behavior that is not captured in typical soil respiration pulse models. Projected changes in montane climate such as earlier snowmelt and prolonged fore‐summer drought may decrease soil respiration fluxes by decreasing the overlap between peak productivity and the summer monsoon. Finally, we observed significant late season CO2 fluxes from the deep subsoil (>165 cm) that support growing evidence for the importance of subsoil processes in driving integrated respiration fluxes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JG005924","usgsCitation":"Winnick, M., Lawrence, C.R., McCormick, M., Druhan, J., and Maher, K., 2020, Soil respiration response to rainfall modulated by plant phenology in a montane meadow, East River, Colorado, USA: Journal of Geophysical Research Biogeosciences, v. 125, no. 10, e2020JG005924, 20 p., https://doi.org/10.1029/2020JG005924.","productDescription":"e2020JG005924, 20 p.","ipdsId":"IP-108485","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455072,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1664387","text":"External Repository"},{"id":381100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.061767578125,\n 38.50626606567193\n ],\n [\n -106.82968139648436,\n 38.50626606567193\n ],\n [\n -106.82968139648436,\n 38.922023851268925\n ],\n [\n -107.061767578125,\n 38.922023851268925\n ],\n [\n -107.061767578125,\n 38.50626606567193\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Winnick, Mathew","contributorId":245458,"corporation":false,"usgs":false,"family":"Winnick","given":"Mathew","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":806219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":806220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Maeve","contributorId":245459,"corporation":false,"usgs":false,"family":"McCormick","given":"Maeve","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Druhan, Jennifer","contributorId":245460,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":806222,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Kate","contributorId":245461,"corporation":false,"usgs":false,"family":"Maher","given":"Kate","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806223,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215189,"text":"70215189 - 2020 - A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data","interactions":[],"lastModifiedDate":"2020-10-29T15:15:46.334579","indexId":"70215189","displayToPublicDate":"2020-10-07T07:27:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data","docAbstract":"Evapotranspiration (ET) is needed in a range of applications in hydrology, climatology, ecology, and agriculture. Remote sensing-based estimation is the only viable and economical method for ET estimation over large areas. The current Landsat satellites provide images every 16 days limiting the ability to capture biophysical changes affecting ET. Thus, we explored the potential integration of Landsat 8 and Sentinel-2 data for estimating ET using a surface energy balance model. The results indicate the proposed Landsat-Sentinel data fusion approach substantially reduced relative errors from 48% to 10% on area-wide and from 49% to 17% on pixel-wide compared to linear interpolation between two Landsat images. The proposed approach had a better agreement with expected actual ET maps across high-vegetation conditions than in low-vegetation conditions. The finer temporal resolution and better accuracy of ET maps based on Landsat-Sentinel integration is of great importance in managing limited water resources.
Near-term extirpations of macroinvertebrates are predicted for mountain streams worldwide as a warming climate drives the recession of high-elevation ice and snow. However, hydrological sources likely vary in their resistance to climate change, and thus streams fed by more resistant sources could persist as climate refugia for imperiled biota. In 2015–2016, we measured habitat characteristics and quantified macroinvertebrate community structure along 6 alpine streams in the Teton Range, Wyoming, USA. Strong differences in habitat characteristics (e.g., temperature, bed stability, conductivity) confirmed 3 major stream sources: surface glaciers, perennial snowfields, and subterranean ice. Subterranean ice-fed streams—termed “icy seeps”—appear common in the Teton Range and elsewhere, yet are globally understudied. Midges in the family Chironomidae dominated our study sites, representing 78.6% of all specimens sampled, with nematodes, caddisflies (Neothremma), and mayflies (Epeorus) also common. At the community scale, glacier- and snowmelt-fed streams differed significantly in multivariate space, with icy-seep communities intermediate between them, incorporating components of both assemblages. Because the thermal environment of subterranean ice, including rock glaciers, is decoupled from large-scale climatic conditions, we predict that icy seeps will remain intact longer than streams fed by surface ice and snow. Furthermore, our results suggest that icy seeps are suitable habitat for many macroinvertebrates occupying streams fed by vulnerable hydrological sources. Thus, icy seeps may act as key climate refugia for mountain stream biodiversity, an idea in need of further investigation.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.080.0311","usgsCitation":"Tronstad, L., Hotaling, S., Giersch, J.J., Wilmot, O.J., and Finn, D.S., 2020, Headwaters fed by subterranean ice: Potential climate refugia for alpine stream communities?: Western North American Naturalist, v. 3, no. 80, p. 395-407, https://doi.org/10.3398/064.080.0311.","productDescription":"13 p.","startPage":"395","endPage":"407","ipdsId":"IP-110169","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":455125,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/788273","text":"External Repository"},{"id":386021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Grand Teton National Park, Jedediah Smith Wilderness","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.99349975585938,\n 43.4947753137023\n ],\n [\n -110.42633056640625,\n 43.4947753137023\n ],\n [\n -110.42633056640625,\n 44.12801374373221\n ],\n [\n -110.99349975585938,\n 44.12801374373221\n ],\n [\n -110.99349975585938,\n 43.4947753137023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"80","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tronstad, Lusha M.","contributorId":224819,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha M.","affiliations":[{"id":40947,"text":"Wyoming Natural Diversity Database, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":816646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hotaling, Scott 0000-0002-5965-0986","orcid":"https://orcid.org/0000-0002-5965-0986","contributorId":176860,"corporation":false,"usgs":false,"family":"Hotaling","given":"Scott","email":"","affiliations":[],"preferred":false,"id":816647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giersch, J. Joseph 0000-0001-7818-3941 jgiersch@usgs.gov","orcid":"https://orcid.org/0000-0001-7818-3941","contributorId":198074,"corporation":false,"usgs":true,"family":"Giersch","given":"J.","email":"jgiersch@usgs.gov","middleInitial":"Joseph","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":816648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilmot, Oliver J.","contributorId":258868,"corporation":false,"usgs":false,"family":"Wilmot","given":"Oliver","email":"","middleInitial":"J.","affiliations":[{"id":52320,"text":"Wyoming Natural Diversity Database, University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":816649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finn, Debra S.","contributorId":198312,"corporation":false,"usgs":false,"family":"Finn","given":"Debra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":816650,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215254,"text":"70215254 - 2020 - Linking mesoscale meteorology with extreme landscape response: Effects of narrow cold frontal rainbands (NCFR)","interactions":[],"lastModifiedDate":"2020-10-14T12:30:56.62952","indexId":"70215254","displayToPublicDate":"2020-10-04T07:23:39","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6454,"text":"Journal of Geophysical Research - Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Linking mesoscale meteorology with extreme landscape response: Effects of narrow cold frontal rainbands (NCFR)","docAbstract":"Landscapes evolve in response to prolonged and/or intense precipitation resulting from atmospheric processes at various spatial and temporal scales. Whereas synoptic (large‐scale) features (e.g., atmospheric rivers and hurricanes) govern regional‐scale hydrologic hazards such as widespread flooding, mesoscale features such as thunderstorms or squall lines are more likely to trigger localized geomorphic hazards such as landslides. Thus, to better understand relations between hydrometeorological drivers and landscape response, a knowledge of mesoscale meteorology and its impacts is needed. Here we investigate the extreme geomorphic response associated with one type of mesoscale meteorological feature, the narrow cold frontal rainband (NCFR). Resulting from low‐level convergence and shallow convection along a cold front, NCFRs are narrow bands of high‐intensity rainfall that occur in midlatitude areas of the world. Our study examines an NCFR impacting the Sierra Nevada foothills (California, USA) that initiated over 500 landslides, mobilized ~360,000 metric tons of sediment to the fluvial system (as much as 16 times the local annual sediment yield), and severely damaged local infrastructure and regional water transport facilities. Coupling geomorphological field investigations with meteorological analyses, we demonstrate that precipitation associated with the NCFR was both intense (maximum 15 min intensity of 70 mm/hr) and localized, resulting in a highly concentrated band of shallow landsliding. This meteorological phenomenon likely plays an important role in landscape evolution and hazard initiation. Other types of mesoscale meteorological features also occur globally and offer new avenues for understanding the effects of storms on landscapes.
The Hooskanaden landslide is a large (~600 m wide × 1,300 m long), deep (~30 – 45 m) slide located in southwestern Oregon. Since 1958, it has had five moderate/major movements that catastrophically damaged the intersecting U.S. Highway 101, along with persistent slow wet‐season movements and a long‐term accelerating trend due to coastal erosion. Multiple remote sensing approaches, borehole measurements, and hydrological observations have been integrated to interpret the motion behaviors of the slide. Pixel offset tracking of both Sentinel‐1 and Sentinel‐2 images was carried out to reconstruct the 3‐D displacement field of the 2019 major event, and the results agree well with field measurements. A 12‐year displacement history of the landslide from 2007 to 2019 has been retrieved by incorporating offsets from Light Detection and Ranging (LiDAR) digital elevation model (DEM) gradients and Interferometric Synthetic Aperture Radar (InSAR) processing of ALOS and Sentinel‐1 images. Comparisons with daily/hourly ground precipitation reveal that the motion dynamics are predominantly controlled by intensity and temporal pattern of rainfall. A new empirical threefold rainfall threshold was therefore proposed to forecast the dates for the moderate/major movements. This threshold relies upon antecedent water‐year and previous 3‐day and daily precipitation and was able to represent observed movement periods well. Adaptation of our threshold methodology could prove useful for other large, deep landslides for which temporal forecasting has long been generally intractable. The averaged characteristic hydraulic conductivity and diffusivity were estimated as 6.6 × 10−6 m/s and 6.6 × 10−4 m2/s, respectively, based on the time lags between rainfall pulses and slide accelerations. Hydrologic modeling using these parameters helps to explain the ability of the new rainfall threshold.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JF005640","usgsCitation":"Xu, Y., Lu, Z., Schulz, W.H., and Kim, J., 2020, Twelve-year dynamics and rainfall thresholds for alternating creep and rapid movement of the Hooskanaden landslide from integrating InSAR, pixel offset tracking, and borehole and hydrological measurements: JGR Earth Surface, e2020JF005640, 17 p., https://doi.org/10.1029/2020JF005640.","productDescription":"e2020JF005640, 17 p.","ipdsId":"IP-122021","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jf005640","text":"Publisher Index Page"},{"id":380683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Hooskanaden Landslide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.4146728515625,\n 42.09822241118974\n ],\n [\n -124.11392211914062,\n 42.09822241118974\n ],\n [\n -124.11392211914062,\n 42.2752765520868\n ],\n [\n -124.4146728515625,\n 42.2752765520868\n ],\n [\n -124.4146728515625,\n 42.09822241118974\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Y.","contributorId":245125,"corporation":false,"usgs":false,"family":"Xu","given":"Y.","affiliations":[{"id":49088,"text":"Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USA","active":true,"usgs":false}],"preferred":false,"id":805387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Z.","contributorId":199276,"corporation":false,"usgs":false,"family":"Lu","given":"Z.","affiliations":[],"preferred":false,"id":805388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":805389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim, J.","contributorId":245126,"corporation":false,"usgs":false,"family":"Kim","given":"J.","affiliations":[{"id":49088,"text":"Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USA","active":true,"usgs":false}],"preferred":false,"id":805390,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216471,"text":"70216471 - 2020 - Improved prediction of management-relevant groundwater discharge characteristics throughout river networks","interactions":[],"lastModifiedDate":"2020-11-20T13:56:50.942422","indexId":"70216471","displayToPublicDate":"2020-10-01T07:54:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Improved prediction of management-relevant groundwater discharge characteristics throughout river networks","docAbstract":"Groundwater discharge zones connect aquifers to surface water, generating baseflow and serving as ecosystem control points across aquatic ecosystems. The influence of groundwater discharge on surface flow connectivity, fate and transport of contaminants and nutrients, and thermal habitat depends strongly on hydrologic characteristics such as the spatial distribution, age, and depth of source groundwater flow paths. Groundwater models have the potential to predict spatial discharge characteristics within river networks, but models are often not evaluated against these critical characteristics and model equifinality with respect to discharge processes is a known challenge. We quantify discharge characteristics across a suite of groundwater models with commonly used frameworks and calibration data. We developed a base model (MODFLOW‐NWT) for a 1,570‐km2 watershed in the northeastern United States and varied the calibration data, control of river‐aquifer exchange directionality, and resolution. Most models (n = 11 of 12) fit similarly to calibration metrics, but patterns in discharge location, flow path depth, and subsurface travel time varied substantially. We found (1) a 15% difference in the percent of discharge going to first‐order streams, (2) threefold variations in flow path depth, and (3) sevenfold variations in the subsurface travel times among the models. We recalibrated three models using a synthetic discharge location data set. Calibration with discharge location data reduced differences in simulated discharge characteristics, suggesting an approach to improved equifinality based on widespread field‐based mapping of discharge zones. Our work quantifying variation across common modeling approaches is an important step toward characterizing and improving predictions of groundwater discharge characteristics.
The goal of this research was to examine the impacts of Grade Control Structure (GCS) installations at the Heard Scout Pueblo (HSP) study site in the City of Phoenix, Arizona, USA. The study site is around a high-use trail system and is comprised of eroded and incised channels that conduct high flows and associated sediments into a residential neighborhood downstream, a noted stormwater control problem. We established baseline conditions associated with rainfall/runoff response before structures were installed so we could have some data for comparison afterwards.
Innovative monitoring equipment, including video cameras and pressure transducers (to calculate discharge); digital terrain models, sediment samplers and sediment chains (to measure erosion and deposition); soil moisture sensors in monitoring wells (to document infiltration and potential recharge); and weather stations (to track temperature and relative humidity) were established and a small Unmanned Aircraft System (sUAS) survey was completed by July, 11, 2017, in time for the typical summer monsoon season which officially runs from June 15th to September 30th. Only one pre-GCS installation rain event incurred a significant flow event (October 13, 2018).
Natural Channel Design (NCD), a landscape restoration company with decades of experience, was hired through a competitive bid process to develop a novel layout of ~30 GCS installations (sills, modified one-rock dams (ORD), and plugs, as well as a modified Zuni-bowl). The American Conservation Experience (ACE) hand-built the structures based on these designs in the main channel from November 13, 2018 through December 1, 2018. ACE built another ten structures in locations adjacent to the channel from January 15 through January 18, 2019. NCD worked with the landscape forensics to identify a historic channel and reinstate it using GCS.
A surface-water model was also applied, using some of the baseline measurements (terrain and hydraulic conductivity) to track the flows of water and potential infiltration associated with rainfall events before GCS installation, to assist NCD in their design. The same model was applied using the installed GCS locations to simulate impacts of the structures on flow and infiltration. Our model was able to predict the slight reduction and delay in peak flows for small events and simulate infiltration, which was measured and occurred in the channel. Results demonstrated that structures could increase infiltration by ~15% over time. More data describing geomorphology and hydrology after repeated rainfall events will allow for increased analyses.
Innovative monitoring, including the large‐scale particle image velocimetry (LSPIV) were invaluable to this research. Given the arid-land location and added drought conditions, the water levels were not high enough to compute, even using the continuous slope-area method, so discharge was calculated solely using the LSPIV. The careful redundancy of data acquisition is extremely important when studying dryland hydrology.
Weather data indicated that the HSP GCS installations created roughly a three-degree microclimate cooling effect for at least two days following rainfall events, as compared with the untreated channel. The cooling was attributed to increased moisture, evaporation, and latent heat expulsion from the evaporation.
","language":"English","publisher":"Bureau of Reclamation","usgsCitation":"Tosline, D., Norman, L., Greimann, B.P., Cederberg, J., Huang, V., and Ruddell, B., 2020, Impacts of grade control structure installations on hydrology and sediment transport as an adaptive management strategy: Final Report ST-2017-1751-01, iv, 65 p.","productDescription":"iv, 65 p.","ipdsId":"IP-121918","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":382021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382013,"type":{"id":15,"text":"Index Page"},"url":"https://data.usbr.gov/catalog/4414/item/6298"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.09899902343749,\n 33.293803558346596\n ],\n [\n -111.9784927368164,\n 33.293803558346596\n ],\n [\n -111.9784927368164,\n 33.38529959859565\n ],\n [\n -112.09899902343749,\n 33.38529959859565\n ],\n [\n -112.09899902343749,\n 33.293803558346596\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tosline, Deborah","contributorId":247510,"corporation":false,"usgs":false,"family":"Tosline","given":"Deborah","affiliations":[{"id":49564,"text":"Reclamation, Hydrologist / Program Manager","active":true,"usgs":false}],"preferred":false,"id":807809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":807810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greimann, Blair P.","contributorId":247511,"corporation":false,"usgs":false,"family":"Greimann","given":"Blair","email":"","middleInitial":"P.","affiliations":[{"id":49565,"text":"Reclamation, Hydraulic Engineer","active":true,"usgs":false}],"preferred":false,"id":807811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cederberg, Jay 0000-0001-6649-7353","orcid":"https://orcid.org/0000-0001-6649-7353","contributorId":219724,"corporation":false,"usgs":true,"family":"Cederberg","given":"Jay","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807812,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Victor","contributorId":247512,"corporation":false,"usgs":false,"family":"Huang","given":"Victor","email":"","affiliations":[{"id":49565,"text":"Reclamation, Hydraulic Engineer","active":true,"usgs":false}],"preferred":false,"id":807813,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruddell, Benjamin L.","contributorId":247513,"corporation":false,"usgs":false,"family":"Ruddell","given":"Benjamin L.","affiliations":[{"id":49567,"text":"Northern Arizona University, Professor","active":true,"usgs":false}],"preferred":false,"id":807814,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222425,"text":"70222425 - 2020 - Mississippi Alluvial Valley Forest-breeding landbird population & quantitative habitat objectives","interactions":[],"lastModifiedDate":"2021-09-10T11:37:31.771137","indexId":"70222425","displayToPublicDate":"2020-09-30T09:04:28","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Mississippi Alluvial Valley Forest-breeding landbird population & quantitative habitat objectives","docAbstract":"The Mississippi Alluvial Valley (MAV) is a 9 million ha (22-million-acre) floodplain that supports a diverse and ecologically rich bottomland hardwood forest ecosystem – one of the most productive in North America. It extends from roughly Cape Girardeau, Missouri, to the Gulf of Mexico and features a mosaic of ridges, swales, meander belts, and backswamps. Small changes in elevation (<1 foot) in the MAV are associated with large shifts in hydrology, which in turn, strongly affect plant and animal community composition and structure. The resultant diversity contributes to a fertile and productive floodplain. General forest types in the MAV include: Oak-gum-cypress (41%), elm-ash-cottonwood (29%), oakhickory (17%), and the remainder is other forest types (Oswalt 2013). Within the oak-gum-cypress and elm-ash-cottonwood categories, sugarberry-hackberry-elm-green ash and sweetgum-Nuttall oak-willow oak forest types account for close to one-half of MAV bottomland forest acreage, while baldcypress-tupelo forests are about 16 percent (Oswalt 2013). Although we emphasize bottomland hardwood habitat and associated bird species, this planning effort includes analyses based upon all forest types within the MAV. Hence, the term ‘forest’ refers to all forest types in the MAV.
","language":"English","publisher":"Lower Mississippi Valley Joint Venture","usgsCitation":"Demarest, D.W., Elliott, B., Ford, R., Hanni, D., McKnight, S.K., Mini, A.E., Twedt, D.J., and Wilson, R., 2020, Mississippi Alluvial Valley Forest-breeding landbird population & quantitative habitat objectives, 14 p.","productDescription":"14 p.","ipdsId":"IP-120883","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":389001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389000,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.lmvjv.org/landbird-plans"}],"country":"United States","state":"Arkansas, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"lower Mississippi Alluvial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.615478515625,\n 37.38761749978395\n ],\n [\n -92.2412109375,\n 34.813803317113155\n ],\n [\n -92.35107421874999,\n 34.642247047768535\n ],\n [\n -92.48291015625,\n 34.225429015241396\n ],\n [\n -91.571044921875,\n 33.578014746143985\n ],\n [\n -91.790771484375,\n 31.952162238024975\n ],\n [\n -91.95556640625,\n 31.109388560814963\n ],\n [\n -91.966552734375,\n 30.600093873550072\n ],\n [\n -90.72509765625,\n 29.7453016622136\n ],\n [\n -89.725341796875,\n 29.439597566602902\n ],\n [\n -89.45068359374999,\n 29.81205076752506\n ],\n [\n -90.4833984375,\n 30.192618218499273\n ],\n [\n -91.219482421875,\n 31.12819929911196\n ],\n [\n -90.626220703125,\n 32.37996146435729\n ],\n [\n -90.50537109375,\n 33.8521697014074\n ],\n [\n -89.84619140625,\n 35.146862906756304\n ],\n [\n -89.05517578125,\n 36.48314061639213\n ],\n [\n -88.9892578125,\n 37.204081555898526\n ],\n [\n -89.615478515625,\n 37.38761749978395\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Demarest, Dean W.","contributorId":175184,"corporation":false,"usgs":false,"family":"Demarest","given":"Dean","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":820004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, Blaine","contributorId":261424,"corporation":false,"usgs":false,"family":"Elliott","given":"Blaine","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":820005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, Robert","contributorId":214858,"corporation":false,"usgs":false,"family":"Ford","given":"Robert","email":"","affiliations":[{"id":37063,"text":"U.S. Environmental Protection Agency, Cincinnati, OH","active":true,"usgs":false}],"preferred":false,"id":820006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanni, David","contributorId":261426,"corporation":false,"usgs":false,"family":"Hanni","given":"David","email":"","affiliations":[{"id":13408,"text":"Tennessee Wildlife Resources Agency","active":true,"usgs":false}],"preferred":false,"id":820007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKnight, S. Keith","contributorId":221729,"corporation":false,"usgs":false,"family":"McKnight","given":"S.","email":"","middleInitial":"Keith","affiliations":[{"id":40410,"text":"Lower Mississippi Valley Joint Venture","active":true,"usgs":false}],"preferred":false,"id":820008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mini, Anne E.","contributorId":261428,"corporation":false,"usgs":false,"family":"Mini","given":"Anne","email":"","middleInitial":"E.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":820009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":820010,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, R. Randy","contributorId":259210,"corporation":false,"usgs":false,"family":"Wilson","given":"R. Randy","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":820011,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70224335,"text":"70224335 - 2020 - Assessing plot-scale impacts of land use on overland flow generation in Central Panama","interactions":[],"lastModifiedDate":"2021-09-23T12:24:52.951151","indexId":"70224335","displayToPublicDate":"2020-09-30T07:22:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Assessing plot-scale impacts of land use on overland flow generation in Central Panama","docAbstract":"Land use in Panama has changed dramatically with ongoing deforestation and conversion to cropland and cattle pastures, potentially altering the soil properties that drive the hydrological processes of infiltration and overland flow. We compared plot-scale overland flow generation between hillslopes in forested and actively cattle-grazed watersheds in Central Panama. Soil physical and hydraulic properties, soil moisture and overland flow data were measured along hillslopes of each land-use type. Soil characteristics and rainfall data were input into a simple, 1-D representative model, HYDRUS-1D, to simulate overland flow that we used to make inferences about overland flow response at forest and pasture sites. Runoff ratios (overland flow/rainfall) were generally higher at the pasture site, although no overall trends were observed between rainfall characteristics and runoff ratios across the two land uses at the plot scale. Saturated hydraulic conductivity (Ks) and bulk density were different between the forest and pasture sites (p < 10−4). Simulating overland flow in HYDRUS-1D produced more outputs similar to the overland flow recorded at the pasture site than the forest site. Results from our study indicate that, at the plot scale, Hortonian overland flow is the main driver for overland flow generation at the pasture site during storms with high-rainfall totals. We infer that the combination of a leaf litter layer and the activation of shallow preferential flow paths resulting in shallow saturation-excess overland flow are likely the main drivers for plot scale overland flow generation at the forest site. Results from this study contribute to the broader understanding of the delivery of freshwater to streams, which will become increasingly important in the tropics considering freshwater resource scarcity and changing storm intensities.
The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011.
The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies.
Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205083","collaboration":"USGS Greater Everglades Priority Ecosystems Science ProgramDirector, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
We measured food availability and diet composition of juvenile salmonids over multiple years and seasons before and during the world’s largest dam removal on the Elwha River, Washington State. We conducted these measurements over three sediment-impacted sections (the estuary and two sections of the river downstream of each dam) and compared these to data collected from mainstem tributaries not directly affected by the massive amount of sediment released from the reservoirs. We found that sediment impacts from dam removal significantly reduced invertebrate prey availability, but juvenile salmon adjusted their foraging so that the amount of energy in diets was similar before and during dam removal. This general pattern was seen in both river and estuary habitats, although the mechanisms driving the change and the response differed between habitats. In the estuary, the dietary shifts were related to changes in invertebrate assemblages following a hydrological transition from brackish to freshwater caused by sediment deposition at the river’s mouth. The loss of brackish invertebrate species caused fish to increase piscivory and rely on new prey sources such as plankton. In the river, energy provided to fish by Ephemeroptera, Plecoptera, and Trichoptera taxa before dam removal was replaced first by terrestrial invertebrates, and then by sediment-tolerant taxa such as Chironomidae. The results of our study are consistent with many others that have shown sharp declines in invertebrate density during dam removal. Our study further shows how those changes can move through the food web and affect fish diet composition, selectivity, and energy availability. As we move further along the dam removal response trajectory, we hypothesize that food web complexity will continue to increase as annual sediment load now approaches natural background levels, anadromous fish have recolonized the majority of the watershed between and above the former dams, and revegetation and microhabitats continue to develop in the estuary.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0239198","usgsCitation":"Morley, S.A., Foley, M.M., Duda, J.J., Beirne, M.M., Paradis, R.L., Johnson, R.C., McHenry, M.L., Elofson, M., Sampson, E.M., McCoy, R.E., Stapleton, J., and Pess, G.R., 2020, Shifting food web structure during dam removal—Disturbance and recovery during a major restoration action: PLoS ONE, v. 15, no. 9, e0239198, 34 p., https://doi.org/10.1371/journal.pone.0239198.","productDescription":"e0239198, 34 p.","ipdsId":"IP-117389","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":455196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0239198","text":"Publisher Index Page"},{"id":378966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River, Olympic Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.64974975585938,\n 47.81960975604292\n ],\n [\n -123.38882446289061,\n 47.81960975604292\n ],\n [\n -123.38882446289061,\n 48.16333749877855\n ],\n [\n -123.64974975585938,\n 48.16333749877855\n ],\n [\n -123.64974975585938,\n 47.81960975604292\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Morley, Sarah A.","contributorId":148956,"corporation":false,"usgs":false,"family":"Morley","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":17601,"text":"NOAA Fisheries, Northwest Fisheries Science Center, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":800243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Melissa M 0000-0002-5832-6404","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":238117,"corporation":false,"usgs":false,"family":"Foley","given":"Melissa","email":"","middleInitial":"M","affiliations":[{"id":47699,"text":"San Francisco Estuary Institute, Richmond, CA","active":true,"usgs":false}],"preferred":false,"id":800244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":800245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beirne, Mathew M","contributorId":241958,"corporation":false,"usgs":false,"family":"Beirne","given":"Mathew","email":"","middleInitial":"M","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paradis, Rebecca L","contributorId":241960,"corporation":false,"usgs":false,"family":"Paradis","given":"Rebecca","email":"","middleInitial":"L","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":800248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McHenry, Michael L.","contributorId":39672,"corporation":false,"usgs":false,"family":"McHenry","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":800249,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Elofson, Mel","contributorId":241966,"corporation":false,"usgs":false,"family":"Elofson","given":"Mel","email":"","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800250,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sampson, Earnest M","contributorId":241968,"corporation":false,"usgs":false,"family":"Sampson","given":"Earnest","email":"","middleInitial":"M","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800251,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCoy, Randall E","contributorId":241971,"corporation":false,"usgs":false,"family":"McCoy","given":"Randall","email":"","middleInitial":"E","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800252,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stapleton, Justin","contributorId":241974,"corporation":false,"usgs":false,"family":"Stapleton","given":"Justin","email":"","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800253,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":800254,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70214530,"text":"70214530 - 2020 - Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","interactions":[],"lastModifiedDate":"2020-09-30T14:56:14.381095","indexId":"70214530","displayToPublicDate":"2020-09-26T09:49:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","docAbstract":"Hydrology is a critical driver controlling mangrove wetlands structural and functional attributes at different spatial and temporal scales. Yet, human activities have negatively affected hydrology, causing mangrove diebacks and coverage loss worldwide. In fact, the assessment of mangrove water budgets, impacted by natural and human disturbances, is limited due to a lack of long-term data and information that hinders our understanding of how changes in hydroperiod and salinity control mangrove productivity and spatial distribution. In this study, we implemented a mass balance-based hydrological model (RHYMAN) that explicitly considers groundwater discharge in the Shark River estuary (SRE, southwestern Everglades) located in a karstic geomorphic setting and influenced by regional hydrological restoration. We used long-term hydroperiod and porewater salinity (PWS) datasets obtained from 2004 to 2016 for model calibration and validation and to determine spatiotemporal variability in water levels and PWS at three riverine mangrove sites (downstream, SRS-6; midstream, SRS-5; upstream, SRS-4) along SRE. Model results agree with a distinct PWS pattern along the estuarine salinity gradient where the highest PWS occurs at SRS-6 (mean: 25, range: 22–30 ppt), followed by SRS-5 (17, 14–25 ppt) and SRS-4 (5, 3–13 ppt). A commensurate increase in PWS over a thirteen-year period indicates a long-term reduction in freshwater inflow coupled with sea-level rise (SLR). Increasing freshwater scenario simulation results show a significant reduction (17–27%) in PWS along the estuary in contrast with a high SLR scenario when salinity increases up to 1.1 to 2.5 times that of control values. Model results show that freshwater inflow and SLR are key drivers controlling mangrove wetlands PWS in this karstic coastal region. Given its relatively simple structure, this mass balance-based hydrological model could be used in other environmental settings to evaluate potential habitat and regime shifts due to changes in hydrology and PWS under regional hydrological restoration management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2020.109292","usgsCitation":"Zhao, X., Rivera-Monroy, V.H., Wang, H., Xue, Z., Tsai, C., Willson, C.S., Castañeda-Moya, E., and Twilley, R.R., 2020, Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate: Ecological Modelling, v. 436, 109292, 18 p., https://doi.org/10.1016/j.ecolmodel.2020.109292.","productDescription":"109292, 18 p.","ipdsId":"IP-117526","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.lsu.edu/civil_engineering_pubs/1184","text":"Publisher Index Page"},{"id":378913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.9085693359375,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 25.06072125231416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"436","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhao, Xiaochen","contributorId":219696,"corporation":false,"usgs":false,"family":"Zhao","given":"Xiaochen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":219641,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":799836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xue, Zuo 0000-0003-4018-0248","orcid":"https://orcid.org/0000-0003-4018-0248","contributorId":241655,"corporation":false,"usgs":false,"family":"Xue","given":"Zuo","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tsai, Cheng-Feng","contributorId":241949,"corporation":false,"usgs":false,"family":"Tsai","given":"Cheng-Feng","email":"","affiliations":[],"preferred":false,"id":799838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willson, C. S.","contributorId":90440,"corporation":false,"usgs":false,"family":"Willson","given":"C.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":799839,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Castañeda-Moya, E. 0000-0001-7759-4351","orcid":"https://orcid.org/0000-0001-7759-4351","contributorId":241657,"corporation":false,"usgs":false,"family":"Castañeda-Moya","given":"E.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":799840,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799841,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70214980,"text":"70214980 - 2020 - Predicting bird guilds using vegetation composition and structure on a wild and scenic river in Arizona","interactions":[],"lastModifiedDate":"2020-12-29T21:37:34.223766","indexId":"70214980","displayToPublicDate":"2020-09-25T09:03:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Predicting bird guilds using vegetation composition and structure on a wild and scenic river in Arizona","docAbstract":"Riparian areas are among the most ecologically diverse terrestrial ecosystems but make up <2% of landscape area in southwestern USA. Many species of resident and neotropical migratory birds utilize riparian habitats for breeding, foraging, and nesting. We quantified vegetation composition and structure to predict bird guilds on Wild and Scenic portions of the Verde River, Arizona. We grouped plant species into guilds based on similar functional traits to describe composition. We surveyed birds during the breeding and migrating season to determine abundance and categorized species into guilds using preferences of breeding habitat, foraging substrate, and nest placement. Riparian obligate and facultative breeding guilds were most common. Both vegetation composition and structure were useful predictors of birds. Vegetation structure was most complex in gallery riparian forest. Abundance of riparian-obligate birds in the breeding guild were positively associated with vegetation structure of dense, multi-canopy canopy and tall trees. Abundance of most bird guilds were positively associated with composition of tall trees (Populus fremontii, Salix gooddingii) and drought tolerant shrubs (Prosopis velutina, Celtis reticulata). Our findings show complex riparian habitat important to wildlife is created by both composition and structure of near-stream vegetation that is tied to hydrology and sensitive to flow change.
Stream fish survival and recruitment are products of a physicochemical environment that affects growth and provides refuge; yet, the drivers of spatiotemporal variation in juvenile fish abundance remain unclear. Understanding how physicochemical conditions drive spatial and temporal patterns in fish abundances provides insight into how conditions across stream networks influence fish population success, thereby providing direction to managers about the types and locations of conservation actions that would be most beneficial. Using snorkel and habitat surveys of 120 sites sampled from 2015 to 2017, we evaluated the multiscale relationships among physicochemical features, hydrology, and age-0 Smallmouth Bass (Micropterus dolomieu velox) abundance in relation to network spatial position. Abundance of age-0 bass was spatiotemporally variable in relation to a July streamflow–network position interaction, a pool depth–stream size interaction, and a stream temperature–network position interaction. High flows at the end of the nesting season were related to lower age-0 abundance, but this effect was dampened in stream reaches in close proximity to larger mainstems. In small streams, reaches with deeper pool habitat supported higher age-0 bass abundances, but this trend was not apparent in larger tributaries and mainstem systems. Generally, colder streams had lower age-0 Smallmouth Bass abundance, though this relationship was not apparent in reaches adjacent to larger streams that generally supported higher age-0 bass abundances. Conservation actions that (1) facilitate habitat connectivity within and among streams, (2) limit future anthropogenic practices that alter natural geomorphology by creating shallower stream channels, and (3) maintain adequate flow magnitude and timing to support channel complexity (e.g., deeper pools within smaller catchments) would be most beneficial to supporting rearing habitat for age-0 riverine Smallmouth Bass.
Effluent-dominated streams are becoming increasingly common in temperate regions and generate complex pharmaceutical mixture exposure conditions that may impact aquatic organisms via drug–drug interactions. Here, we quantified spatiotemporal pharmaceutical exposure concentrations and composition mixture dynamics during baseflow conditions at four sites in a temperate-region effluent-dominated stream (upstream, at, and progressively downstream from effluent discharge). Samples were analyzed monthly for 1 year for 109 pharmaceuticals/degradates using a comprehensive U.S. Geological Survey analytical method and biweekly for 2 years focused on 14 most common pharmaceuticals/degradates. We observed a strong chemical gradient with pharmaceuticals only sporadically detected upstream from the effluent. Seventy-four individual pharmaceuticals/degradates were detected, spanning 5 orders of magnitude from 0.28 to 13 500 ng/L, with 38 compounds detected in >50% of samples. “Biweekly” compounds represented 77 ± 8% of the overall pharmaceutical concentration. The antidiabetic drug metformin consistently had the highest concentration with limited in-stream attenuation. The antihistamine drug fexofenadine inputs were greater during warm- than cool-season conditions but also attenuated faster. Differential attenuation of individual pharmaceuticals (i.e., high = citalopram; low = metformin) contributed to complex mixture evolution along the stream reach. This research demonstrates that variable inputs over multiple years and differential in-stream attenuation of individual compounds generate evolving complex mixture exposure conditions for biota, with implications for interactive effects.
Hydrological and bioclimatic processes that lead to drought may stress plants and wildlife, restructure plant community type and architecture, increase monotypic stands and bare soils, facilitate the invasion of non‐native plant species and accelerate soil erosion. Our study focuses on the impact of a paucity of Colorado River surface flows from the United States (U.S.) to Mexico. We measured change in riparian plant greenness and water use over the past two decades using remotely sensed measurements of vegetation index (VI), evapotranspiration (ET), and a new annualized Phenology Assessment Metric (PAM) for ET. We measure these long‐term (2000‐2019) metrics and their short‐term (2014‐2019) response to an environmental, pulse flow in 2014, as prescribed under Minute 319 of the 1944 Water Treaty between the two nations. In subsequent years, small directed flows were provided to restoration areas under Minute 323. We use 250 m MODIS and 30 m Landsat imagery to evaluate three vegetation indices (NDVI, EVI, EVI2). We select EVI2 to parameterize an optical‐based ET algorithm and test the relationship between ET from Landsat and MODIS by regression approaches. Our analyses show significant decreases in VIs and ET for both the 20‐year and post‐pulse 5‐year periods. Over the last 20 years, EVI Landsat declined 34% (30% by EVIMODIS) and ETLandsat‐EVI declined 38% (27% by ETMODIS‐EVI), overall ca. 1.61 mmd‐1 or 476 mmyr‐1 drop in ET. Over the 5 years since the 2014 pulse flow, EVI Landsat declined 20% (13% by EVIMODIS) and ETLandsat‐EVI declined 23% (4% by ETMODIS‐EVI) with a 0.77 mmd‐1 or a 209 mmyr‐1 5‐year drop in ET. Data and change maps show the pulse flow contributed enough water to slow the rate of loss, but only for the very short‐term (1‐2 years). These findings are critically important as they suggest further deterioration of biodiversity, wildlife habitat and key ecosystem services due to anthropogenic diversions of water in the U.S. and Mexico and from land clearing, fires, and plant‐related drought which affect hydrological processes.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13911","usgsCitation":"Nagler, P.L., Barreto-Muñoz, A., Chavoshi Borujeni, S., Jarchow, C., Gómez‐Sapiens, M., Nouri, H., Herrmann, S.M., and Didan, K., 2020, Ecohydrological responses to surface flow across borders: Two decades of changes in vegetation greenness and water use in the riparian corridor of the Colorado River Delta: Hydrological Processes, v. 34, no. 25, p. 4851-4883, https://doi.org/10.1002/hyp.13911.","productDescription":"33 p.; Data Release","startPage":"4851","endPage":"4883","ipdsId":"IP-117414","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":378804,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":436784,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PGDJ1","text":"USGS data release","linkHelpText":"Colorado River Delta Project: A compilation of vegetation indices, phenology assessment metrics, estimates of evapotranspiration and change maps for seven reaches of the delta's 150 km region, for nearly the last two decades"}],"country":"Mexico, United States","otherGeospatial":"Colorado River delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.15869140624999,\n 31.606609719226917\n ],\n [\n -114.521484375,\n 31.606609719226917\n ],\n [\n -114.521484375,\n 32.76880048488168\n ],\n [\n -115.15869140624999,\n 32.76880048488168\n ],\n [\n -115.15869140624999,\n 31.606609719226917\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"25","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":799708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barreto-Muñoz, Armando","contributorId":239891,"corporation":false,"usgs":false,"family":"Barreto-Muñoz","given":"Armando","affiliations":[{"id":48028,"text":"University of Arizona, Biosystems Engineering, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":799709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chavoshi Borujeni, Sattar","contributorId":241612,"corporation":false,"usgs":false,"family":"Chavoshi Borujeni","given":"Sattar","email":"","affiliations":[{"id":48363,"text":"Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Centre, AREEO, Isfahan, Iran","active":true,"usgs":false}],"preferred":false,"id":799710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":799711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gómez‐Sapiens, Marth M.","contributorId":241615,"corporation":false,"usgs":false,"family":"Gómez‐Sapiens","given":"Marth M.","affiliations":[],"preferred":false,"id":799732,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nouri, Hamideh","contributorId":178847,"corporation":false,"usgs":false,"family":"Nouri","given":"Hamideh","affiliations":[],"preferred":false,"id":799733,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herrmann, Stefanie M. 0000-0002-4069-2019","orcid":"https://orcid.org/0000-0002-4069-2019","contributorId":20234,"corporation":false,"usgs":true,"family":"Herrmann","given":"Stefanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":799734,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":799735,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218272,"text":"70218272 - 2020 - Application of a new species-richness based flow ecology framework for assessing flow reduction effects on aquatic communities","interactions":[],"lastModifiedDate":"2021-02-23T13:33:50.365096","indexId":"70218272","displayToPublicDate":"2020-09-19T07:30:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Application of a new species-richness based flow ecology framework for assessing flow reduction effects on aquatic communities","docAbstract":"Water‐resources managers are challenged with maintaining a balance among beneficial uses throughout river networks and need robust means of assessing potential risks to aquatic life resulting from flow alterations. This study generated ecological limit functions from species‐streamflow relations to quantify potential fish richness response to flow alteration and compared results to currently accepted streamflow management guidelines. Modeled responses of absolute richness change were watershed specific and varied among sample sets derived from hydrologic unit classifications of different sizes (large HUC 6 basins to regional scale HUC 8). With a 20% flow reduction, 10% of HUC 8 predicted a richness decrease in one or more taxa. While absolute richness change was consistent across streams within a HUC, percent richness change was stream size dependent. Comparisons with Instream Flow Incremental Methodology habitat models predicted habitat loss greater than percent richness change; however, predictions for habitat and richness decreased similarly as stream size decreased. Watershed‐specific responses from flow reductions could allow water‐resources management decisions to be made locally based on the predicted richness change for certain sized streams. Quantitative results highlight the utility of a richness‐based framework for generating watershed‐specific risk assessments that validate and inform currently employed water‐resources management practices.
Water-quality conditions (including temperature) in the Willamette River and many of its adjacent off-channel features, such as alcoves and side channels, were monitored between river miles 67 (near Salem, Oregon) and 168 (near Eugene, Oregon) during the summers of 2015 and 2016. One or more parameters (water temperature, dissolved oxygen, pH, specific conductance, and [or] water depth) were continuously measured at sites in the main channel (9 sites in 2015; 5 sites in 2016) and select off-channel features (20 features in 2015; 22 features in 2016). This study was initiated in reaction to the unusually warm, dry weather and resulting low streamflows that occurred in the Pacific Northwest in 2015 and the need for flow managers to understand the effects of streamflow on water-quality conditions in off-channel features of the Willamette River. Field monitoring was focused on documenting water-quality conditions during low summer streamflows and during fluctuations in streamflow, including when side channels became alcoves and reconnected to become side channels again.
Water in the main channel of the Willamette River upstream from river mile 50 near Newberg typically is well mixed during summer, with warm water temperatures (greater than 18 degrees Celsius) and high dissolved-oxygen concentrations (often greater than 7.7 milligrams per liter). During low summer flows, a diverse suite of off-channel features exists adjacent to the main channel of the Willamette River. Despite temporal and spatial variability within individual features, comparison of continuous water-temperature data between the main channel and off-channel features indicated that some off-channel features were consistently cooler than the main channel, some were consistently warmer than the main channel, and others frequently fluctuated between warmer or cooler than the main channel. Site-specific characteristics including upstream connection, depth, and presence or absence of aquatic or riparian vegetation were factors that seemed to affect the water quality of a feature.
Results from this study showed a relation between the geomorphology, hydrology, ecology, and water quality of an off-channel feature. Data confirmed that many features that can be classified as cold-water refuges based on water-temperature standards also contained low concentrations of dissolved oxygen that may not be suitable for sensitive fish species. A simplified site classification scheme is proposed that links water-quality conditions in measured off-channel features with site-specific characteristics and summer streamflows. The site classification scheme was extended to create a theoretical process matrix that relates measured water-quality conditions to a list of the processes and site-specific characteristics that could create those conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205068","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Smith, C.D., Mangano, J.F., and Rounds, S.A., 2020, Temperature and water-quality diversity and the effects of surface-water connection in off-channel features of the Willamette River, Oregon, 2015–16: U.S. Geological Survey Scientific Investigations Report 2020–5068, 70 p., https://doi.org/10.3133/sir20205068.","productDescription":"Report: viii, 70 p.; 3 Data Releases","onlineOnly":"Y","ipdsId":"IP-102289","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":378475,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73T9FPK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Continuous temperature measurements to assess upstream connection of off-channel features of the middle and upper Willamette River, Oregon, summer, 2016"},{"id":378473,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ315D","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Point measurements of temperature and water quality in main-channel and off-channel features of the Willamette River, 2015 -16"},{"id":378472,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5068/sir20205068.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5068"},{"id":378471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5068/coverthb.jpg"},{"id":378474,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77M06DV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water surface elevations recorded by submerged water level loggers in off-channel features of the middle and upper Willamette River, Oregon, summer, 2016"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.46435546875,\n 44.133333\n ],\n [\n -122.43713378906249,\n 44.133333\n ],\n [\n -122.43713378906249,\n 45.216667\n ],\n [\n -123.46435546875,\n 45.216667\n ],\n [\n -123.46435546875,\n 44.133333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
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.
The Glen Canyon Group Aquifer (GCGA) is the sole source of public water supply for the city of Moab, Utah, a domestic and international tourist destination. Population and tourism growth are likely to target the GCGA for future water resources, but our analysis indicates that additional withdrawals would likely be sourced from groundwater storage and not be sustained by recharge. A quantitative estimate of groundwater discharge from the GCGA is problematic because the downgradient aquifer boundary is the Colorado River, and groundwater discharge to the river is very small compared to the river flow. A water budget based on a conceptual model of GCGA discharging into an adjacent alluvial Valley-Fill Aquifer (VFA) was reported by Sumsion (1971) and numerous subsequent studies have repeated and utilized this water budget. The GCGA contains stable isotopes, tritium, 3He/4He ratios, dissolved solids, and sulfate concentrations that contrast with the VFA, indicating it is instead recharged by local streams rather than from the GCGA. Water-budget calculations, based on: (1) measured spring discharge and streamflow gains, (2) horizontal gradients in VFA groundwater age, and (3) GCGA outcrop area vadose-zone pore waters are all less than previously thought. Using a lumped parameter model and 14C groundwater ages, we estimate recharge to the deeper GCGA (DGCGA) to be 4.2 ± 2.3 × 106 m3/yr, which is approximately equal to the measured discharge from wells and springs.
Groundwater provides nearly half of the Nation’s drinking water. As the Nation’s population grows, the importance of (and need for) high-quality drinking-water supplies increases. As part of a national-scale effort to assess groundwater quality in principal aquifers (PAs) that supply most of the groundwater used for public supply, the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Project staff sampled six principal aquifers in the western United States between 2013 and 2017: (1) the Basin and Range carbonate-rock aquifers, (2) Basin and Range basin-fill aquifers, (3) Rio Grande aquifer system, (4) High Plains aquifer, (5) Colorado Plateaus aquifers, and (6) Columbia Plateau basaltic-rock aquifers. These six PAs supply a large part of the Nation’s drinking water and cover a large geographic extent of the western conterminous United States. Groundwater samples were analyzed for a large suite of water-quality constituents including major ions, nutrients, trace elements, volatile organic compounds (VOCs), pesticide compounds, radioactive constituents, age tracers, and, in selected PAs, perchlorate. Two types of assessments were made: (1) a status assessment that describes the quality of the groundwater resource at time of collection and (2) an understanding assessment that evaluates relations between groundwater quality and potential explanatory factors that represent characteristics of the aquifer system. The assessments characterize untreated groundwater quality, which might be different than the quality of drinking water delivered to consumers. The assessments are based on water-quality data collected from 352 wells and 6 springs using an equal-area grid sampling design. This sampling approach allows for the estimation of the proportion of high, moderate, or low concentrations relative to federal water-quality benchmarks of selected constituents in the area of each PA. Results were compared to established benchmarks for drinking-water quality to provide context for evaluating the quality of untreated groundwater: Federal regulatory benchmarks for protecting human health, non-regulatory human-health benchmarks, and non-regulatory benchmarks for nuisance chemicals. Not all constituents that were analyzed have benchmarks and thus were not considered for assessments. Concentrations are characterized as high if they are greater than their benchmark. Concentrations are considered moderate if they are greater than one-half their benchmark (for inorganic constituents), or greater than one-tenth their benchmark (for organic constituents). Concentrations are considered low if they are less than moderate or the constituent was not detected.
Status assessment results indicated that inorganic constituents more commonly occurred at high and moderate concentrations in the six PAs than organic constituents, and organic constituents predominately occurred at low concentrations. Inorganic constituents that exceeded health-based benchmarks (high concentrations) were present in all six PAs; aquifer-scale proportion were 30 percent in the Rio Grande aquifer system, 22 percent in the Basin and Range basin-fill aquifers, 20 percent in the Basin and Range carbonate-rock aquifers, 19 percent in the High Plains aquifer, 16 percent in the Colorado Plateaus aquifers, and 8 percent in the Columbia Plateau basaltic-rock aquifers. Arsenic, fluoride, manganese, and total dissolved solids were the constituents most commonly present at high concentrations. Organic constituents with human-health benchmarks (pesticide compounds and VOCs) did not occur at high concentrations and moderate concentrations were infrequent; aquifer-scale proportions ranged from 0 to 5 percent. Detections of organic compounds at low concentrations, however, occurred in all six PAs, with detection frequencies ranging from 10 to 26 percent for pesticide compounds and from 10 to 46 percent for VOCs. Specific organic constituents with detection frequencies greater than 10 percent were four herbicides (atrazine, didealkylatrazine, bromoform, and propazine), one insecticide (propoxur), and two VOCs (the trihalomethanes chloroform and bromodichloromethane). Where collected—in the Rio Grande aquifer system and High Plains aquifer—perchlorate did not occur at high concentrations; moderate aquifer-scale proportions were 3 and 11 percent, respectively.
The understanding assessment included statistical tests to evaluate relations between constituent concentrations and potential explanatory factors to identify natural and human factors that affect groundwater quality. Potential explanatory factors included depth to bottom of well perforation, groundwater age category, land use, aquifer lithology, hydrologic conditions, and geochemical conditions. Higher concentrations of trace elements, radioactive constituents, and constituents with non-health-based benchmarks generally were associated with unconsolidated sand and gravel aquifer lithologies, premodern groundwater age, greater aridity, and more alkaline pH. Organic constituents with detection frequencies greater than 10 percent generally were associated with urban land use, shallower well depths, and higher total dissolved solids concentrations. The results for the six western PAs provide important insights into the quality of groundwater that is used for drinking water in the western United States, as well as natural and human factors that affect groundwater quality in this region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205078","collaboration":"National Water Quality Program","usgsCitation":"Rosecrans, C.Z., and Musgrove, M., 2020, Water Quality of groundwater used for public supply in principal aquifers of the western United States: U.S. Geological Survey Scientific Investigations Report 2020–5078, 142 p., https://doi.org/10.3133/sir20205078.","productDescription":"Report: x, 142 p.; 5 Data Releases","onlineOnly":"Y","ipdsId":"IP-097925","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":378206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5078/coverthb.jpg"},{"id":378207,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5078/sir20205078.pdf","text":"Report","size":"29.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5078"},{"id":378208,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HQ3X18","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater quality data from the National Water Quality Assessment Project, May 2012 through December 2013"},{"id":378209,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W0942N","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Datasets from groundwater-quality data from the National Water-Quality Assessment Project, January through December 2014 and select quality-control data from May 2012 through December 2014"},{"id":378210,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7XK8DHK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Datasets from groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2015 and previously unpublished data from 2013 to 2014"},{"id":378211,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W4RR74","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Datasets from groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015"},{"id":378212,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P916H748","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for groundwater-quality and select quality-control data for the Colorado Plateaus Principal Aquifer"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Kansas, Montana, Nebraska, Nevada, New Mexico, North Dakota, Oklahoma, Oregon, South Dakota, Texas, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.2548828125,\n 27.605670826465445\n ],\n [\n -96.0205078125,\n 27.605670826465445\n ],\n [\n -96.0205078125,\n 49.296471602658066\n ],\n [\n -126.2548828125,\n 49.296471602658066\n ],\n [\n -126.2548828125,\n 27.605670826465445\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Globally, peatlands play an important role in the carbon (C) cycle. High water level is a key factor in maintaining C storage in peatlands, but water levels are vulnerable to climate change and anthropogenic disturbance. This review examines literature related to the effects of water level alteration on C cycling in peatlands to summarize new ideas and uncertainties emerging in this field. Peatland ecosystems maintain their function by altering plant community structure to adapt to changing water levels. Regarding primary production, woody plants are more productive in unflooded, well-aerated conditions, while Sphagnum mosses are more productive in wetter conditions. The responses of sedges to water level alteration are species-specific. While peat decomposition is faster in unflooded, well aerated conditions, increased plant production may counteract the C loss induced by increased ecosystem respiration (ER) for a period of time. In contrast, rising water table maintains anaerobic conditions and enhances the role of the peatland as a C sink. Nevertheless, changes in DOC flux during water level fluctuation is complicated and depends on the interactions of flooding with environment. Notably, vegetation also plays a role in C flux but particular species vary in their ability to sequester and transport C. Bog ecosystems have a greater resilience to water level alteration than fens, due to differences in biogeochemical responses to hydrology. The full understanding of the role of peatlands in global C cycling deserves much more study due to uncertainties of vegetation feedbacks, peat–water interactions, microbial mediation of vegetation, wildfire, and functional responses after hydrologic restoration.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20964129.2020.1806113","usgsCitation":"Zhong, Y., Ming, J., and Middleton, B., 2020, Effects of water level alteration on carbon cycling in peatlands: Ecosystem Health and Sustainability, v. 6, no. 1, 1806113, 29 p., https://doi.org/10.1080/20964129.2020.1806113.","productDescription":"1806113, 29 p.","ipdsId":"IP-109966","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455385,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/20964129.2020.1806113","text":"Publisher Index Page"},{"id":378449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhong, Yehui","contributorId":240734,"corporation":false,"usgs":false,"family":"Zhong","given":"Yehui","email":"","affiliations":[{"id":48133,"text":"Chinese Academy of Science (Beijing University)","active":true,"usgs":false}],"preferred":false,"id":798866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ming, Jiang","contributorId":240735,"corporation":false,"usgs":false,"family":"Ming","given":"Jiang","email":"","affiliations":[{"id":48136,"text":"Chinese Academy of Science","active":true,"usgs":false}],"preferred":false,"id":798867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206609,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":798868,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218273,"text":"70218273 - 2020 - elfgen: A new instream flow framework for rapid generation and optimization of flow-ecology relations","interactions":[],"lastModifiedDate":"2021-02-24T13:06:57.400429","indexId":"70218273","displayToPublicDate":"2020-09-06T07:25:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"elfgen: A new instream flow framework for rapid generation and optimization of flow-ecology relations","docAbstract":"Effective water resource management requires practical, data‐driven determination of instream flow needs. Newly developed, high‐resolution flow models and aquatic species databases provide enormous opportunity, but the volume of data can prove challenging to manage without automated tools. The objective of this study was to develop a framework of analytical methods and best practices to reduce costs of entry into flow–ecology analysis by integrating widely available hydrologic and ecological datasets. Ecological limit functions (ELFs) describing the relation between maximum species richness and stream size characteristics (streamflow or drainage area) were developed. Species richness is expected to increase with streamflow through a watershed up to a point where it either plateaus or transitions to a decreasing trend in larger streams. Our results show that identifying the location of this \"breakpoint\" is critical for producing optimal ELF model fit. We found that richness breakpoints can be estimated using automated low‐supervision methods, with high‐supervision providing negligible improvement in detection accuracy. Model fit (and predictive capability) was found to be superior in smaller hydrologic units. The ELF model (\"elfgen\" R package available on GitHub: https://github.com/HARPgroup/elfgen) can be used to generate ELFs using built‐in datasets for the conterminous United States, or applied anywhere else streamflow and biodiversity data inputs are available.
Linked hydrologic, hydraulic, and ecological models can facilitate planning and implementing water releases from reservoirs to achieve ecological objectives along rivers. We applied a flow‐ecology model, the Ecosystem Functions Model (HEC‐EFM), to the Bill Williams River in southwestern USA to estimate areas suitable for recruitment of riparian tree seedlings in the context of managing flow releases from a large dam for riparian restoration. Ecological variables in the model included timing of seed dispersal, tolerable rates of flow recession, and tolerable duration of inundation following germination and early seedling establishment for native Fremont cottonwood and Goodding's willow, and non‐native tamarisk. Hydrological variables included peak flow timing, rate of flow recession following the peak, and duration of inundation. A one‐dimensional hydraulic model was applied to estimate stage‐discharge relationships along ~58 river kilometres. We then used HEC‐EFM to apply relationships between seedling ecology and streamflow to link hydrological dynamics with ecological response. We developed and validated HEC‐EFM based on an examination of seedling recruitment following an experimental flow release from Alamo Dam in spring 2006. The model predicted the largest area of potential recruitment for cottonwood (280–481 ha), with smaller areas predicted for willow (174–188 ha) and tamarisk (59–60 ha). Correlations between observed and predicted patches with successful seedling recruitment for areas within 40 m of the main channel ranged from 0.66 to 0.94. Finally, we examined arrays of hydrographs to identify which are most conducive to seedling recruitment along the river, given different combinations of peak flow, recession rate, and water volume released. Similar application of this model could be useful for informing reservoir management in the context of riparian restoration along other rivers facing similar challenges.