{"pageNumber":"41","pageRowStart":"1000","pageSize":"25","recordCount":16445,"records":[{"id":70223823,"text":"70223823 - 2022 - Identifying climate-resistant vernal pools: Hydrologic refugia for amphibian reproduction under droughts and climate change","interactions":[],"lastModifiedDate":"2022-08-01T16:47:26.011836","indexId":"70223823","displayToPublicDate":"2021-09-02T07:41:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Identifying climate-resistant vernal pools: Hydrologic refugia for amphibian reproduction under droughts and climate change","docAbstract":"

Vernal pools of the northeastern United States provide important breeding habitat for amphibians but may be sensitive to droughts and climate change. These seasonal wetlands typically fill by early spring and dry by mid-to-late summer. Because climate change may produce earlier and stronger growing-season evapotranspiration combined with increasing droughts and shifts in precipitation timing, management concerns include the possibility that some pools will increasingly become dry earlier in the year, potentially interfering with amphibian life-cycle completion. In this context, a subset of pools that continue to provide wetland habitat later into the year under relatively dry conditions might function as ecohydrologic refugia, potentially supporting species persistence even as summer conditions become warmer and droughts more frequent. We used approximately 3,000 field observations of inundation from 449 pools to train machine-learning models that predict the likelihood of pool inundation based on pool size, day of the year, climate conditions, short-term weather patterns, and soil, geologic, and landcover attributes. Models were then used to generate predictions of pool wetness across five seasonal time points, three short-term weather scenarios, and four sets of downscaled climate projections. Model outputs are available through a website allowing users to choose the inundation thresholds, time points, weather scenarios, and future climate projections most relevant to their management needs. Together with long-term monitoring of individual pools at the site scale, this regional-scale study can support amphibian conservation by helping to identify which pools may be most likely to function as ecohydrologic refugia from droughts and climate change.

","language":"English","publisher":"Wiley","doi":"10.1002/eco.2354","usgsCitation":"Cartwright, J.M., Morelli, T.L., and Campbell Grant, E.H., 2022, Identifying climate-resistant vernal pools: Hydrologic refugia for amphibian reproduction under droughts and climate change: Ecohydrology, v. 15, no. 5, e2354, 23 p., https://doi.org/10.1002/eco.2354.","productDescription":"e2354, 23 p.","ipdsId":"IP-122474","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":449730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.2354","text":"Publisher Index Page"},{"id":388994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":822795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":822796,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229532,"text":"70229532 - 2022 - Factors affecting nest success of colonial nesting waterbirds in southwest Louisiana","interactions":[],"lastModifiedDate":"2022-03-28T16:57:27.539992","indexId":"70229532","displayToPublicDate":"2021-08-27T09:49:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting nest success of colonial nesting waterbirds in southwest Louisiana","docAbstract":"

Subsidence and accelerated sea level rise impact nesting area availability and flood probabilities of breeding islands for colonial nesting waterbirds. In 2017 and 2018, we monitored 855 nests of four species of colonial nesting waterbirds on Rabbit Island, LA, to determine factors affecting nest and chick success. Based on logistic exposure models of nests, tricolored herons had the greatest likelihood of survival to hatch (mean (95% confidence interval)) (77% (65.9–83.1%)), followed by brown pelicans (70% (59.9–98.5%)), roseate spoonbills (70% (38.9–83.8%)), and Forster’s terns (12% (10.7–12.2%)). Likelihood of survival to fledge was highest for tricolored herons (32% (12.8–40.7%)), followed by brown pelicans (28% (19.5–28.6%)), roseate spoonbills (47% (43.7–53.3%)), and Forster’s terns (0% (0.005–0.01%)). Nesting strategy and nest timing impacted survival rate; however, the effect depended on timing of inundation events as the timing of inundation events varied across years. Flooding was the primary cause of nest failure for most species. In 2003–2012, rapid expansion in brown pelican colony numbers and significant chick production occurred at Rabbit Island, but hydrologic records indicate no island inundation occurred during the breeding season from the beginning of the hydrologic record (2006) through 2011. Thus, our results contrast with those of previous studies conducted under different hydrologic conditions and demonstrate the challenges of short-term studies informing coastal restoration in a system that is influenced by multi-year to multi-decadal climatic cycles.


","language":"English","publisher":"Springer Link","doi":"10.1007/s12237-021-00993-4","usgsCitation":"Ritenour, K., King, S.L., Collins, S.M., and Kaller, M., 2022, Factors affecting nest success of colonial nesting waterbirds in southwest Louisiana: Estuaries and Coasts, v. 45, p. 897-912, https://doi.org/10.1007/s12237-021-00993-4.","productDescription":"16 p.","startPage":"897","endPage":"912","ipdsId":"IP-126736","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":489112,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.lsu.edu/gradschool_theses/4981","text":"External Repository"},{"id":397020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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M.","contributorId":273184,"corporation":false,"usgs":false,"family":"Collins","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":837774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaller, M.D.","contributorId":288351,"corporation":false,"usgs":false,"family":"Kaller","given":"M.D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837775,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70224977,"text":"70224977 - 2022 - Quantifying the response of nitrogen speciation to hydrology in the Chesapeake Bay Watershed using a multilevel modeling approach","interactions":[],"lastModifiedDate":"2023-01-18T15:37:05.805872","indexId":"70224977","displayToPublicDate":"2021-07-26T07:16:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6465,"text":"Journal of American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the response of nitrogen speciation to hydrology in the Chesapeake Bay Watershed using a multilevel modeling approach","docAbstract":"

Excessive nitrogen (N) inputs to coastal waters can lead to severe eutrophication and different chemical forms of N exhibit varying levels of effectiveness in fueling primary production. Efforts to mitigate N fluxes from coastal watersheds are often guided by models that predict changes in N loads as a function of changes in land use, management practices, and climate. However, relatively little is known on the impacts of such changes on the relative fractions of different N forms. We leveraged a long-term dataset of N loads from over 100 river stations to investigate how the \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0001\" fraction, that is, the ratio of \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0002\" to total N (\"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0003\"/TN), changes as a function of spatio-temporal changes in TN loads in the Chesapeake Bay watershed. We built a hierarchical model that separates the response of \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0004\" to changes in TN load occurring at different scales: Across river stations, where differences in TN loads are largely driven by spatial differences in anthropogenic inputs, and within stations, where inter-annual variability in hydrology is a key driver of changes in TN loads. Results suggest that while increases in TN loads resulting from changes in anthropogenic inputs lead to an increase in the \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0005\" fraction, a decrease in the \"urn:x-wiley:1093474X:media:jawr12951:jawr12951-math-0006\" fraction may occur when increases in TN loads are driven by increased streamflow. These results are especially relevant in watersheds that may experience changes in N loads due to both management decisions and climate-driven changes in hydrology.

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0000-0001-6451-2513","orcid":"https://orcid.org/0000-0001-6451-2513","contributorId":225440,"corporation":false,"usgs":true,"family":"Shenk","given":"Gary","email":"","middleInitial":"W.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":824994,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221167,"text":"70221167 - 2022 - Short communication: evidence for geologic control of rip channels along Prince Edward Island, Canada","interactions":[],"lastModifiedDate":"2022-03-15T15:55:06.481082","indexId":"70221167","displayToPublicDate":"2021-06-03T07:44:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3059,"text":"Physical Geography","active":true,"publicationSubtype":{"id":10}},"title":"Short communication: evidence for geologic control of rip channels along Prince Edward Island, Canada","docAbstract":"

Rip currents can move unsuspecting swimmers offshore rapidly and represent a significant risk to beach users worldwide, including along the northern coast of Prince Edward Island (PEI), Canada. Although many rip currents are ephemeral and/or spatially variable in response to changes in the nearshore bar morphology and wave and tidal forcing, it is possible for rip channels to be geologically controlled and quasi-permanent in morphology, location, and flow. Several rip channels along the northern coast of PEI appear in the same location from year to year and correspond to elongated lakes, rivers, or swales behind the modern coastal dune system. Given their persistent location and alignment with back dune hydrology, ground-penetrating radar surveys were collected along Brackley and Cavendish Beaches in July 2019 to determine whether persistent rip channels are associated with now-buried river channels extending beneath the modern dunes and continuing offshore. Strong reflectors similar to V-shaped river valleys are present in alongshore transects at both beaches. These infilled valleys align with back-dune hydrology and persistent rip channels, suggesting modern rip channels are structurally controlled and maintained by antecedent geology. This link provides important guidance to beach access management and the distribution of lifesaving strategies along the affected beaches.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02723646.2021.1923389","usgsCitation":"Wernette, P., and Houser, C., 2022, Short communication: evidence for geologic control of rip channels along Prince Edward Island, Canada: Physical Geography, v. 43, no. 2, p. 145-162, https://doi.org/10.1080/02723646.2021.1923389.","productDescription":"18 p.","startPage":"145","endPage":"162","ipdsId":"IP-118879","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Prince Edward Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.434814453125,\n 45.909122123907295\n ],\n [\n -61.85852050781249,\n 45.909122123907295\n ],\n [\n -61.85852050781249,\n 47.16730970131578\n ],\n [\n -64.434814453125,\n 47.16730970131578\n ],\n [\n -64.434814453125,\n 45.909122123907295\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Chris 0000-0002-7880-7619","orcid":"https://orcid.org/0000-0002-7880-7619","contributorId":259276,"corporation":false,"usgs":false,"family":"Houser","given":"Chris","email":"","affiliations":[{"id":52343,"text":"University of Windsor, School of the Environment","active":true,"usgs":false}],"preferred":false,"id":816926,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224261,"text":"70224261 - 2022 - Estimating the influence of oyster reef chains on freshwater detention at the estuary scale using Landsat-8 imagery","interactions":[],"lastModifiedDate":"2022-01-06T17:19:15.625237","indexId":"70224261","displayToPublicDate":"2021-05-26T07:17:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the influence of oyster reef chains on freshwater detention at the estuary scale using Landsat-8 imagery","docAbstract":"

Oyster reef chains grow in response to local hydrodynamics and can redirect flows, particularly when reef chains grow perpendicular to freshwater flow paths. Singularly, oyster reef chains can act as porous dams that may facilitate nearshore accumulation of fresh or low-salinity water, in turn creating intermediate salinities that support oyster growth and estuarine conditions. However, oyster-driven freshwater detention has only been confirmed by limited, point-scale observational data, and simplified models. Oyster reef-driven freshwater detention in real ecosystems at the estuary scale remains largely unexplored. In this study, we analyzed the visible bands in 30-m resolution remote sensing (RS) images recorded by the Operational Land Imager aboard Landsat-8 to characterize the freshwater detention effect of oyster reef chains across a set of hydrologic conditions. Our results support prior findings indicating that 30-m resolution RS images recorded by the Operational Land Imager aboard Landsat-8 are useful for analyzing coastal dynamics after atmospheric correction, despite having been originally designed for terrestrial studies. Statistical models of water-leaving reflectance revealed that freshwater detention by oyster reefs was evident across the estuary, with the greatest effect occurring in the region closest to shore. Additionally, statistical modeling results and spatial patterns apparent in the satellite images suggested that reef-driven freshwater detention occurred under high riverine discharge conditions, but was less evident when flow was low. Beyond offering insight on the potential role of oyster reefs as mediators of estuarine hydrology, this study presents a transferable methodological framework for exploring estuarine biophysical feedbacks in blackwater river estuaries using satellite remote sensing.

","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-00959-6","usgsCitation":"Alonso, A., Nelson, N.G., Yurek, S., Kaplan, D., Olabarrieta, M., and Frederick, P., 2022, Estimating the influence of oyster reef chains on freshwater detention at the estuary scale using Landsat-8 imagery: Estuaries and Coasts, v. 45, p. 1-16, https://doi.org/10.1007/s12237-021-00959-6.","productDescription":"16 p.","startPage":"1","endPage":"16","ipdsId":"IP-120934","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":489117,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2078.1/246633","text":"External Repository"},{"id":389328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Suwannee Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.353271484375,\n 29.13776825498331\n ],\n [\n -82.67211914062499,\n 29.13776825498331\n ],\n [\n -82.67211914062499,\n 29.551955878093022\n ],\n [\n -83.353271484375,\n 29.551955878093022\n ],\n [\n -83.353271484375,\n 29.13776825498331\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2021-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Alonso, Alice","contributorId":265791,"corporation":false,"usgs":false,"family":"Alonso","given":"Alice","email":"","affiliations":[{"id":54799,"text":"Earth and Life Institute, Universite catholique de Louvain, Louvain-la-Neuve, Belgium","active":true,"usgs":false}],"preferred":false,"id":823387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Natalie G.","contributorId":265792,"corporation":false,"usgs":false,"family":"Nelson","given":"Natalie","email":"","middleInitial":"G.","affiliations":[{"id":54801,"text":"Biological and Agricultural Engineering, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":823388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216738,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":823389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaplan, David","contributorId":218612,"corporation":false,"usgs":false,"family":"Kaplan","given":"David","affiliations":[],"preferred":false,"id":823390,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":823391,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frederick, Peter C","contributorId":150013,"corporation":false,"usgs":false,"family":"Frederick","given":"Peter C","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":823392,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222132,"text":"70222132 - 2022 - Environmental evolution of peat in the Sacramento – San Joaquin Delta (California) during the Middle and Late Holocene as deduced from pollen, diatoms and magnetism","interactions":[],"lastModifiedDate":"2022-04-11T16:29:49.277945","indexId":"70222132","displayToPublicDate":"2020-05-31T06:55:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"Environmental evolution of peat in the Sacramento – San Joaquin Delta (California) during the Middle and Late Holocene as deduced from pollen, diatoms and magnetism","docAbstract":"

We studied the sequence of climatic and hydrological events associated with the formation of peat during the Holocene, using pollen, diatoms and environmental magnetism from peat cores at three locations in the Sacramento-San Joaquin Delta of California: Browns Island, Franks Wetland and Webb Track Levee. Our data show that peat first formed under relatively dry conditions in a freshwater environment before 6.5 ka BP. Subsequently, pollen accumulation rates were highest prior to intervals with high peat accretion rates but are inversely correlated with organic accumulation rate. Intervals of high peat accretion were preceded by pulses of terrigenous material. During intensive drainage episodes, high flows delivered abundant, coarser-grained sediment to the marshes, which inundated the existing vegetation and decreased the rate of biochemical decay. The build-up of undecomposed organic material led to the acceleration of peat accretion. Our data support the rarely discussed hypothesis that most of the peat in the Sacramento-San Joaquin Delta formed in freshwater marshes that were fed by rivers draining from the Sierra Nevada, rather than in saltwater wetlands resulting from sea level rise and estuarine submergence. This result has important implications for current attempts to remediate and restore the Delta ecosystem.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2020.05.012","usgsCitation":"Delusina, I., Starratt, S.W., and Verosub, K.L., 2022, Environmental evolution of peat in the Sacramento – San Joaquin Delta (California) during the Middle and Late Holocene as deduced from pollen, diatoms and magnetism: Quaternary International, v. 621, p. 50-61, https://doi.org/10.1016/j.quaint.2020.05.012.","productDescription":"12 p.","startPage":"50","endPage":"61","ipdsId":"IP-090434","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":449877,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quaint.2020.05.012","text":"Publisher Index Page"},{"id":387320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Sacramento","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.728515625,\n 38.39764411353178\n ],\n [\n -121.23138427734375,\n 38.39764411353178\n ],\n [\n -121.23138427734375,\n 38.732661120482334\n ],\n [\n -121.728515625,\n 38.732661120482334\n ],\n [\n -121.728515625,\n 38.39764411353178\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"621","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Delusina, Irina","contributorId":261263,"corporation":false,"usgs":false,"family":"Delusina","given":"Irina","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":819619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":819620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verosub, Kenneth L","contributorId":261264,"corporation":false,"usgs":false,"family":"Verosub","given":"Kenneth","email":"","middleInitial":"L","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":819621,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222383,"text":"sir20215068 - 2021 - Precipitation-driven flood-inundation mapping of the Little Blue River at Grandview, Missouri","interactions":[],"lastModifiedDate":"2026-04-02T14:16:23.467047","indexId":"sir20215068","displayToPublicDate":"2022-01-07T13:45:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5068","displayTitle":"Precipitation-Driven Flood-Inundation Mapping of the Little Blue River at Grandview, Missouri","title":"Precipitation-driven flood-inundation mapping of the Little Blue River at Grandview, Missouri","docAbstract":"

The U.S. Geological Survey (USGS), in cooperation with the City of Grandview, Missouri, assessed flooding of the Little Blue River at Grandview resulting from varying precipitation magnitudes and durations and expected land-cover changes. The precipitation scenarios were used to develop a library of flood-inundation maps that included a 3.5-mile reach of the Little Blue River and tributaries within and adjacent to the city.

A hydrologic model of the upper Little Blue River Basin and a hydraulic model of a selected study reach of the Little Blue River and tributaries were constructed to assess streamflow magnitudes associated with simulated precipitation amounts and the resulting flood-inundation conditions. The U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS; version 4.4.1) was used to simulate the amount of streamflow produced from a range of rain events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS; version 5.0.7) was then used to construct a steady-state hydraulic model to map resulting areas of flood inundation.

Both models were calibrated to the May 28, 2020, high-flow event that produced a peak streamflow approximating a 10-percent annual exceedance probability (10-year flood-frequency recurrence interval) at the Little Blue River at Grandview streamgage (USGS station 06893750). The calibrated HEC–HMS model was used to simulate streamflows from design rainfall events of 1- to 8-hour durations and ranging from a 100- to 0.2-percent annual exceedance probability. Flood-inundation maps were produced for USGS streamflow stages of 17.0 feet (ft), or near bankfull, to 23.0 ft, or a stage exceeding the 0.2-percent annual exceedance interval flood, using the HEC–RAS model. The consequence of each precipitation duration-frequency value was represented by a 1-ft increment inundation map based on the generated peak streamflow from that rainfall event and the corresponding stage at the reference USGS streamgage.

Four scenarios were developed with the HEC–HMS hydrologic model: (1) current (2016) land cover, normal antecedent soil-moisture conditions; (2) current land cover, wet antecedent soil-moisture conditions; (3) future land cover, normal antecedent soil-moisture conditions; and (4) future land cover, wet antecedent soil-moisture conditions. The future land-cover condition was estimated based on anticipated development in the basin. All precipitation scenarios were input into each of the four land-cover antecedent moisture conditions and then assigned to a resulting flood-inundation map based on the generated peak flow and corresponding stage at the reference streamgage.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215068","collaboration":"Prepared in cooperation with City of Grandview, Missouri","usgsCitation":"Heimann, D.C., Voss, J.D., and Rydlund, P.H., Jr., 2021, Precipitation-driven flood-inundation mapping of the Little Blue River at Grandview, Missouri (ver. 1.1, January 2022): U.S. Geological Survey Scientific Investigations Report 2021–5068, 19 p., https://doi.org/10.3133/sir20215068.","productDescription":"Report: viii, 19 p.; 2 Data Releases; Dataset","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-127298","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501949,"rank":7,"type":{"id":36,"text":"NGMDB Index 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1.0: July 2021; Version 1.1: January 2022","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, Missouri 65401

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-07-26","revisedDate":"2022-01-07","noUsgsAuthors":false,"publicationDate":"2021-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Jonathon D. 0000-0001-8219-7887","orcid":"https://orcid.org/0000-0001-8219-7887","contributorId":224636,"corporation":false,"usgs":true,"family":"Voss","given":"Jonathon","email":"","middleInitial":"D.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819899,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227203,"text":"70227203 - 2021 - Dominant Sonoran Desert plant species have divergent phenological responses to climate change","interactions":[],"lastModifiedDate":"2022-01-04T14:31:38.457341","indexId":"70227203","displayToPublicDate":"2022-01-04T08:19:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9976,"text":"Madroño - A West American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Dominant Sonoran Desert plant species have divergent phenological responses to climate change","docAbstract":"

The southwestern U.S. is a global hotspot of climate change. Models project that temperatures will continue to rise through the end of the 21st century, accompanied by significant changes to the hydrological cycle. Within the Sonoran Desert, a limited number of studies have documented climate change impacts on the phenology of native plant species. Much of this phenological work to understand climate change impacts to phenology builds on research conducted nearly three decades ago to define flowering triggers and developmental requirements for native keystone Sonoran Desert woody species. Here we expand on the drivers and explore recent phenological trends for six species using a unique 36-year observational data set. We use statistical models to determine which aspects of climate influence the probability of flowering, and how flowering time may respond to climate change. We move beyond traditional models of phenology by incorporating different metrics of moisture availability in addition to temperature, weather, and climate at several time scales, including daily, weekly, seasonal, and antecedent conditions. Our results provide evidence of a trend towards earlier flowering (on the order of 1–4 days per decade) for five of the six species analyzed, and no trend for one species. The species we evaluated had contrasting phenological responses to different aspects of climate, suggesting individualistic changes in phenology and the potential of divergent plant community flowering patterns under future climate change. Understanding recent changes in flowering phenology and their climatic triggers is important to anticipating whether plant species can attract pollinators, reproduce, and persist within the community under continued climate change.

","language":"English","publisher":"California Botanical Society","doi":"10.3120/0024-9637-68.4.473","usgsCitation":"Zachmann, L.J., Wiens, J.F., Franklin, K., Crausbay, S.D., Landau, V.A., and Munson, S.M., 2021, Dominant Sonoran Desert plant species have divergent phenological responses to climate change: Madroño - A West American Journal of Botany, v. 68, no. 4, p. 473-486, https://doi.org/10.3120/0024-9637-68.4.473.","productDescription":"14 p.","startPage":"473","endPage":"486","ipdsId":"IP-126703","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":449939,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3120/0024-9637-68.4.473","text":"Publisher Index Page"},{"id":393845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Arizona-Sonora Desert Museum, King Canyon, Saguaro National Park, Sonoran Desert, Tucson Mountain Park, Tucson Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.2197494506836,\n 32.204086355917944\n ],\n [\n -111.06250762939452,\n 32.204086355917944\n ],\n [\n -111.06250762939452,\n 32.283794824838274\n ],\n [\n -111.2197494506836,\n 32.283794824838274\n ],\n [\n -111.2197494506836,\n 32.204086355917944\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"68","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zachmann, Luke J 0000-0003-2313-1460","orcid":"https://orcid.org/0000-0003-2313-1460","contributorId":265938,"corporation":false,"usgs":false,"family":"Zachmann","given":"Luke","email":"","middleInitial":"J","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":830071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiens, John F.","contributorId":270798,"corporation":false,"usgs":false,"family":"Wiens","given":"John","email":"","middleInitial":"F.","affiliations":[{"id":56218,"text":"Arizona-Sonora Desert Museum, Tucson, AZ 85743","active":true,"usgs":false}],"preferred":false,"id":830072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franklin, Kim","contributorId":270799,"corporation":false,"usgs":false,"family":"Franklin","given":"Kim","affiliations":[{"id":56218,"text":"Arizona-Sonora Desert Museum, Tucson, AZ 85743","active":true,"usgs":false}],"preferred":false,"id":830073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crausbay, Shelley D.","contributorId":197220,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","email":"","middleInitial":"D.","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":830074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landau, Vincent A. 0000-0001-9290-9438","orcid":"https://orcid.org/0000-0001-9290-9438","contributorId":265939,"corporation":false,"usgs":false,"family":"Landau","given":"Vincent","email":"","middleInitial":"A.","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":830075,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":830076,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227019,"text":"ofr20211117 - 2021 - Optimization of salt marsh management at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges, Virginia, through use of structured decision making","interactions":[],"lastModifiedDate":"2021-12-28T14:30:08.263314","indexId":"ofr20211117","displayToPublicDate":"2021-12-27T14:05:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1117","displayTitle":"Optimization of Salt Marsh Management at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges, Virginia, Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges, Virginia, through use of structured decision making","docAbstract":"

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges in Virginia. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of six marsh management units within the refuges, totaling about 575 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $143,000, but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than $143,000 included digging runnels by hand to improve drainage from the marsh surface, breaching a road to restore natural hydrology, trapping predators to enhance nest success of tidal marsh birds, and reducing the abundance of Odocoileus virginianus (white-tailed deer) to minimize their effects on marsh vegetation. The potential management benefits were derived from expected increases in number of tidal marsh obligate breeding birds, species richness of nekton, and density of spiders (as an indicator of trophic health); and an expected decrease in duration of surface flooding. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211117","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Denmon, P., and Leffel, R., 2021, Optimization of salt marsh management at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges, Virginia, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1117, 32 p., https://doi.org/10.3133/ofr20211117.","productDescription":"Report: vi, 32 p.; Database","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131973","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":393431,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":393427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1117/coverthb.jpg"},{"id":393428,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1117/ofr20211117.pdf","text":"Report","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1117"},{"id":393429,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1117/images/"},{"id":393430,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1117/ofr20211117.XML"}],"country":"United States","state":"Virginia","otherGeospatial":"Fisherman Island National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.99586486816406,\n 37.072162624715375\n ],\n [\n -75.92857360839844,\n 37.072162624715375\n ],\n [\n -75.92857360839844,\n 37.14061402065652\n ],\n [\n -75.99586486816406,\n 37.14061402065652\n ],\n [\n -75.99586486816406,\n 37.072162624715375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-12-27","noUsgsAuthors":false,"publicationDate":"2021-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Neckles, Hilary A. 0000-0002-5662-2314 hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":829243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":210574,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":829244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":829245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adamowicz, Susan C.","contributorId":174712,"corporation":false,"usgs":false,"family":"Adamowicz","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":829246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mikula, Toni","contributorId":208473,"corporation":false,"usgs":false,"family":"Mikula","given":"Toni","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":829247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Denmon, Pamela","contributorId":270392,"corporation":false,"usgs":false,"family":"Denmon","given":"Pamela","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":829248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leffel, Robert","contributorId":270393,"corporation":false,"usgs":false,"family":"Leffel","given":"Robert","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":829249,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70226991,"text":"ofr20211115 - 2021 - Optimization of salt marsh management at the Moosehorn National Wildlife Refuge, Maine, through use of structured decision making","interactions":[],"lastModifiedDate":"2021-12-27T15:49:07.673301","indexId":"ofr20211115","displayToPublicDate":"2021-12-27T10:25:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1115","displayTitle":"Optimization of Salt Marsh Management at the Moosehorn National Wildlife Refuge, Maine, Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Moosehorn National Wildlife Refuge, Maine, through use of structured decision making","docAbstract":"

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Moosehorn National Wildlife Refuge in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of four marsh management units within the refuge, totaling about 13 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $1,000, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $1,000 included improving nesting habitat for Ammodramus nelsoni (Nelson’s sparrow) or restoring hydrologic connections to the upper marsh in one marsh management unit (Hobart Stream West). The potential management benefits were derived from expected increases in the density of nekton and of spiders (as an indicator of trophic health). The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Moosehorn National Wildlife Refuge that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211115","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Mills, M., Brown, R.E., and Ramos, K., 2021, Optimization of salt marsh management at the Moosehorn National Wildlife Refuge, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1115, 28 p., https://doi.org/10.3133/ofr20211115.","productDescription":"Report: vi, 28 p.; Database","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131976","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":393375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1115/coverthb.jpg"},{"id":393376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1115/ofr20211115.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":393377,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1115/ofr20211115.xml"},{"id":393379,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":393378,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1115/images"}],"country":"United States","state":"Maine","otherGeospatial":"Moosehorn National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.27890014648438,\n 44.80132682904856\n ],\n [\n -67.15,\n 44.80132682904856\n ],\n [\n -67.15,\n 44.918625522424925\n ],\n [\n -67.27890014648438,\n 44.918625522424925\n ],\n [\n -67.27890014648438,\n 44.80132682904856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-12-27","noUsgsAuthors":false,"publicationDate":"2021-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Neckles, Hilary A. 0000-0002-5662-2314 hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":829105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":829106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":829107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adamowicz, Susan C.","contributorId":174712,"corporation":false,"usgs":false,"family":"Adamowicz","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":829108,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mikula, Toni","contributorId":208473,"corporation":false,"usgs":false,"family":"Mikula","given":"Toni","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":829109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mills, Maurice","contributorId":270343,"corporation":false,"usgs":false,"family":"Mills","given":"Maurice","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":829110,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Raymond E.","contributorId":85064,"corporation":false,"usgs":false,"family":"Brown","given":"Raymond","email":"","middleInitial":"E.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":829111,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ramos, Keith","contributorId":270344,"corporation":false,"usgs":false,"family":"Ramos","given":"Keith","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":829112,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228917,"text":"70228917 - 2021 - A statistical framework to track temporal dependence of chlorophyll–nutrient relationships with implications for lake eutrophication management","interactions":[],"lastModifiedDate":"2022-02-24T23:14:04.830404","indexId":"70228917","displayToPublicDate":"2021-12-23T16:55:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A statistical framework to track temporal dependence of chlorophyll–nutrient relationships with implications for lake eutrophication management","docAbstract":"

A reliable chlorophyll–nutrient relationship (CNR) is essential for lake eutrophication management. Although the spatial variability of CNRs has been extensively explored, temporal variations of CNRs at the individual lake scale has rarely been discussed. The paucity of information about temporal dependence in CNRs may in part be due to the lack of a suitable statistical framework that helps guide such investigations. In order to reveal temporal dependence of CNR, this study develop a novel statistical framework. In the framework, we employ quantile regression to generate overall (the entire dataset), annual (subsets for each year), and accumulative (subsets collected before a certain year) CNRs. We aim to 1) show biases of annual relationships by comparing the overall and annual relationships and 2) determine whether or not data accumulation is enough to develop a reliable CNR. We use Lake Champlain and Lake Kasumigaura as case studies to illustrate the necessary steps needed to utilize this novel framework. Results show that large interannual variations exist for CNRs. Accumulative relationships tend to converge to the overall relationship, indicating that overall relationships are reliable for informing lake-specific eutrophication management in the two case study lakes. The novel statistical framework that we propose for a procedure to estimate reliable CNRs is important for informing lake-specific eutrophication control decision-making processes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125883","usgsCitation":"Qiu, Q., Liang, Z., Xu, Y., Matsuzaki, S.S., Komatsu, K., and Wagner, T., 2021, A statistical framework to track temporal dependence of chlorophyll–nutrient relationships with implications for lake eutrophication management: Journal of Hydrology, v. 603, no. Part D, 127134, 10 p., https://doi.org/10.1016/j.jhydrol.2020.125883.","productDescription":"127134, 10 p.","ipdsId":"IP-119115","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":449983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2020.125883","text":"Publisher Index Page"},{"id":396460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, United States","otherGeospatial":"Ibaraki Prefecture, Lake Champlain, Lake Kasumigaura","volume":"603","issue":"Part D","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qiu, Qianlinglin","contributorId":280020,"corporation":false,"usgs":false,"family":"Qiu","given":"Qianlinglin","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liang, Zhongyao","contributorId":280018,"corporation":false,"usgs":false,"family":"Liang","given":"Zhongyao","email":"","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":835889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, Yaoyang","contributorId":280019,"corporation":false,"usgs":false,"family":"Xu","given":"Yaoyang","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":835890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matsuzaki, Shin-Ichiro S.","contributorId":203197,"corporation":false,"usgs":false,"family":"Matsuzaki","given":"Shin-Ichiro","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":836003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Komatsu, Kazuhiro","contributorId":280073,"corporation":false,"usgs":false,"family":"Komatsu","given":"Kazuhiro","email":"","affiliations":[],"preferred":false,"id":836005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":835888,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226963,"text":"70226963 - 2021 - Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area","interactions":[],"lastModifiedDate":"2021-12-22T12:45:24.962293","indexId":"70226963","displayToPublicDate":"2021-12-20T06:41:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area","docAbstract":"
Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVIMccL and EVI2MccL) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption. 
","language":"English","publisher":"MDPI","doi":"10.3390/rs13245167","usgsCitation":"Abbasi, N., Nouri, H., Didan, K., Barreto Munez, A., Chavoshi Borujeni, S., Salemi, H., Opp, C., Siebert, S., and Nagler, P.L., 2021, Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area: Remote Sensing, v. 13, no. 24, 5167, 27 p., https://doi.org/10.3390/rs13245167.","productDescription":"5167, 27 p.","ipdsId":"IP-133278","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13245167","text":"Publisher Index Page"},{"id":393291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"24","noUsgsAuthors":false,"publicationDate":"2021-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Abbasi, Neda","contributorId":270293,"corporation":false,"usgs":false,"family":"Abbasi","given":"Neda","email":"","affiliations":[{"id":56138,"text":"Dept of Crop Sciences, University of Göttingen, Von-Siebold-Straße 8, 37075, Göttingen, Germany; Dept of Geography, Philipps-Universität Marburg, Deutschhausstraße 10, 35032, Marburg, Germany","active":true,"usgs":false}],"preferred":false,"id":828951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nouri, Hamideh","contributorId":178847,"corporation":false,"usgs":false,"family":"Nouri","given":"Hamideh","affiliations":[],"preferred":false,"id":828952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":828953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barreto Munez, Armando","contributorId":270294,"corporation":false,"usgs":false,"family":"Barreto Munez","given":"Armando","email":"","affiliations":[{"id":56140,"text":"Biosystems Engineering. The University of Arizona, 1177 E. 4th St., Tucson, AZ 85719, USA","active":true,"usgs":false}],"preferred":false,"id":828954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":828955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salemi, Hamidreza","contributorId":270295,"corporation":false,"usgs":false,"family":"Salemi","given":"Hamidreza","email":"","affiliations":[{"id":56141,"text":"Agricultural Engineering Research Institute, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan 19395-1113, Iran","active":true,"usgs":false}],"preferred":false,"id":828956,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Opp, Christian","contributorId":270296,"corporation":false,"usgs":false,"family":"Opp","given":"Christian","email":"","affiliations":[{"id":56142,"text":"Dept of Geography, Philipps-Universität Marburg, Deutschhausstraße 10, 35032, Marburg, Germany","active":true,"usgs":false}],"preferred":false,"id":828957,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siebert, Stefan","contributorId":270297,"corporation":false,"usgs":false,"family":"Siebert","given":"Stefan","email":"","affiliations":[{"id":56143,"text":"Dept of Crop Sciences, University of Göttingen, Von-Siebold-Straße 8, 37075, Göttingen, Germany","active":true,"usgs":false}],"preferred":false,"id":828958,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":828959,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70226852,"text":"sir20215138 - 2021 - Streamflow response to potential changes in climate in the Upper Rio Grande Basin","interactions":[],"lastModifiedDate":"2022-01-04T23:47:17.277742","indexId":"sir20215138","displayToPublicDate":"2021-12-16T16:27:02","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5138","displayTitle":"Streamflow Response to Potential Changes in Climate in the Upper Rio Grande Basin","title":"Streamflow response to potential changes in climate in the Upper Rio Grande Basin","docAbstract":"

The Rio Grande is a vital water source for the southwestern States of Colorado, New Mexico, and Texas and for northern Mexico. The river serves as the primary source of water for irrigation in the region, has many environmental and recreational uses, and is used by more than 13 million people including those in the Cities of Albuquerque and Las Cruces, New Mexico; El Paso, Texas; and Ciudad Juárez, Chihuahua, Mexico. However, concern is growing over the increasing gap between water supply and demand in the Upper Rio Grande Basin. As populations increase and agricultural crop patterns change, demands for water are increasing, at the same time the region is undergoing a decrease in supply due to drought and climate change.

Quantifying the impact of projected climate change on Rio Grande streamflow is difficult because of numerous anthropogenic influences on the hydrologic system. The conveyance and use of surface water in the Upper Rio Grande Basin are achieved through an engineered system of reservoirs, diversions, and irrigation canals designed to deliver water to agricultural, municipal, and industrial users, who greatly reduce the cumulative volume of water in the river. For example, streamflow at Fort Quitman, Tex., the southernmost point of the Upper Rio Grande Basin, has undergone a 95-percent reduction in flow relative to the river’s native state, and some stretches of the river can intermittently go dry. Because streamflow in the basin is highly altered, disentangling the impacts of climate change and changes in streamflow due to anthropogenic influences such as dams, diversions, and other forms of water use is difficult. Therefore, a model of naturalized flow was developed to determine to what degree changes in streamflow can be attributed to potential changes in future temperature and precipitation without quantifying future changes in anthropogenic influences. This study, conducted by the U.S. Geological Survey in cooperation with the South Central Climate Adaptation Science Center and the U.S. Army Corps of Engineers, included the development and calibration of a watershed model of the Upper Rio Grande Basin using the Precipitation-Runoff Modeling System to simulate naturalized streamflow conditions for historical and future time periods.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215138","collaboration":"Prepared in cooperation with the South Central Climate Adaptation Science Center","usgsCitation":"Moeser, C.D., Chavarria, S.B., and Wootten, A.M., 2021, Streamflow response to potential changes in climate in the Upper Rio Grande Basin: U.S. Geological Survey Scientific Investigations Report 2021–5138, 41 p., https://doi.org/10.3133/sir20215138.","productDescription":"Report: x, 41 p.; Data Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125477","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":49928,"text":"South Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":393890,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://webapps.usgs.gov/urgb-prms/","text":"Streamflow Response to Potential Changes in Climate—Upper Rio Grande Basin"},{"id":392955,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5138/sir20215138.pdf","text":"Report","size":"25.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5138"},{"id":392954,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5138/coverthb.jpg"},{"id":392958,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5138/images"},{"id":392956,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ML93QB","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Hydrologic simulations using projected climate data as input to the Precipitation-Runoff Modeling System (PRMS) in the Upper Rio Grande Basin (ver. 2.0, September 2021)"}],"country":"Mexico, United States","state":"Colorado, New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.7314453125,\n 30.410781790845864\n ],\n [\n -102.21679687500001,\n 30.410781790845864\n ],\n [\n -102.21679687500001,\n 38.30718056188316\n ],\n [\n -109.7314453125,\n 38.30718056188316\n ],\n [\n -109.7314453125,\n 30.410781790845864\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-12-16","noUsgsAuthors":false,"publicationDate":"2021-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Moeser, C. David 0000-0003-0154-9110","orcid":"https://orcid.org/0000-0003-0154-9110","contributorId":214563,"corporation":false,"usgs":true,"family":"Moeser","given":"C.","email":"","middleInitial":"David","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chavarria, Shaleene B. 0000-0001-8792-1010","orcid":"https://orcid.org/0000-0001-8792-1010","contributorId":223376,"corporation":false,"usgs":true,"family":"Chavarria","given":"Shaleene","email":"","middleInitial":"B.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":828490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wootten, Adrienne M. 0000-0001-6004-5823","orcid":"https://orcid.org/0000-0001-6004-5823","contributorId":270141,"corporation":false,"usgs":false,"family":"Wootten","given":"Adrienne","email":"","middleInitial":"M.","affiliations":[{"id":49928,"text":"South Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":828491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227007,"text":"70227007 - 2021 - Experimental tree mortality does not induce marsh transgression in a Chesapeake Bay low-lying coastal forest","interactions":[],"lastModifiedDate":"2021-12-27T14:25:45.009662","indexId":"70227007","displayToPublicDate":"2021-12-10T08:19:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Experimental tree mortality does not induce marsh transgression in a Chesapeake Bay low-lying coastal forest","docAbstract":"

Transgression into adjacent uplands is an important global response of coastal wetlands to accelerated rates of sea level rise. “Ghost forests” mark a signature characteristic of marsh transgression on the landscape, as changes in tidal inundation and salinity cause bordering upland tree mortality, increase light availability, and the emergence of tidal marsh species due to reduced competition. To investigate these mechanisms of the marsh migration process, we conducted a field experiment to simulate a natural disturbance event (e.g., storm-induced flooding) by inducing the death of established trees (coastal loblolly pine, Pinus taeda) at the marsh-upland forest ecotone. After this simulated disturbance in 2014, we monitored changes in vegetation along an elevation gradient in control and treatment areas to determine if disturbance can lead to an ecosystem shift from forested upland to wetland vegetation. Light availability initially increased in the disturbed area, leading to an increase in biodiversity of vegetation with early successional grass and shrub species. However, over the course of this 5-year experiment, there was no increase in inundation in the disturbed areas relative to the control and pine trees recolonized becoming the dominant plant cover in the disturbed study areas. Thus, in the 5 years since the disturbance, there has been no overall shift in species composition toward more hydrophytic vegetation that would be indicative of marsh transgression with the removal of trees. These findings suggest that disturbance is necessary but not sufficient alone for transgression to occur. Unless hydrological characteristics suppress tree re-growth within a period of several years following disturbance, the regenerating trees will shade and outcompete any migrating wetland vegetation species. Our results suggest that complex interactions between disturbance, biotic resistance, and slope help determine the potential for marsh transgression.

","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2021.782643","usgsCitation":"Walters, D., Carr, J., Hockaday, A., Jones, J.A., McFarland, E., Kovalenko, K., Kirwan, M.L., Cahoon, D., and Guntenspergen, G.R., 2021, Experimental tree mortality does not induce marsh transgression in a Chesapeake Bay low-lying coastal forest: Frontiers in Marine Science, v. 8, 782643, 12 p., https://doi.org/10.3389/fmars.2021.782643.","productDescription":"782643, 12 p.","ipdsId":"IP-131666","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450046,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.782643","text":"Publisher Index Page"},{"id":436096,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V4NJXW","text":"USGS data 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1940–2007","interactions":[],"lastModifiedDate":"2021-12-07T11:38:30.513661","indexId":"sim3482","displayToPublicDate":"2021-12-06T16:19:48","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3482","displayTitle":"Mean Annual Runoff and Annual Runoff Variability Map for Oklahoma, 1940–2007","title":"Mean annual runoff and annual runoff variability map for Oklahoma, 1940–2007","docAbstract":"

Hydrologic records used to create previously published maps depicting mean annual runoff are biased to a relatively dry period in Oklahoma history that was dominated by droughts. Therefore, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, developed an updated mean annual runoff and annual runoff variability map for Oklahoma and parts of adjacent States. The updated map, which is based on mean-annual-streamflow regression equations developed from available streamgage data through 2007, is assumed to be representative of the long-term mean annual runoff conditions. The map covers all 69 8-digit hydrologic units with at least 1 square mile of area in Oklahoma; those 8-digit hydrologic units contain 2,870 12-digit hydrologic units that provided the geographic framework for the analysis described in this report. Although parts of adjacent States are included in the study area, this report is primarily focused on providing a map of mean annual runoff and annual runoff variability for Oklahoma.

The mean annual runoff increased from less than 0.25 inch per year in the Panhandle of northwestern Oklahoma to more than 30 inches per year in the mountainous terrain of southeastern Oklahoma. The orientation and pattern of mean annual runoff contours in this report were comparable to those of previously published map reports. The annual runoff variability, or the difference between the 80-percent and 20-percent streamflow-duration statistics, increased from less than 0.25 inch per year in the Panhandle of northwestern Oklahoma to more than 40 inches per year in the mountainous terrain of southeastern Oklahoma. The annual runoff variability data were similar in orientation and pattern to the mean annual runoff contours; annual runoff variability generally increased proportionally with increasing mean annual runoff. The annual runoff variability was also greatest, therefore, in the mountainous terrain of southeastern Oklahoma.

The mean annual runoff and annual runoff variability were calculated at sampled points representing the outlets of 12-digit hydrologic units, so the map in this report is most representative of runoff conditions in rural, unregulated drainage basins at the 12-digit hydrologic-unit scale. The map was developed by using regression equations formulated on streamgage data for the entire period of record through 2007, but those equations are biased to the period 1940–2007 when streamgages became more numerous and distributed across Oklahoma. Therefore, the map is likely most representative of runoff conditions during the period 1940–2007. Because runoff is a function of climate variables that can change over time, caution is warranted when using the information in this report to project mean annual runoff and annual runoff variability conditions beyond 2007.

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U.S. Geological Survey
1505 Ferguson Lane
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","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-12-06","noUsgsAuthors":false,"publicationDate":"2021-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, S. Jerrod 0000-0002-9379-8167 sjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9379-8167","contributorId":981,"corporation":false,"usgs":true,"family":"Smith","given":"S.","email":"sjsmith@usgs.gov","middleInitial":"Jerrod","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827620,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, Elise M.","contributorId":269639,"corporation":false,"usgs":false,"family":"Sherrod","given":"Elise","email":"","middleInitial":"M.","affiliations":[{"id":18135,"text":"Oklahoma Water Resources Board","active":true,"usgs":false}],"preferred":false,"id":827621,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238745,"text":"70238745 - 2021 - Hydrometeorology and hydrology of flooding in Cape Fear River basin during Hurricane Florence in 2018","interactions":[],"lastModifiedDate":"2022-12-07T13:06:34.924368","indexId":"70238745","displayToPublicDate":"2021-12-06T07:01:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrometeorology and hydrology of flooding in Cape Fear River basin during Hurricane Florence in 2018","docAbstract":"

Hurricanes are the major flood generating mechanism dominating the upper tail of the peak discharge distribution over the Cape Fear River Basin (CFRB). In 2018, Hurricane Florence swamped CFRB as the ninth-most-destructive hurricane ever hit the United States and set new records of peak discharges over the main river channel and three out of five of its major tributaries. In this study, we examined the hydrometeorology and hydrology of this flood via combined observation and numerical experiment analyses. Our results suggest that the slow-motion in combination to the “L-shaped” path was the most distinctive feature of the hurricane that incurred catastrophic and widespread rainfall and flooding over CFRB. The total rainfall from the storm played a controlling role in the magnitude and spatial distribution of the flood peaks at basin scale. Above that, the spatial heterogeneities of rainfall distribution and hydrologic characteristics was responsible for the distinctive flood responses within the basin. The bi-peak shape of the flood hydrograph for the Deep River was due to the combined effects of rainfall distribution, land cover, and topographic gradient. The exceptional unit peak discharge over the Black River basin was associated with its drainage network structure, topographic gradient and rainfall distribution. The floodplain downstream of the Cape Fear River temporarily stored flood water and attenuated both the riverine floods from upstream and the compound flood over the coastal area. Furthermore, numerical analyses found that re-infiltration accounted for 76% of the total infiltration on average. Re-infiltration was superior to local infiltration over CFRB during Hurricane Florence.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2021.127139","usgsCitation":"Yin, D., Xue, G., Warner, J.C., Bao, D., Huang, Y., and Yu, W., 2021, Hydrometeorology and hydrology of flooding in Cape Fear River basin during Hurricane Florence in 2018: Journal of Hydrology, v. 603, no. Part D, 127139, 15 p., https://doi.org/10.1016/j.jhydrol.2021.127139.","productDescription":"127139, 15 p.","ipdsId":"IP-131752","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.lsu.edu/oceanography_coastal_pubs/1431","text":"Publisher Index Page"},{"id":410156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Fear River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.56206874563571,\n 33.81973951724899\n ],\n [\n -77.88120555106067,\n 33.910925705881354\n ],\n [\n -77.2442690142006,\n 34.45599193210546\n ],\n [\n -78.26693504492098,\n 35.4311680446702\n ],\n [\n -79.95811136692888,\n 36.14381729662\n ],\n [\n -80.99038782321952,\n 36.40940940873304\n ],\n [\n -81.58339770236566,\n 35.82391601747226\n ],\n [\n -80.66093789036115,\n 34.928524377901226\n ],\n [\n -79.4749181320694,\n 34.40466304791357\n ],\n [\n -78.56206874563571,\n 33.81973951724899\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"603","issue":"Part D","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yin, Dongxiao","contributorId":294535,"corporation":false,"usgs":false,"family":"Yin","given":"Dongxiao","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":858467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xue, George","contributorId":294533,"corporation":false,"usgs":false,"family":"Xue","given":"George","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":858468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bao, Daoyang","contributorId":294534,"corporation":false,"usgs":false,"family":"Bao","given":"Daoyang","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":858469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Yongjie","contributorId":298848,"corporation":false,"usgs":false,"family":"Huang","given":"Yongjie","email":"","affiliations":[{"id":64696,"text":"chool of Meteorology, University of Oklahoma, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":858493,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yu, Wei","contributorId":299740,"corporation":false,"usgs":false,"family":"Yu","given":"Wei","email":"","affiliations":[],"preferred":false,"id":858494,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229409,"text":"70229409 - 2021 - A statistical framework to track temporal dependence of chlorophyll–nutrient relationships with implications for lake eutrophication management","interactions":[],"lastModifiedDate":"2022-03-07T12:28:13.441591","indexId":"70229409","displayToPublicDate":"2021-12-06T06:25:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A statistical framework to track temporal dependence of chlorophyll–nutrient relationships with implications for lake eutrophication management","docAbstract":"

A reliable chlorophyll–nutrient relationship (CNR) is essential for lake eutrophication management. Although the spatial variability of CNRs has been extensively explored, temporal variations of CNRs at the individual lake scale has rarely been discussed. The paucity of information about temporal dependence in CNRs may in part be due to the lack of a suitable statistical framework that helps guide such investigations. In order to reveal temporal dependence of CNR, this study develop a novel statistical framework. In the framework, we employ quantile regression to generate overall (the entire dataset), annual (subsets for each year), and accumulative (subsets collected before a certain year) CNRs. We aim to 1) show biases of annual relationships by comparing the overall and annual relationships and 2) determine whether or not data accumulation is enough to develop a reliable CNR. We use Lake Champlain and Lake Kasumigaura as case studies to illustrate the necessary steps needed to utilize this novel framework. Results show that large interannual variations exist for CNRs. Accumulative relationships tend to converge to the overall relationship, indicating that overall relationships are reliable for informing lake-specific eutrophication management in the two case study lakes. The novel statistical framework that we propose for a procedure to estimate reliable CNRs is important for informing lake-specific eutrophication control decision-making processes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2021.127134","usgsCitation":"Qiu, Q., Liang, Z., Xu, Y., Matsuzaki, S.S., Komatsu, K., and Wagner, T., 2021, A statistical framework to track temporal dependence of chlorophyll–nutrient relationships with implications for lake eutrophication management: Journal of Hydrology, v. 603, no. Part D, 127134, 10 p., https://doi.org/10.1016/j.jhydrol.2021.127134.","productDescription":"127134, 10 p.","ipdsId":"IP-124914","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":450086,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2021.127134","text":"Publisher Index Page"},{"id":396776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"603","issue":"Part D","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qiu, Qianlinglin","contributorId":288047,"corporation":false,"usgs":false,"family":"Qiu","given":"Qianlinglin","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":837298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liang, Zhongyao","contributorId":288053,"corporation":false,"usgs":false,"family":"Liang","given":"Zhongyao","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":837302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, Yaoyang","contributorId":288048,"corporation":false,"usgs":false,"family":"Xu","given":"Yaoyang","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":837299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matsuzaki, Shin-ichiro S.","contributorId":288050,"corporation":false,"usgs":false,"family":"Matsuzaki","given":"Shin-ichiro","email":"","middleInitial":"S.","affiliations":[{"id":61688,"text":"National Institute for Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":837300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Komatsu, Kazuhiro","contributorId":288052,"corporation":false,"usgs":false,"family":"Komatsu","given":"Kazuhiro","affiliations":[{"id":61688,"text":"National Institute for Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":837301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837297,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226526,"text":"sir20215104 - 2021 - Simulating the effects of climate-related changes to air temperature and precipitation on streamflow and water temperature in the Meduxnekeag River watershed, Maine","interactions":[],"lastModifiedDate":"2022-04-14T16:02:19.852264","indexId":"sir20215104","displayToPublicDate":"2021-12-02T11:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5104","displayTitle":"Simulating the Effects of Climate-Related Changes to Air Temperature and Precipitation on Streamflow and Water Temperature in the Meduxnekeag River Watershed, Maine","title":"Simulating the effects of climate-related changes to air temperature and precipitation on streamflow and water temperature in the Meduxnekeag River watershed, Maine","docAbstract":"

Responsible stewardship of native fish populations and riparian plants in the Meduxnekeag River watershed in northeastern Maine is a high priority for the Houlton Band of Maliseet Indians. Understanding the potential changes in hydrology and water temperature as a result of climate change is important to this priority for evaluating future habitat conditions in the watershed. This report, prepared in cooperation with the Houlton Band of Maliseet Indians, documents and presents the results of a model using the Precipitation-Runoff Modeling System (PRMS), a hydrologic model designed to provide streamflow and water temperature simulations under predicted changes in precipitation and air temperature during the next century.

To estimate streamflows and water temperature in the Meduxnekeag River watershed, a PRMS model was developed and calibrated. By using the calibrated PRMS model, simulations were made for projected scenarios of 0, 5, 10, and 15 percent increases in precipitation and for increases in air temperature of 0.0, 3.6, 7.0, and 10.4 degrees Fahrenheit (°F). The increases in precipitation and temperature were applied to all the daily input values uniformly. These scenarios were based upon the results from 30 climate change models summarized in the National Climate Change Viewer. Streamflows and water temperatures modeled for different climate scenarios were compared with streamflows and water temperatures modeled with unadjusted climate inputs.

Overall, streamflow increased with increasing precipitation and decreased with increasing air temperature. Water temperature increased with increasing air temperature. At the outlet of the studied Meduxnekeag River watershed, with both a 15 percent increase in precipitation and a 10.4 °F increase in air temperature, the mean annual streamflow increased by 17 percent from 489 cubic feet per second (ft3/s) to 572 ft3/s, and the mean annual maximum streamflow decreased by 8.3 percent from 3,870 ft3/s to 3,550 ft3/s. At the same location and under the same scenario, the mean annual water temperature increased by 17.5 percent from 47.4 °F to 55.7 °F.

Significant changes in mean monthly streamflows were found with increasing air temperature. The PRMS model results showed that when air temperature was increased, there was an increase in mean monthly streamflow during the winter months and a decrease in mean monthly streamflow during the spring months. In addition, with a 10.4 °F increase in the air temperature, the month with the greatest monthly streamflow changed from April to December. In addition, the PRMS model estimated that the mean annual maximum snowpack in snow water equivalent for the watershed would decrease from 7.67 inches to 1.26 inches, and the mean annual date of the maximum snowpack would change from March 21 to January 28 with a 15 percent increase in precipitation and a 10.4 °F increase in air temperature.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215104","collaboration":"Prepared in cooperation with the Houlton Band of Maliseet Indians","usgsCitation":"Bjerklie, D.M., and Olson, S.A., 2021, Simulating the effects of climate-related changes to air temperature and precipitation on streamflow and water temperature in the Meduxnekeag River watershed, Maine: U.S. Geological Survey Scientific Investigations Report 2021–5104, 35 p., https://doi.org/10.3133/sir20215104.","productDescription":"Report: vi, 35 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123224","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":392380,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215104/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":392032,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5104/sir20215104.XML"},{"id":392030,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EB4H6H","text":"USGS data release","linkHelpText":"Data for simulating the effects of air temperature and precipitation changes on streamflow and water temperature in the Meduxnekeag River watershed, Maine"},{"id":392029,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5104/sir20215104.pdf","text":"Report","size":"20.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5104"},{"id":392031,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5104/images/"},{"id":392028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5104/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Meduxnekeag River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.302001953125,\n 45.92154267288144\n ],\n [\n -67.78289794921875,\n 45.92154267288144\n ],\n [\n -67.78289794921875,\n 46.26913887119721\n ],\n [\n -68.302001953125,\n 46.26913887119721\n ],\n [\n -68.302001953125,\n 45.92154267288144\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-11-30","noUsgsAuthors":false,"publicationDate":"2021-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Bjerklie, David M. 0000-0002-9890-4125 dmbjerkl@usgs.gov","orcid":"https://orcid.org/0000-0002-9890-4125","contributorId":3589,"corporation":false,"usgs":true,"family":"Bjerklie","given":"David","email":"dmbjerkl@usgs.gov","middleInitial":"M.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226652,"text":"sir20215133 - 2021 - Streambed scour of salmon (Oncorhynchus spp.) redds in the Sauk River, Northwestern Washington","interactions":[],"lastModifiedDate":"2021-12-03T00:21:45.583067","indexId":"sir20215133","displayToPublicDate":"2021-12-01T16:17:54","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5133","displayTitle":"Streambed Scour of Salmon (Oncorhynchus spp.) Redds in the Sauk River, Northwestern Washington","title":"Streambed scour of salmon (Oncorhynchus spp.) redds in the Sauk River, Northwestern Washington","docAbstract":"

The autumn and winter flood season of western Washington coincides with the incubation period of many Pacific salmon (Onchorhynchus spp.) populations. During this period, salmon embryos incubating within gravel nests called “redds” are vulnerable to mobilization of surrounding sediment during floods. As overlying sediment is transported downstream, the vertical position of the streambed can be lowered, a process termed streambed scour; thus developing salmon embryos may be destroyed resulting in decreasing egg-to-fry survival rates. The Sauk River, which drains a 1,900 km2 (733.5 mi2) area of the central Cascade Range of Washington State, provides spawning and rearing habitat for several species of Pacific salmon including Chinook salmon (O. tshawytscha), which were listed as threatened under the Endangered Species Act (ESA) in 1999. In order to assess the hydrologic conditions when streambed scour and concomitant geomorphic changes occur, accelerometer scour monitors (ASMs), which record the time when streambed scour lowers the streambed to the level of salmon egg pockets, were deployed in two geomorphically different reaches of the Sauk River to monitor scour during water year 2018. Nineteen ASMs were deployed in an upstream reach, which was largely confined by valley walls with vegetated, stable banks and low channel-migration rates near the confluence of the Sauk and White Chuck Rivers. Twelve additional ASMs were deployed in a downstream reach within an unconfined valley with unvegetated, unstable banks and high channel-migration rates between the town of Darrington and the confluence of the Sauk and Suiattle Rivers. During the ASM deployment, discharge measured at the U.S. Geological Survey (USGS) streamgage Sauk River above White Chuck River, near Darrington, Washington (12186000), peaked at 479 m3/s (16,900 ft3/s) with an estimated 0.18 probability of annual exceedance (5.7-year recurrence interval). During the flood season, large-scale geomorphic changes, including channel migration and bar deposition, were measured at the downstream reach, but only minimal geomorphic changes were measured at the upstream reach. ASMs deployed at the downstream reach were not recovered after the flood season and total scour depth was presumed to have exceeded ASM anchor depth. At the upstream reach, 7 of the 19 deployed ASMs were recovered after the flood season and all recovered ASMs recorded scour at discharges that equaled or exceeded 204 m3/s (7,210 ft3/s). The remaining 12 ASMs deployed at the upstream reach were not recovered and total scour depth was presumed to have exceeded ASM anchor depth. Collectively, this analysis enhances the ability of fisheries managers to forecast egg-to-fry survival rates of salmonids by determining the hydrologic conditions at which scour at the level of salmon redds initiates.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215133","collaboration":"Prepared in cooperation with the Sauk-Suiattle Indian Tribe","usgsCitation":"Gendaszek, A.S., 2021, Streambed scour of salmon (Oncorhynchus spp.) redds in the Sauk River, Northwestern Washington: U.S. Geological Survey Scientific Investigations Report 2021–5133, 19 p., https://doi.org/10.3133/sir20215133.","productDescription":"Report: iv, 19 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124695","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":392362,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95KOMTC","text":"USGS data release","description":"USGS data release.","linkHelpText":"Accelerometer scour monitor data on the Sauk River, Washington, Water Year 2018"},{"id":392360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5133/coverthb.jpg"},{"id":392361,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5133/sir20215133.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5133"}],"country":"United States","state":"Washington","otherGeospatial":"Sauk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.80816650390625,\n 48.31060120649363\n ],\n [\n -121.36871337890625,\n 48.31060120649363\n ],\n [\n -121.36871337890625,\n 48.6927734325279\n ],\n [\n -121.80816650390625,\n 48.6927734325279\n ],\n [\n -121.80816650390625,\n 48.31060120649363\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402

","tableOfContents":"","publishedDate":"2021-12-01","noUsgsAuthors":false,"publicationDate":"2021-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827597,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70260125,"text":"70260125 - 2021 - Selected crater and small caldera lakes in Alaska: Characteristics and hazards","interactions":[],"lastModifiedDate":"2024-10-29T16:56:34.784541","indexId":"70260125","displayToPublicDate":"2021-12-01T11:53:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Selected crater and small caldera lakes in Alaska: Characteristics and hazards","docAbstract":"

This study addresses the characteristics, potential hazards, and both eruptive and non-eruptive role of water at selected volcanic crater lakes in Alaska. Crater lakes are an important feature of some stratovolcanoes in Alaska. Of the volcanoes in the state with known Holocene eruptive activity, about one third have summit crater lakes. Also included are two volcanoes with small caldera lakes (Katmai, Kaguyak). The lakes play an important but not well studied role in influencing eruptive behavior and pose some significant hydrologic hazards. Floods from crater lakes in Alaska are evaluated by estimating maximum potential crater lake water volumes and peak outflow discharge with a dam-break model. Some recent eruptions and hydrologic events that involved crater lakes also are reviewed. The large volumes of water potentially hosted by crater lakes in Alaska indicate that significant flowage hazards resulting from catastrophic breaching of crater rims are possible. Estimates of maximum peak flood discharge associated with breaching of lake-filled craters derived from dam-break modeling indicate that flood magnitudes could be as large as 103–106 m3/s if summit crater lakes drain rapidly when at maximum volume. Many of the Alaska crater lakes discussed are situated in hydrothermally altered craters characterized by complex assemblages of stratified unconsolidated volcaniclastic deposits, in a region known for large magnitude (>M7) earthquakes. Although there are only a few historical examples of eruptions involving crater lakes in Alaska, these provide noteworthy examples of the role of external water in cooling pyroclastic deposits, acidic crater-lake drainage, and water-related hazards such as lahars and base surge.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2021.751216","usgsCitation":"Waythomas, C.F., 2021, Selected crater and small caldera lakes in Alaska: Characteristics and hazards: Frontiers in Earth Science, v. 9, 751216, 23 p., https://doi.org/10.3389/feart.2021.751216.","productDescription":"751216, 23 p.","ipdsId":"IP-132664","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467219,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.751216","text":"Publisher Index Page"},{"id":463360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -142.4292614840023,\n 61.7867815706897\n ],\n [\n -179,\n 61.7867815706897\n ],\n [\n -179,\n 49.606118935666444\n ],\n [\n -144.99994877731635,\n 56.83072738947416\n ],\n [\n -142.4292614840023,\n 61.7867815706897\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917093,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70226491,"text":"sir20215116 - 2021 - Simulation of groundwater budgets and travel times for watersheds on the north shore of Long Island Sound, with implications for nitrogen-transport studies","interactions":[],"lastModifiedDate":"2021-11-30T15:46:29.595385","indexId":"sir20215116","displayToPublicDate":"2021-11-30T09:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5116","displayTitle":"Simulation of Groundwater Budgets and Travel Times for Watersheds on the North Shore of Long Island Sound, With Implications for Nitrogen-Transport Studies","title":"Simulation of groundwater budgets and travel times for watersheds on the north shore of Long Island Sound, with implications for nitrogen-transport studies","docAbstract":"

Aquatic systems in and around the Long Island Sound (LIS) provide a variety of ecological and economic benefits, but in some areas of the LIS, aquatic ecosystems have become degraded by excess nitrogen. A substantial fraction of the nitrogen inputs to the LIS are transported through the groundwater-flow system. Because groundwater travel times in surficial aquifers can exceed 100 years, multiyear lags are introduced between inputs at the water table in recharge areas and discharge to inland or coastal receiving waters. The U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection and the U.S. Environmental Protection Agency’s Long Island Sound Study, developed a steady-state groundwater model of the watersheds draining from the northern shore of the LIS for the purpose of calculating groundwater budgets and travel times to coastal waters.

The model was developed by using the MODFLOW–NWT software and existing spatial data on aquifers, river networks, land-surface altitudes, land cover, groundwater recharge, and water use. Coastal waters were delineated on the basis of the National Wetland Inventory; all non-coastal waters were collectively termed “inland waters.” A coarse-resolution model was calibrated by using the PEST++ software, long-term records of water levels in 65 wells, stream altitudes from 477 streams, base-flow records for 14 streamgages that are relatively unaffected by withdrawals, and error metrics based on incorrectly simulated flooding and incorrectly simulated dry streams. The calibrated values were used in a fine-resolution model in which the mean absolute residuals were 4.5 meters for groundwater levels, 1.3 meters for stream altitudes, and 7,200 cubic meters per day (2.9 cubic feet per second) for base flow. About 89 percent of the terrestrial cells were correctly simulated with the water table below land surface, and nearly 90 percent of the cells representing streams were correctly simulated as having the water table above the stream bottom. Together, these metrics suggest that this model is robust for simulating regional-scale groundwater patterns.

Simulated groundwater budgets were compiled for the entire study area, for each HUC12 (Hydrologic Unit Code no. 12) watershed and its adjacent coastal waters, if applicable, within the study area, and for 14 coastal-embayment watersheds. Most groundwater (90.6 percent of inflows) discharged to inland waters, with smaller fractions to coastal waters (7.0 percent) and well withdrawals (2.4 percent). When computed for HUC12 watersheds with coastal discharge, the portions of groundwater discharging to coastal waters ranged from 0.02 to 66 percent of groundwater outflows, with a median of 13 percent. Within priority-embayment watersheds, the portions of groundwater discharging to coastal waters ranged from 2 to 56 percent, with a median of 15 percent.

Groundwater travel times also were simulated for the entire study area, for each HUC12 watershed and its adjacent coastal waters, if applicable, within the study area and for 14 priority coastal embayments. Within the entire study area, the median groundwater travel time was 1.9 years, with an interquartile range of 0.1 to 5.9 years. Sensitivity analysis of groundwater travel times within a subbasin in the study area indicates that the travel times are a function of the grid resolution, with coarser grids resulting in shorter median travel times. Travel times for groundwater discharging to coastal waters were similar to travel times for groundwater discharging to inland waters, with a median of 1.9 years. Median travel times for the HUC12 watersheds ranged from 0.9 to 53.5 years, with a median of 1.8 years. Among HUC12 watersheds that include coastal areas, travel times for groundwater discharging to coastal waters ranged from less than 1 to 61.6 years, with a median of 2.8 years. The HUC12 watersheds with the longest simulated travel times were in the urban area near New York City where the model performance is less accurate. Median travel times for groundwater discharging to coastal waters within the priority-embayment watersheds ranged from less than 1 to 18.6 years, with a median of 2.3 years.

A more focused analysis was conducted for the Niantic River watershed to demonstrate the applicability of the regional model to local-scale nitrogen-transport analyses by using nitrogen-input and -attenuation rates from literature sources. Nitrogen inputs were estimated by using land-cover-based loading factors, and attenuation was estimated by using attenuation factors based on geologic zones and soil properties. Based on this analysis, groundwater transports an estimated 22,000 kilograms of nitrogen per year (2.9 kilograms of nitrogen per hectare per year) to streams, rivers, and coastal waters within the Niantic River watershed. Approximately 36 percent of discharging nitrogen is from atmospheric-deposition sources, 38 percent is from fertilizers, and 26 percent is from septic systems. Most of the groundwater-transported nitrogen (88 percent) discharges first to streams and rivers, with only 12 percent discharging directly to coastal waters. Travel times for groundwater-transported nitrogen ranged from less than 1 day to more than 100 years, with a median of 1.6 years.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215116","collaboration":"Prepared in cooperation with the United States Environmental Protection Agency’s Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Barclay, J.R., and Mullaney, J.R., 2021, Simulation of groundwater budgets and travel times for watersheds on the north shore of Long Island Sound, with implications for nitrogen-transport studies: U.S. Geological Survey Scientific Investigations Report 2021–5116, 84 p., https://doi.org/10.3133/sir20215116.","productDescription":"Report: x, 84 p.; 2 Data Releases","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-117840","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":391933,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91TQ895","text":"USGS data release","linkHelpText":"Summary data on groundwater budgets and travel times for watersheds on the north shore of Long Island Sound"},{"id":391932,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BLHPIT","text":"USGS data release","linkHelpText":"MODFLOW–NWT and MODPATH groundwater flow models of steady-state conditions in coastal Connecticut and adjacent areas of New York and Rhode Island, as well as a nitrogen transport model of the Niantic River watershed"},{"id":391931,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5116/sir20215116.pdf","text":"Report","size":"30.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5116"},{"id":391930,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5116/coverthb.jpg"}],"country":"United States","state":"Connecticut, New York, Rhode Island","otherGeospatial":"Long island Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.9324951171875,\n 40.826280356677124\n ],\n [\n -71.45782470703125,\n 40.826280356677124\n ],\n [\n -71.45782470703125,\n 41.50857729743935\n ],\n [\n -73.9324951171875,\n 41.50857729743935\n ],\n [\n -73.9324951171875,\n 40.826280356677124\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-11-30","noUsgsAuthors":false,"publicationDate":"2021-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mullaney, John R. 0000-0003-4936-5046 jmullane@usgs.gov","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":1957,"corporation":false,"usgs":true,"family":"Mullaney","given":"John","email":"jmullane@usgs.gov","middleInitial":"R.","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827098,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237233,"text":"70237233 - 2021 - Hierarchical models improve the use of alligator abundance as an indicator","interactions":[],"lastModifiedDate":"2022-10-05T12:09:51.687767","indexId":"70237233","displayToPublicDate":"2021-11-24T07:07:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical models improve the use of alligator abundance as an indicator","docAbstract":"

Indicator species are species which can be monitored as an index to measure the overall health of an ecosystem. Crocodylians have been shown to be good indicators of wetland condition as they respond to changes in hydrology, can be efficiently monitored, and are a key part of ecosystem trophic relationships. Eye shine surveys at night are a standard method used to sample alligators, but because some individuals that are present in a study area may go undetected and the proportion of individuals counted is not constant over time, appropriate modeling is required to convert counts to estimates of abundance. We analyzed 13 years of American alligator (Alligator mississippiensis) survey count data from South Florida using an N-mixture model. Alligator abundance estimates were assigned to quartiles that were then represented as color coded categories of red, yellow, or green to provide a straightforward rating of Everglades restoration based on familiar stoplight coloring. These results were then compared to a previously used method in which unadjusted counts of these same data were assigned to color coded quartile categories. Water depth played a major role in the detection probability of alligators and the stoplight colors between the two methods matched 76% of the time. This suggests that the original stoplight score method provided a good overall snapshot of the trends in alligator abundance in the Everglades; however, the hierarchical models estimate abundance and trends of alligator abundance by incorporating detection probability thus providing unbiased estimates of abundance.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.108406","usgsCitation":"Farris, S.C., Waddle, J., Hackett, C.E., Brandt, L.A., and Mazzotti, F., 2021, Hierarchical models improve the use of alligator abundance as an indicator: Ecological Indicators, v. 133, 108406, 8 p., https://doi.org/10.1016/j.ecolind.2021.108406.","productDescription":"108406, 8 p.","ipdsId":"IP-135347","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":450140,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.108406","text":"Publisher Index Page"},{"id":407953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.100830078125,\n 24.806681353851964\n ],\n [\n -79.56298828125,\n 24.806681353851964\n ],\n [\n -79.56298828125,\n 26.78484736105119\n ],\n [\n -82.100830078125,\n 26.78484736105119\n ],\n [\n -82.100830078125,\n 24.806681353851964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"133","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Farris, Seth C.","contributorId":297226,"corporation":false,"usgs":false,"family":"Farris","given":"Seth","email":"","middleInitial":"C.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":853682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":222916,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackett, Caitlin E. 0000-0003-3934-4321","orcid":"https://orcid.org/0000-0003-3934-4321","contributorId":261435,"corporation":false,"usgs":true,"family":"Hackett","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":853684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Laura A.","contributorId":146646,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":853685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":853686,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254965,"text":"70254965 - 2021 - Using isotopic data to evaluate Esox lucius (Linnaeus, 1758) natal origins in a hydrologically complex river basin","interactions":[],"lastModifiedDate":"2024-06-12T00:49:20.647676","indexId":"70254965","displayToPublicDate":"2021-11-22T19:47:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Using isotopic data to evaluate Esox lucius (Linnaeus, 1758) natal origins in a hydrologically complex river basin","docAbstract":"
Otolith microchemistry has emerged as a powerful technique with which to identify the natal origins of fishes, but it relies on differences in underlying geology that may occur over large spatial scales. An examination of how small a spatial scale on which this technique can be implemented, especially in water bodies that share a large proportion of their flow, would be useful for guiding aquatic invasive species control efforts. We examined trace isotopic signatures in northern pike (Esox lucius) otoliths to estimate their provenance between two reservoirs in the Upper Yampa River Basin, Colorado, USA. This is a challenging study area as these reservoirs are only 11-rkm apart on the same river and thus share a high proportion of their inflow. We found that three isotopes (86Sr, 137Ba, and 55Mn) were useful in discriminating between these reservoirs, but their signatures varied annually, and the values overlapped. Strontium isotope ratios (87Sr/86Sr) were different between sites and relatively stable across three years, which made them an ideal marker for determining northern pike provenance. Our study demonstrates the usefulness of otolith microchemistry for natal origin determination within the same river over a relatively small spatial scale when there are geologic differences between sites, especially geologic differences underlying tributaries between sites.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes6040067","usgsCitation":"Fitzpatrick, R., Winkelman, D.L., and Johnson, B., 2021, Using isotopic data to evaluate Esox lucius (Linnaeus, 1758) natal origins in a hydrologically complex river basin: Fishes, v. 6, no. 4, 67, 14 p., https://doi.org/10.3390/fishes6040067.","productDescription":"67, 14 p.","ipdsId":"IP-134717","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":450149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes6040067","text":"Publisher Index Page"},{"id":429941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.9498723827442,\n 40.21929782464798\n ],\n [\n -106.74308073055617,\n 40.21929782464798\n ],\n [\n -106.74308073055617,\n 40.39596925752221\n ],\n [\n -106.9498723827442,\n 40.39596925752221\n ],\n [\n -106.9498723827442,\n 40.21929782464798\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Ryan M.","contributorId":338176,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Ryan M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":902995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Brett M.","contributorId":338178,"corporation":false,"usgs":false,"family":"Johnson","given":"Brett M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":902996,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70226712,"text":"70226712 - 2021 - Nutrient and suspended-sediment concentrations in the Maumee River and tributaries during 2019 rain-induced fallow conditions","interactions":[],"lastModifiedDate":"2022-01-07T16:05:22.102391","indexId":"70226712","displayToPublicDate":"2021-11-22T08:21:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient and suspended-sediment concentrations in the Maumee River and tributaries during 2019 rain-induced fallow conditions","docAbstract":"

Above average precipitation from October 2018 through July 2019 in the Maumee River (R.) Basin resulted in 29% of cropland left fallow, providing a glimpse of potential effects from decreased nutrient application. Ongoing monitoring at 15 water-quality sites on the Maumee R. upstream from Defiance enabled comparison with 2017, which was hydrologically similar to 2019 in precipitation and streamflow. In 2019, nitrate (as nitrogen; NO3-N) for March-July was significantly less than previous years (2015–2018), but the response for phosphorus (P) was more complicated. Relative to 2017, total P (TP) was lower at 7 of 15 sites, but higher at 7, reflecting higher suspended sediment (SS). Dissolved P (DP) was generally lower, but less different than NO3; DP was higher at 3 sites. DP-P:NO3-N was generally higher in 2019, DP-P:TP was lower, and there was less TP relative to SS. Overall, less P was in the system in 2019. However smaller streams showed a large range of difference between 2019 and 2017 for all constituents, indicating variability in land management and physiography. In contrast, all constituents were lower in 2019 in larger (>5000 km2) streams, including the Maumee R. near Defiance, where the difference in NO3 (−37%) exceeded that for TP (−16%), DP (−10%), and SS (−20%). Differences in these relations among N, P, and SS indicate that P was available from legacy sources that are more difficult to distinguish during typical agricultural production years and that some material from 2019 was stored in the system upstream from the largest sites.

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Numerical models for tides, storm surge, and wave runup have demonstrated ability to accurately define spatially varying flood surfaces. However these models are typically too computationally expensive to dynamically simulate the full parameter space of future oceanographic, atmospheric, and hydrologic conditions that will constructively compound in the nearshore to cause both extreme event and nuisance flooding during the 21st century. A surrogate modeling framework of waves, winds, and tides is developed in this study to efficiently predict spatially varying nearshore and estuarine water levels contingent on any combination of offshore forcing conditions. The surrogate models are coupled with a time-dependent stochastic climate emulator that provides efficient downscaling for hypothetical iterations of offshore conditions. Together, the hybrid statistical-dynamical framework can assess present day and future coastal flood risk, including the chronological characteristics of individual flood and wave-induced dune overtopping events and their changes into the future. The framework is demonstrated at Naval Base Coronado in San Diego, CA, utilizing the regional Coastal Storm Modeling System (CoSMoS; composed of Delft3D and XBeach) as the dynamic simulator and Gaussian process regression as the surrogate modeling tool. Validation of the framework uses both in-situ tide gauge observations within San Diego Bay, and a nearshore cross-shore array deployment of pressure sensors in the open beach surf zone. The framework reveals the relative influence of large-scale climate variability on future coastal flood resilience metrics relevant to the management of an open coast artificial berm, as well as the stochastic nature of future total water levels.

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