The range of 187Re/188Os values measured from samples of five organic-rich lacustrine mudstones units in the Eocene Green River Formation in the easternmost Uinta Basin covaries with organic matter diversity driven by changing water column conditions. A set of samples from the Douglas Creek Member has the highest pristane/phytane ratio and lowest β-carotane/n-C30 ratio compared to overlying units, indicating deposition in an oxic-anoxic environment with low salinity that would have allowed for the accumulation of a diverse assemblage of aquatic organisms. These samples define the broadest 187Re/188Os range of 1504. In contrast, samples from the R6 and Mahogany zones possess lower pristane/phytane ratios and higher β-carotane/n-C30 ratios indicating deposition in a more restricted lacustrine environment with elevated salinities and alkalinities that would have limited aquatic organic matter diversity. The R6 and Mahogany zones have the narrowest range of 187Re/188Os values measured in this study of 254.9 and 154.6, respectively. As noted by previous workers, these results suggest that organic matter diversity plays a primary role in determining the range of 187Re/188Os ratios in a sample set, and in turn the uncertainty of Re-Os age determinations from organic-rich sedimentary rocks.
The Re-Os data from the R3 zone and R6 zone yield ages of 49.7 ± 3.4 Ma and 42.0 ± 18 Ma, respectively, which are statistically indistinguishable based on 2σ uncertainty from three previously reported Re-Os age determinations and those provided by 40Ar/39Ar geochronology of interbedded volcanic ash beds. Although the age uncertainty is high, these findings further highlight the importance of Re-Os geochronology in lacustrine basins, particularly those with thick mudstone successions that lack volcanic ash layers, reliable biostratigraphy, or magnetostratigraphic control. In these cases, even ages with large uncertainties can be useful to constrain burial history and thermal history models.
Together, the initial 187Os/188Os ratios of five sets of samples analyzed from the Uinta Basin define the largest Os isotope stratigraphic record from any lacustrine basin compiled to date and record a shift from a value of 1.40 to 1.48 between the R3 and R4 zones in the lower part of the Parachute Creek Member. This small shift may signify a change in the chemical weathering products that entered the lake preserved 20 to 50 m above the contact between the Douglas Creek and the lower Parachute Creek members during a period when the basin transitioned from a shallow lake with mostly open hydrology to an alkaline lake with more frequent basin restrictions.
The effects of a warming climate will alter the hydrological cycles of arid southwestern U.S. reservoirs which primarily support agricultural needs, provide flood control, and generate hydroelectric power while secondarily supporting fish communities and sport fishing opportunities. The success of littoral spawning fishes depends on the timing and variability of water levels. The onset of drought between 2017 and 2018 provided an opportunity to evaluate the timing of hatch dates and relative abundance of young-of-year Largemouth Bass Micropterus salmoides across two water years of varying water temperatures and water levels in a southwestern U.S. reservoir. A retrospective analysis of otoliths in young-of-year Largemouth Bass revealed similar hatch dates in 2017 (14 April–29 May) and 2018 (13 April–28 May) despite differences in water temperature and water level rate of change. Median water temperature during hatch dates was greater in 2017 (median 19.0°C, range 14.3–24.4°C) than 2018 (17.6°C, range 13.5–21.7°C). Water level rate of change during hatch dates in 2017 was positive (+3.1 to +13.1 cm/d), which reflected reservoir filling. In contrast, water level rate of change during hatch dates in 2018 was negative (−8.5 to −0.6 cm/d), which reflected reservoir receding. Relative abundance of young-of-year fish was greater in 2017 (21.7 fish/h) when the reservoir was filling compared with relative abundance in 2018 (6.8 fish/h) when the reservoir was receding. The median growth rate was greater in 2017 (1.02 mm/d) when the reservoir was filling than in 2018 (0.82 mm/d) when the reservoir was receding. Despite differences in water temperature and contrasting reservoir levels between the two water years, the Largemouth Bass population in a southwest U.S. reservoir exhibited similar hatch dates reported for the species in southeastern and northeastern U.S. reservoirs. While water demand in the 21st century may exceed availability, the opportunity exists to collaborate with water managers to benefit Largemouth Bass populations in southwestern reservoirs.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-071","usgsCitation":"Vaisvil, A., Caldwell, C.A., and Frey, E., 2022, Water-level fluctuations and water temperature effects on young-of-year Largemouth Bass in a southwest irrigation reservoir: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 534-543, https://doi.org/10.3996/JFWM-21-071.","productDescription":"10 p.","startPage":"534","endPage":"543","ipdsId":"IP-133206","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-071","text":"Publisher Index Page"},{"id":429779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","county":"Sierra County","otherGeospatial":"Elephant Butte Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.12656805641583,\n 33.33034159767031\n ],\n [\n -107.22643051078117,\n 33.33034159767031\n ],\n [\n -107.22643051078117,\n 33.13668854992092\n ],\n [\n -107.12656805641583,\n 33.13668854992092\n ],\n [\n -107.12656805641583,\n 33.33034159767031\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Vaisvil, Alexander","contributorId":337757,"corporation":false,"usgs":false,"family":"Vaisvil","given":"Alexander","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":902658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frey, Eric","contributorId":337759,"corporation":false,"usgs":false,"family":"Frey","given":"Eric","email":"","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":902659,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70233942,"text":"70233942 - 2022 - Environmental DNA methods for ecological monitoring and biodiversity assessment in estuaries","interactions":[],"lastModifiedDate":"2022-10-17T15:43:31.657314","indexId":"70233942","displayToPublicDate":"2022-06-25T07:13:32","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":"Environmental DNA methods for ecological monitoring and biodiversity assessment in estuaries","docAbstract":"Environmental DNA (eDNA) detection methods can complement traditional biomonitoring to yield new ecological insights in aquatic systems. However, the conceptual and methodological frameworks for aquatic eDNA detection and interpretation were developed primarily in freshwater environments and have not been well established for estuaries and marine environments that are by nature dynamic, turbid, and hydrologically complex. Environmental context and species life history are critical for successful application of eDNA methods, and the challenges associated with eDNA detection in estuaries were the subject of a symposium held at the University of California Davis on January 29, 2020 (https://marinescience.ucdavis.edu/engagement/past-events/edna). Here, we elaborate upon topics addressed in the symposium to evaluate eDNA methods in the context of monitoring and biodiversity studies in estuaries. We first provide a concise overview of eDNA science and methods, and then examine the San Francisco Estuary (SFE) as a case study to illustrate how eDNA detection can complement traditional monitoring programs and provide regional guidance on future potential eDNA applications. Additionally, we offer recommendations for enhancing communication between eDNA scientists and natural resource managers, which is essential for integrating eDNA methods into existing monitoring programs. Our intent is to create a resource that is accessible to those outside the field of eDNA, especially managers, without oversimplifying the challenges or advantages of these methods.
Tactile-feeding wading birds, such as wood storks and white ibises, require high densities of prey such as small fishes and crayfish to support themselves and their offspring during the breeding season. Prey availability in wetlands is often determined by seasonal hydrologic pulsing, such as in the subtropical Everglades, where spatial distributions of prey can vary through time, becoming heterogeneously clumped in patches, such as ponds or sloughs, as the wetland dries out. In this mathematical modeling study, we selected two possible foraging strategies to examine how they impact total energetic intake over a time scale of one day. In the first, wading birds sample prey patches without a priori knowledge of the patches' prey densities, moving from patch to patch, staying long enough to estimate the prey density, until they find one that meets a predetermined satisfactory threshold, and then staying there for a longer period. For this case, we solve for a wading bird's expected prey intake over the course of a day, given varying theoretical probability distributions of patch prey densities across the landscape. In the second strategy considered, it is assumed that the wading bird samples a given number of patches, and then uses memory to return to the highest quality patch. Our results show how total intake over a day is impacted by assumptions of the parameters governing the spatial distribution of prey among patches, which is a key source of parameter uncertainty in both natural and managed ecosystems. Perhaps surprisingly, the foraging strategy that uses a prey density threshold generally led to higher maximum potential prey intake than the strategy for using memory to return to the best patch sampled. These results will contribute to understanding the foraging of wading birds and to the management of wetlands.
","language":"English","publisher":"AIMS Press","doi":"10.3934/mbe.2022361","usgsCitation":"Lee, H.W., DeAngelis, D.L., Yurek, S., and Tennenbaum, S., 2022, Wading bird foraging on a wetland landscape: A comparison of two strategies: Mathematical Biosciences and Engineering, v. 19, no. 8, p. 7687-7718, https://doi.org/10.3934/mbe.2022361.","productDescription":"32 p.","startPage":"7687","endPage":"7718","ipdsId":"IP-138910","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447339,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3934/mbe.2022361","text":"Publisher Index Page"},{"id":401534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Hyo Won","contributorId":292184,"corporation":false,"usgs":false,"family":"Lee","given":"Hyo","email":"","middleInitial":"Won","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":844003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":844004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216733,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tennenbaum, Stephen","contributorId":292180,"corporation":false,"usgs":false,"family":"Tennenbaum","given":"Stephen","email":"","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":844006,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232276,"text":"sir20225050 - 2022 - Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020","interactions":[],"lastModifiedDate":"2022-09-27T12:34:49.194432","indexId":"sir20225050","displayToPublicDate":"2022-06-22T14:13:29","publicationYear":"2022","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":"2022-5050","displayTitle":"Mapping the Altitude of the Top of the Dockum Group and Paleochannel Analysis Using Surface Geophysical Methods On and Near Cannon Air Force Base in Curry County, New Mexico, 2020","title":"Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020","docAbstract":"The hydrogeology on and near Cannon Air Force Base (AFB) in eastern New Mexico was assessed to gain a better understanding of preferential groundwater flow paths through paleochannels. In and near the study area, paleochannels incised the top surface of the Dockum Group (Chinle Formation) and were subsequently filled in with electrically resistive coarse-grained sediments of the overlying Ogallala Formation, resulting in a preferential groundwater flow path in the form of a paleochannel network. A better understanding of the spatial characteristics of this preferential groundwater flow path is needed to support ongoing efforts to remediate groundwater contamination at Cannon AFB. Therefore, the U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, used surface geophysical resistivity methods and data compiled from previous studies to better understand the spatial distribution and characteristics of the paleochannel network incised into the top of the Dockum Group.
Previous studies have shown these paleochannels incised into the top of the Dockum Group with increasing resolution, but limited borehole data on and near Cannon AFB continued to make accurately mapping the top of Dockum Group challenging. For this study, surface geophysical resistivity measurements in the form of time-domain electromagnetic soundings made by the U.S. Geological Survey were used in conjunction with data previously published by Architecture, Engineering, Construction, Operations, and Management and borehole data compiled from the New Mexico Water Rights Reporting System database to prepare an updated map of the top of the Dockum Group that includes the location and characteristics of paleochannels incised into the top of the Dockum Group (Chinle Formation). A total of 149 borehole picks (determinations of the tops and bases of geologic units and their hydrogeologic-unit equivalents) were obtained from previous studies, along with 72 additional borehole picks from the New Mexico Water Rights Reporting System database and 43 picks from newly collected time-domain electromagnetic soundings. The data were gridded and contoured using Oasis Montaj v. 9.8.1.
The updated map of the top of Dockum Group has many areas of uncertainty greater than 20 feet, because there are not enough data for the gridding process to reliably determine a value. However, this interpretation of the altitude of the top of the Dockum Group represents a substantial improvement in data resolution compared to previous studies.
Two methodologies were used to evaluate paleochannels incised in the top of the Dockum Group across the study area: (1) trend-removal grid analysis and (2) analysis with Esri’s ArcMap Hydrology toolset. These two paleochannel analysis techniques show groundwater flow direction as well as areas having the deepest saturated thickness. Hydrologically, these techniques show where aquifer storage is highest (in the deepest parts of the paleochannel network), as well as the spatial distribution of preferential groundwater flow paths (the paleochannels). The analyses indicate a large paleochannel trending to the southeast, with smaller channels feeding in from the west. Areas where groundwater management could be more beneficial are indicated by locations where these flow lines intersect the deeper parts of the paleochannel.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225050","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Payne, J.D., Teeple, A.P., McDowell, J., Wallace, D., and Hancock, W.A., 2022, Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020: U.S. Geological Survey Scientific Investigations Report 2022–5050, 21 p., https://doi.org/10.3133/sir20225050.","productDescription":"Report: iv, 21 p.; 2 Data Releases; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-125577","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":402462,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225050/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402441,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5050/images"},{"id":402444,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/543e6b86e4b0fd76af69cf4c","text":"USGS data release","linkHelpText":"1 meter digital elevation models (DEMs)—USGS National Map 3DEP downloadable data collection"},{"id":402443,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P6KWR5","text":"USGS data release","linkHelpText":"Surface geophysical data used for mapping the top of the Dockum Group on Cannon Air Force Base in Curry County, New Mexico, 2020"},{"id":402442,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://nmwrrs.ose.state.nm.us/nmwrrs/wellSurfaceDiversion.html","text":"New Mexico Office of the State Engineer online database","linkHelpText":"—New Mexico Water Rights Reporting System"},{"id":402438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5050/coverthb.jpg"},{"id":402439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.pdf","text":"Report","size":"1.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5050"},{"id":402440,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.XML"}],"country":"United States","state":"New Mexico","county":"Curry County","otherGeospatial":"Cannon Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.375,\n 34.333\n ],\n [\n -103.25,\n 34.333\n ],\n [\n -103.25,\n 34.458333\n ],\n [\n -103.375,\n 34.458333\n ],\n [\n -103.375,\n 34.333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
The U.S. Geological Survey, in cooperation with the Montana Department of Transportation, installed cameras and large-scale particle image velocimetry (LSPIV) recording equipment at four sites where the U.S. Geological Survey and Montana Department of Transportation are monitoring bridge scour using other methods. Determination of stream velocities is an important component of hydraulic engineering, river ecology, and fluvial geomorphology. LSPIV is an emerging technique that can be used to estimate stream surface velocities and streamflow using video cameras. Video from the camera is referenced to known locations on streambanks, and postprocessed using computer software that calculates water surface velocity and flow direction between video frames.
The goal of the study was to determine if LSPIV can increase the accuracy of current bridge scour prediction methods using video recordings from 2019 to 2021. Scour around piers is one of the primary failure mechanisms for bridges and poses threats to public safety and interstate commerce. LSPIV installations can capture the flow velocities and directions near bridge piers where other measurement methods might fail or be too dangerous. Additional benefits to the LSPIV technique were continuous data collection throughout the hydrologic cycle and enhanced safety of the methods for estimating velocity magnitude and direction during flood events. Limitations of the LSPIV technique included the angle of the camera to incoming flow; video recordings that were not usable because of ice cover, night, or high winds; and vegetation along the streambank that interfered with water flow analysis. Future applications of the LSPIV technique may continue to improve the processing of the video and reduce limitations for this process.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223040","usgsCitation":"Armstrong, D.W., Holnbeck, S.R., and Chase, K.J., 2022, Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana: U.S. Geological Survey Fact Sheet 2022–3040, 2 p., https://doi.org/10.3133/fs20223040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-137820","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":402153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3040/coverthb.jpg"},{"id":402154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3040"},{"id":402155,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.XML"},{"id":402156,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3040/images"},{"id":402157,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223040/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":501493,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113199.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 45\n ],\n [\n -110.5,\n 45\n ],\n [\n -110.5,\n 46\n ],\n [\n -112.5,\n 46\n ],\n [\n -112.5,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Mauka-to-makai (mountain to sea in the Hawaiian language) hydrologic connectivity – commonly referred to as ridge-to-reef – directly affects biogeochemical processes and socioecological functions across terrestrial, freshwater, and marine systems. The supply of freshwater to estuarine and nearshore environments in a ridge-to-reef system supports the food, water, and habitats utilized by marine fauna. In addition, the ecosystem services derived from this land-to-sea connectivity support social and cultural practices (hereafter referred to as socio-cultural) including fishing, aquaculture, wetland agriculture, religious ceremonies, and recreational activities. To effectively guide island resource management, a better understanding of the linkages from ridge-to-reef across natural and social usages is critical, particularly in the context of climate change, with anticipated increasing temperature and shifting precipitation patterns. The objective of this study was to identify spatial linkages that promote multiple and diverse uses, following the ridge-to-reef concept, at an island-wide scale to identify regions of high conservation importance for aquatic resources. We selected the Island of Maui as a study representative of many Pacific islands. Diverse datasets, including agricultural lands within watersheds, wetland locations, presence of stream species, indicators of freshwater input from streams, coral cover, nearshore fish biomass, socio-cultural data such as fishpond locations, wetland taro cultivation, beach recreation use, and lastly the dynamically downscaled Coupled Model Intercomparison Project Phase (CMIP5) future climate projections scenarios (Representative Concentration Pathway (RCP) 4.5 & 8.5) were used to examine the spatial linkages through hydrological connectivity from land to the sea. Zonation spatial planning software was used to prioritize areas of high management and conservation value and to help inform aquatic resources management. The resulting prioritized areas included many minimally disturbed watersheds in east Maui and western nearshore and coastal zones that are adjacent to diverse coral reefs. These results are driven by the importance of fish biomass and coral reef distribution as well as traditional wetland taro cultivation and coastal access points for recreation. These results underline the importance of examining ridge-to-reef systems for aquatic resource management and including important social and cultural values in resource management upon planning adaptation strategies for climate change. Improving our understanding of diverse natural and socio-cultural influences on habitat conditions and their values in these areas provides an opportunity to strategically plan future management and conservation actions.
This report assesses the status and trends of selected ecological health indicators of the Upper Mississippi River System (UMRS) based on the data collected and analyzed by the Long Term Resource Monitoring element of the Upper Mississippi River Restoration program, supplemented with data from other sources. This report has four objectives: providing a brief introduction of the UMRS, including its significance, history, modern-day stressors, and recent research; using ecological indicators to describe the status of the river system and where and how it has changed from circa 1993 to 2019; discussing management and restoration implications of these changes; and highlighting the fundamental role of long-term monitoring in the understanding, management, and restoration of large-floodplain rivers.
The data were collected in the six Long Term Resource Monitoring element study reaches that spanned much of the UMRS and the various gradients contained therein. These study reaches included Navigation Pools 4, 8, 13, and 26; the part of the Unimpounded Reach of the Upper Mississippi River between Grand Tower and Cairo, Illinois; and the La Grange Pool on the Illinois River. The indicators included in this report describe the status and trends for the hydrology, geomorphology, floodplain vegetation, water quality, vegetation, and fishes of the UMRS. Many of the indicators of river ecosystem health changed significantly over the nearly 30 years of our evaluation. However, there was substantial spatial variability in the magnitude and timing of those changes among study reaches. Few indicators changed everywhere or nowhere; most indicators changed in some reaches but not others. The quantitative assessments of these indicators describe how the conditions of the river differ across hydrogeomorphic and climate gradients and through time and are intended to support the restoration and management of the UMRS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221039","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Species Management Research Program and Land Management Research Program","usgsCitation":"Houser, J.N., ed., 2022, Ecological status and trends of the Upper Mississippi and Illinois Rivers (ver. 1.1, July 2022): U.S. Geological Survey Open-File Report 2022–1039, 199 p., https://doi.org/10.3133/ofr20221039.","productDescription":"xiv, 199 p.","numberOfPages":"220","onlineOnly":"N","ipdsId":"IP-125605","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":402335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1039/coverthb2.jpg"},{"id":402336,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1039/ofr20221039.pdf","text":"Report","size":"41.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1039"},{"id":403771,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2022/1039/versionHist.txt","size":"3.11 kB","linkFileType":{"id":2,"text":"txt"}},{"id":501772,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113198.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, North Dakota, South Dakota, Wisconsin","otherGeospatial":"Illinois River, upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.329833984375,\n 46.172222978455395\n ],\n [\n -90.340576171875,\n 46.30140615437332\n ],\n [\n -92.384033203125,\n 46.49082901981415\n ],\n [\n -93.087158203125,\n 46.74738913515841\n ],\n [\n -93.262939453125,\n 47.42065432071318\n ],\n [\n -94.3505859375,\n 47.76148371616669\n ],\n [\n -95.712890625,\n 47.30903424774781\n ],\n [\n -96.1083984375,\n 46.912750956378915\n ],\n [\n -96.1083984375,\n 46.18743678432541\n ],\n [\n -96.6357421875,\n 45.89000815866184\n ],\n [\n -97.393798828125,\n 45.867062714815475\n ],\n [\n -97.591552734375,\n 45.72152152227954\n ],\n [\n -96.50390625,\n 44.56699093657141\n ],\n [\n -95.43823242187499,\n 43.51668853502906\n ],\n [\n -95.042724609375,\n 42.70665956351041\n ],\n [\n -94.559326171875,\n 41.82045509614034\n ],\n [\n -94.02099609375,\n 41.20345619205131\n ],\n [\n -93.043212890625,\n 39.66491373749128\n ],\n [\n -92.61474609375,\n 39.172658670429946\n ],\n [\n -91.790771484375,\n 38.84826438869913\n ],\n [\n -90.977783203125,\n 38.762650338334154\n ],\n [\n -90.76904296874999,\n 38.736946065676\n ],\n [\n -91.14257812499999,\n 38.35888785866677\n ],\n [\n -91.58203125,\n 37.43997405227057\n ],\n [\n -90.8349609375,\n 36.86204269508728\n ],\n [\n -89.18701171875,\n 37.046408899699564\n ],\n [\n -88.72558593749999,\n 37.87485339352928\n ],\n [\n -88.87939453125,\n 38.685509760012\n ],\n [\n -87.69287109375,\n 40.863679665481676\n ],\n [\n -86.748046875,\n 41.178653972331674\n ],\n [\n -86.781005859375,\n 41.5579215778042\n ],\n [\n -87.593994140625,\n 41.46742831254425\n ],\n [\n -87.86865234374999,\n 42.374778361114195\n ],\n [\n -88.494873046875,\n 43.31718491566705\n ],\n [\n -89.3408203125,\n 43.810747313446996\n ],\n [\n -89.6484375,\n 43.937461690316646\n ],\n [\n -89.40673828125,\n 44.50434127765394\n ],\n [\n -89.329833984375,\n 46.172222978455395\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: June 22, 2022; Version 1.1: July 14, 2022","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
The natal environment can have long-term fitness consequences for individuals, particularly via ‘silver spoon’ or ‘environmental matching’ effects. Invasive species could alter natal effects on native species by changing species interactions, but this potential remains unknown. Using 17 years of data on 2588 individuals across the entire US breeding range of the endangered snail kite (Rostrhamus sociabilis), a wetland raptor that feeds entirely on Pomacea snails, we tested for silver spoon and environmental matching effects on survival and movement and whether the invasion of a non-native snail may alter outcomes. We found support for silver spoon effects, not environmental matching, on survival that operated through body condition at fledging, explained by hydrology in the natal wetland. When non-native snails were present at the natal site, kites were in better condition, individual condition was less sensitive to hydrology, and kites fledged across a wider range of hydrologic conditions, leading to higher survival that persisted for at least 10 years. Movement between wetlands was driven by the current (adult) environment, and birds born in both invaded and uninvaded wetlands preferred to occupy invaded wetlands post-fledging. These results illustrate that species invasions may profoundly impact the role of natal environments on native species.
The Yellowstone Volcano Observatory (YVO) is a consortium of nine Federal, State, and academic agencies that: (1) provides timely monitoring and hazards assessment of volcanic, hydrothermal, and earthquake activity in and around Yellowstone National Park, and (2) conducts research to develop new approaches to volcano monitoring and better understand volcanic activity in the Yellowstone region and elsewhere. The U.S. Geological Survey (USGS) arm of YVO is also responsible for monitoring and reporting on volcanic activity in the Intermountain West of the United States.
The previous YVO monitoring plan for the Yellowstone region spanned 2006–2015 and focused on strengthening the region-wide coverage, or backbone, of monitoring systems (Yellowstone Volcano Observatory, 2006). The goals of that plan have largely been achieved thanks to significant investments in instrumentation and infrastructure, especially by the National Science Foundation EarthScope Plate Boundary Observatory (now known as the Network Of The Americas, or NOTA) and the American Reinvestment and Recovery Act. This revision of the monitoring plan, covering 2022–2032, builds upon these improvements to monitoring systems in the Yellowstone region while also accounting for new insights into the dynamics of the area’s seismic, volcanic, and hydrothermal activity. These additional improvements are designed to fill gaps in the monitoring network and to better understand and track hazards associated with hydrothermal processes. These improvements include:
The 2022–2032 monitoring plan for the Yellowstone volcanic system also proposes to improve monitoring of hydrothermal areas to better understand these dynamic systems and their associated hazards. To date, only a single seismometer has been placed within one of Yellowstone National Park’s geyser basins because seismic noise associated with boiling water can hinder interpretation of overall seismic and magmatic activity, but this concern has been mitigated by improvements to backbone monitoring. Deployment of geophysical, geochemical, hydrological, and geological monitoring instruments in geyser basins will be accompanied by campaigns to measure gas and water chemistry and flux, as well as aerial and satellite surveys of gas and thermal emissions.
Close collaboration between YVO member institutions and other research agencies is needed to achieve these monitoring goals and to use the derived data to advance understanding of how Yellowstone Caldera and similar volcanic systems work. At the same time, attention must be paid to minimize the impact of monitoring efforts and infrastructure on the environment. YVO thus commits to serving as stewards of the natural, cultural, and historical resources in and around Yellowstone National Park while maximizing scientific gain for the betterment of society.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225032","collaboration":"Prepared in cooperation with Yellowstone National Park, University of Utah, UNAVCO, University of Wyoming, Montana Bureau of Mines and Geology, Idaho Geological Survey, Wyoming State Geological Survey, and Montana State University","usgsCitation":"Yellowstone Volcano Observatory, 2022, Volcano and earthquake monitoring plan for the Yellowstone Caldera system, 2022–2032: U.S. Geological Survey Scientific Investigations Report 2022–5032, 23 p., https://doi.org/10.3133/sir20225032.","productDescription":"v, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-120517","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":402337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5032/covrthb.jpg"},{"id":402338,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5032/sir20225032.pdf","text":"Report","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5032"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Caldera, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.04156494140625,\n 44.24716652494939\n ],\n [\n -110.20111083984375,\n 44.24716652494939\n ],\n [\n -110.20111083984375,\n 44.77111175531263\n ],\n [\n -111.04156494140625,\n 44.77111175531263\n ],\n [\n -111.04156494140625,\n 44.24716652494939\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Yellowstone Volcano Observatory
U.S. Geological Survey
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Streamgage record extension methods such as the maintenance of variance Type 3 (MOVE3) method improve flood frequency estimates at a target streamgage by incorporating information from a nearby, hydrologically similar index streamgage. Bulletin 17C recommends using a variation of the MOVE3 method to estimate values at the target streamgage for only a subset of the available data at the index streamgage to account for uncertainty in values estimated using MOVE3. Bulletin 17C recommends the most recent index streamgage data be used for the subset unless these data misrepresent the skewness of the extended record. However, no method is provided to select the subset if the most recent data are inappropriate. The objective of this study is to develop such a method to select the subset of peaks by extending Bulletin 17C’s MOVE3 methodology to control the skewness of the extended streamgage record. The new method allows the extended record skewness to be informed by all available peak-flow data at the index streamgage while accurately computing the variance and resulting confidence intervals for flood frequency estimates. An example is presented comparing three different variations of MOVE3 record extension, which produce extended streamgage records with the same mean and variance, but different values of skewness. In the example, the difference in skewness between the three methods causes the results of flood frequency analysis for the 1% annual exceedance probability flood to differ by about 15%, illustrating the importance of considering skewness when using MOVE3 record extension.
The transition of sagebrush-dominated (Artemisia spp.) shrublands to pinyon (Pinus spp.) and juniper (Juniperus spp.) woodlands markedly alters resource-conserving vegetation structure typical of these landscapes. Land managers and scientists in the western United States need knowledge and predictive tools for assessment and effective targeting of tree-removal treatments to conserve or restore sagebrush vegetation and associated hydrologic function. This study developed modeling approaches to quantify the hydrologic vulnerability and erosion potential of sagebrush rangelands in the later stages of woodland encroachment and in response to commonly applied tree-removal treatments. Using experimental data from multiple sites in the Great Basin Region, USA, and process-based knowledge from decade-long vegetation and rainfall simulation studies at those sites, we (1) assessed the capability of the Rangeland Hydrology and Erosion Model (RHEM) to accurately predict patch-scale (12 m2) measured runoff and erosion from tree canopy and intercanopy hydrologic functional units in untreated and burned woodlands 9 years postfire, and (2) developed and evaluated multiple RHEM approaches/frameworks to model aggregated effects of tree canopy and intercanopy areas on patch- and hillslope-scale (50 m length) runoff and erosion processes in untreated and treated (burned, cut, and masticated) woodlands. The RHEM accurately predicted measured runoff and sediment yield from patch-scale rainfall simulations as partitioned on untreated and treated tree canopy and intercanopy areas and effectively parameterized the dominant controls on runoff and erosion process in woodlands. With few exceptions, evaluated hillslope-scale RHEM frameworks similarly predicted reduced hydrologic vulnerability and erosion potential for conditions 9 years following tree removal by burning, cutting, and mastication treatments. Regressions of RHEM-predicted hillslope runoff, sediment, and hydraulic/erosion parameters with bare ground and ground cover attributes indicate all RHEM frameworks effectively represented the dominant controls on hydrologic and erosion processes for rangelands and woodlands. The results provide RHEM frameworks and recommendations for assessing hydrologic vulnerability and erosion potential on woodland-encroached sites and predicting the effectiveness of tree removal to reestablish a water and soil resource-conserving vegetation structure on sagebrush rangelands. We anticipate our RHEM or similar modeling approaches may be applicable to analogous water-limited landscapes elsewhere subject to woody plant encroachment.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4145","usgsCitation":"Williams, C.J., Pierson, F.B., Al-Hamdan, O.Z., Nouwakpo, S.K., Johnson, J.C., Polyakov, V.O., Kormos, P.R., Shaff, S., and Spaeth, K.E., 2022, Assessing runoff and erosion on woodland-encroached sagebrush steppe using the Rangeland Hydrology and Erosion Model: Ecosphere, v. 13, no. 6, e4145, 32 p., https://doi.org/10.1002/ecs2.4145.","productDescription":"e4145, 32 p.","ipdsId":"IP-137960","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.4145","text":"External Repository"},{"id":402401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.14427185058592,\n 39.44679856427205\n ],\n [\n -115.10032653808594,\n 39.44679856427205\n ],\n [\n -115.10032653808594,\n 39.47807557129829\n ],\n [\n -115.14427185058592,\n 39.47807557129829\n ],\n [\n -115.14427185058592,\n 39.44679856427205\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.47871398925781,\n 40.20824570152502\n ],\n [\n -112.46429443359375,\n 40.20824570152502\n ],\n [\n -112.46429443359375,\n 40.2203056748532\n ],\n [\n -112.47871398925781,\n 40.2203056748532\n ],\n [\n -112.47871398925781,\n 40.20824570152502\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, C. 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Kossi","contributorId":292514,"corporation":false,"usgs":false,"family":"Nouwakpo","given":"S.","email":"","middleInitial":"Kossi","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Justin C.","contributorId":261635,"corporation":false,"usgs":false,"family":"Johnson","given":"Justin","email":"","middleInitial":"C.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":844923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Polyakov, Viktor O.","contributorId":292516,"corporation":false,"usgs":false,"family":"Polyakov","given":"Viktor","email":"","middleInitial":"O.","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kormos, Patrick R.","contributorId":292517,"corporation":false,"usgs":false,"family":"Kormos","given":"Patrick","email":"","middleInitial":"R.","affiliations":[{"id":62927,"text":"National Oceanic and Atmospheric Administration - National Weather Service, US Department of Commerce","active":true,"usgs":false}],"preferred":false,"id":844925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shaff, Scott 0000-0001-8978-9260 sshaff@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-9260","contributorId":5126,"corporation":false,"usgs":true,"family":"Shaff","given":"Scott","email":"sshaff@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844926,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spaeth, Kenneth E.","contributorId":9387,"corporation":false,"usgs":true,"family":"Spaeth","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":844927,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70232243,"text":"sir20225055 - 2022 - Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","interactions":[],"lastModifiedDate":"2022-09-27T12:37:10.865008","indexId":"sir20225055","displayToPublicDate":"2022-06-17T07:23:22","publicationYear":"2022","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":"2022-5055","displayTitle":"Assessment of Streamflow Trends in the Eastern Dakotas, Water Years 1960–2019","title":"Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","docAbstract":"Hydrologic extremes, whether periods of drought or flooding, are occurring more frequently with greater severity and can have substantial economic impacts. Along with flooding, the timing and volume of streamflow also is changing across the United States. The focus of this report is to characterize a unique trend in mean annual streamflow occurring in eastern North and South Dakota, hereafter referred to as the eastern Dakotas, that is not being observed anywhere else in the conterminous United States.
Streamflow records for 1,853 U.S. Geological Survey streamgages obtained from the U.S. Geological Survey National Water Information System database with a continuous record of mean annual streamflow during water years 1960–2019 were included in this study. Using a Kendall tau statistical test (p-value less than or equal to 0.10), 573 streamgages had a statistically significant upward trend in mean annual streamflow and are primarily located in the Midwest and northeastern United States. Of the streamgages, 182 had a statistically significant downward trend and are located primarily in the western and southeastern States. Several sites had increases in streamflow between 100 and 500 percent. Most of the streamgages with the highest increases in mean annual streamflow are along the same rivers in the eastern Dakotas, regardless of basin size.
A comparison of mean annual streamflow of the last decade (2010–19) to the first decade (1960–69) of the study period shows that the largest increases in annual streamflow volumes in the United States also are in the eastern Dakotas. Among all 1,853 streamgages in the United States, the Sheyenne River near Warwick, North Dakota (U.S. Geological Survey station 05056000), has the greatest percent change, with an increase of 486 percent. Several factors may be contributing to increasing trends in streamflow in the eastern Dakotas and may include, in part, precipitation changes owing to climatic variation within the region, geologic makeup of the subsurface, and land-use changes. A better understanding of these research areas will help producers, resource managers, and infrastructure engineers to make more informed environmental and economic decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225055","usgsCitation":"Norton, P.A., Delzer, G.C., Valder, J.F., Tatge, W.S., and Ryberg, K.R., 2022, Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019: U.S. Geological Survey Scientific Investigations Report 2022–5055, 11 p., https://doi.org/10.3133/sir20225055.","productDescription":"Report: iv, 11 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-134818","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":402316,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225055/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5055/images"},{"id":402284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5055"},{"id":402285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.XML"},{"id":402283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5055/coverthb.jpg"},{"id":402287,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.7666015625,\n 42.90816007196054\n ],\n [\n -96.50390625,\n 42.90816007196054\n ],\n [\n -96.50390625,\n 48.980216985374994\n ],\n [\n -100.7666015625,\n 48.980216985374994\n ],\n [\n -100.7666015625,\n 42.90816007196054\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
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1608 Mountain View Road, Rapid City, SD 57702
For agricultural areas facing water scarcity, sustainable water use policy relies on irrigation information that is timely and at a high resolution, but existing publicly available water use data are often insufficient for monitoring compliance or understanding the influence of policy on individual farmer decisions. This study attempts to fill this data gap by using remote sensing to map annual irrigation quantity at the field-scale within the central Ogallala aquifer region of the United States. We compiled in situ annual irrigation volume data at the field scale in the Republican River Basin of Colorado for 2015–2018 and at the Public Land Survey System (PLSS) section scale in western Kansas for 2000–2016, which served as reference data in random forest models that relied on Landsat-based actual evapotranspiration from the Operational Simplified Surface Energy Balance model (SSEBop) along with maps of irrigated area, Landsat spectral indices, climate, soils, and derived hydrologic variables. The models explained 87% of the variability in irrigation volume in Colorado and 75% in Kansas, but accuracy declined when transferring the models in spatial cross-validation (Colorado R2 =0.81; Kansas R2 =0.51) and temporal cross-validation (Colorado R2 =0.82; Kansas R2 =0.68). Predicted annual totals of irrigation volume in western Kansas had a mean absolute error of 11.9%, which was slightly higher than the average annual change of 11%. Use of predicted irrigation maps also lead to an underestimated effect size for a water use restriction policy in Kansas. These results indicate that field- and section-scale irrigation can be mapped with reasonable accuracy within a region and time period that has adequate sample data, but that methods may need to be improved for applying the models more broadly in areas that lack extensive in situ irrigation data to support further research on water use and aid in structuring policy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2022.107764","usgsCitation":"Filippelli, S.S., Sloggy, M.R., Vogeler, J.C., Manning, D.T., Goemans, C., and Senay, G.B., 2022, Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region: Agricultural Water Management, v. 271, 107764, 15 p., https://doi.org/10.1016/j.agwat.2022.107764.","productDescription":"107764, 15 p.","ipdsId":"IP-137832","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":488115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2022.107764","text":"Publisher Index Page"},{"id":428798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado Kansas","otherGeospatial":"Ogallala aquifer, Republican River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.00825131829713,\n 36.98969791337646\n ],\n [\n -97.51352205922755,\n 36.9837502608661\n ],\n [\n -97.3406085961385,\n 38.44391430535899\n ],\n [\n -98.0932074623356,\n 38.87773029390084\n ],\n [\n -99.65122819650178,\n 39.098871590431884\n ],\n [\n -99.26469253047271,\n 40.0142028593921\n ],\n [\n -102.06717715371995,\n 40.032435593038315\n ],\n [\n -102.11261804171953,\n 40.992555768008174\n ],\n [\n -104.06597899342937,\n 40.93187765306061\n ],\n [\n -104.48051561524214,\n 39.43819239944247\n ],\n [\n -103.69918549158801,\n 38.5715258326463\n ],\n [\n -102.64452864991789,\n 38.27521479596666\n ],\n [\n -102.4653590264147,\n 36.967066532161525\n ],\n [\n -102.00825131829713,\n 36.98969791337646\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"271","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Filippelli, Steven S 0000-0001-7291-0888","orcid":"https://orcid.org/0000-0001-7291-0888","contributorId":336733,"corporation":false,"usgs":false,"family":"Filippelli","given":"Steven","email":"","middleInitial":"S","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sloggy, Matthew R 0000-0001-5129-0755","orcid":"https://orcid.org/0000-0001-5129-0755","contributorId":336734,"corporation":false,"usgs":false,"family":"Sloggy","given":"Matthew","email":"","middleInitial":"R","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":900930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogeler, Jody C.","contributorId":264796,"corporation":false,"usgs":false,"family":"Vogeler","given":"Jody","email":"","middleInitial":"C.","affiliations":[{"id":54555,"text":"umn","active":true,"usgs":false}],"preferred":false,"id":900931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manning, Dale T 0000-0001-6465-5530","orcid":"https://orcid.org/0000-0001-6465-5530","contributorId":336735,"corporation":false,"usgs":false,"family":"Manning","given":"Dale","email":"","middleInitial":"T","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goemans, Christopher 0000-0003-4930-4278","orcid":"https://orcid.org/0000-0003-4930-4278","contributorId":336736,"corporation":false,"usgs":false,"family":"Goemans","given":"Christopher","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":900934,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232199,"text":"70232199 - 2022 - Quantifying relations between altered hydrology and fish community responses for streams in Minnesota","interactions":[],"lastModifiedDate":"2022-06-13T15:49:06.160966","indexId":"70232199","displayToPublicDate":"2022-06-13T10:45:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1460,"text":"Ecological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying relations between altered hydrology and fish community responses for streams in Minnesota","docAbstract":"Altered hydrology is a stressor on aquatic life for several streams in Minnesota, but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota. Best subsets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic explanatory metrics (i.e., duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and six categories of biological response metrics (i.e., composition, habitat, life history, reproductive, tolerance, trophic) computed from fish community samples, as well as fish-based indices of biotic integrity (FIBI) scores and FIBI scores normalized to the an impairment threshold of the corresponding stream class (FIBI_BCG4). Three hydrologic datasets were used to examine rRelations between altered hydrology and fish community responses were examined at three different temporal scalesusing three hydrologic datasets that represented periods of record, long-term changes, and short-term changes to flow regimes in streams of Minnesota.","language":"English","publisher":"Springer","doi":"10.1186/s13717-022-00383-z","usgsCitation":"Ziegeweid, J.R., Johnson, G.D., Krall, A.L., Fitzpatrick, K., and Levin, S., 2022, Quantifying relations between altered hydrology and fish community responses for streams in Minnesota: Ecological Processes, v. 11, 41, 25 p., https://doi.org/10.1186/s13717-022-00383-z.","productDescription":"41, 25 p.","ipdsId":"IP-125704","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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\"}}]}","volume":"11","noUsgsAuthors":false,"publicationDate":"2022-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Gregory D.","contributorId":201568,"corporation":false,"usgs":false,"family":"Johnson","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":844552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krall, Aliesha L. 0000-0003-2521-5043 adiekoff@usgs.gov","orcid":"https://orcid.org/0000-0003-2521-5043","contributorId":176545,"corporation":false,"usgs":true,"family":"Krall","given":"Aliesha","email":"adiekoff@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzpatrick, Kara","contributorId":292426,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Kara","email":"","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":844554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Levin, Sara B. 0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844555,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232544,"text":"70232544 - 2022 - A water quality barometer for Chesapeake Bay: Assessing spatial and temporal patterns using long-term monitoring data","interactions":[],"lastModifiedDate":"2022-07-07T11:56:20.480306","indexId":"70232544","displayToPublicDate":"2022-06-13T06:51:51","publicationYear":"2022","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":"A water quality barometer for Chesapeake Bay: Assessing spatial and temporal patterns using long-term monitoring data","docAbstract":"This paper develops a barometer that indexes water quality in the Chesapeake Bay and summarizes quality over spatial regions and temporal periods. The barometer has a basis in risk assessment and hydrology, and is a function of three different metrics of water quality relative to numerical criteria: relative frequency of criterion attainment; magnitude of deviation from a numerical criterion; and duration of criterion attainment. Metrics associated with these features are calculated at the station level, allowing flexibility for simultaneously evaluating multiple stressors, different designated uses, and physical characteristics of the water. The barometer score is then created as a geometric mean of the three metrics. The water quality barometer (WQB) station scores may be spatially aggregated to report habitat scores across a spectrum of spatial resolutions (e.g., management segment, tidal subsystem, or the whole tidal bay). Dissolved oxygen measurements in the Chesapeake Bay collected during summer seasons of 1985 to 2020 are used to evaluate water quality. The WQB score and its bootstrapped confidence interval are reported at the station, segment, tidal subsystem and whole tidal bay levels. Notably, water quality interpreted through application of the WQB with dissolved oxygen concentration data and averaged over the 29-year period of record is good (i.e. protects aquatic living resources) in tributaries such as the James River, Rappahannock River and others; but is not as good in areas such as the Upper Tributaries and the York River. Recent summaries indicate that while the water quality is improving in much of the bay and its tidal tributaries, however, there is an indication of decline in quality in the period 20182020, especially in the upper regions of the Bay. The barometer is designed around using the time series data produced by the Chesapeake Bay Programs annual monitoring strategy; the approach has application to other large water bodies with large scale monitoring programs with extended time series or for integrating information from environmental sensor systems.
Increasing demand for river water now conflicts with an increasing desire to maintain riparian ecosystems. Efficiently managing river flows for riparian vegetation requires an understanding of the time scale of flow effects, but this information is limited by the absence of long-term studies of vegetation change in response to flow variation. To investigate the influence of short- and long-term flow variability and dam operation on riparian vegetation, we determined the occurrence of 107 plant species in 133 permanent plots of known inundating discharge along the Gunnison River in Colorado on five different occasions between 1990 and 2013. Individual species moved up and down the gradient of inundating discharge coincident with increases and decreases in mean annual flow, and the correlations between flow and species occurrence were strongest when flows were weighted by time before vegetation sampling with a median half-life of 1.5 years. Some tall, rhizomatous, perennial species, however, responded to flows on a longer time scale. Logistic regression of species occurrence showed a significant relation with inundation duration for 70 out of 107 species. Plot species richness and total vegetative cover decreased in association with desiccation at low inundation durations and with fluvial disturbance at high inundation durations. Within-plot similarity in species occurrence between years decreased strongly with increasing inundation duration. Moderate inundation durations were dominated by tall, rhizomatous, perennial herbs, including invasive Phalaris arundinacea (reed canary grass). Over the 23-year study period, species richness declined, and the proportion of rhizomatous perennials increased, consistent with the hypothesis that decreases in flow peaks and increases in low flows caused by flow regulation have decreased establishment opportunities for disturbance-dependent species. In summary, annual-scale changes in vegetation were strongly influenced by flow variation, and decadal-scale changes were influenced by decreases in fluvial disturbance from upstream flow regulation beginning decades prior to the onset of this study.
The rate and timing of hydrologically forced landslides is a complex function of precipitation patterns, material properties, topography, and groundwater hydrology. In the simplest form, however, slopes fail when subsurface pore pressure grows large enough to exceed the Mohr-Coulomb failure criterion. The capacity for pore pressure rise in a landslide is determined in part by the thickness of the unsaturated zone above the water table, which itself is set by weathering patterns that should have predictable patterns across different lithologies. To investigate how this structure affects landslide behavior, we exploit a multi-year record of precipitation, pore pressure, and velocity from Oak Ridge earthflow, a slow-moving landslide set in Franciscan mélange, northern California, USA. In conjunction with electrical resistivity tomography and hydraulic conductivity measurements, these data show that Oak Ridge has a thin weathered profile that is comparable in thickness to other mélange landslides in California. We propose that due to the inherently thin vadose zone, mélange landscapes experience an unusually high water table that frequently brings them close to movement; however, the capacity to increase stress is limited by the small amount of dynamic storage available. Instead, excess pore pressure is shed via springs and saturation overland flow once the water table reaches the surface. Linkages between weathering patterns, hydrology, and deformation can explain behavior patterns exhibited by Franciscan mélange earthflows across a large precipitation gradient.
Nearly all of the wetlands in the coastal zone of Lake Erie have been degraded or destroyed since the 1860s, and most of those that remain are separated from their watersheds by earthen dikes. Hydrologic isolation of these wetlands disrupts ecosystem benefits typical to Great Lakes coastal wetlands, particularly the ability to trap sediments and retain nutrients when inundated by runoff and lake water. High-frequency measurements of turbidity and discharge were taken in 2013 and 2014 to observe turbidity and water flow dynamics to estimate total phosphorus flux of a hydrologically reconnected diked wetland pool in the Crane Creek-Lake Erie wetland complex. Modeled estimates suggest the reconnected pool retained 8% of the total phosphorus loading in 2013 and 10% in 2014, which included short periods of phosphorus export to Lake Erie. Water flowing out of the wetland generally had lower turbidity than inflowing water, but flux in and out of the pool varied seasonally and was linked to changes in lake-levels, seiche dynamics, and weather conditions. More frequent storms, higher winds, and stronger seiches in the spring and fall created turbidity patterns that suggest more phosphorus retention than in summer or winter. Estimates suggest that phosphorus was released during the summer when higher lake levels and the absence of frequent storms, larger short-term seiche oscillations, and potentially soil oxygen availability were driving flux dynamics. This study demonstrated that reestablishing lake hydrology through reconnection of wetland pools can reduce loading and alter timing of delivery of total phosphorus to Lake Erie.
","language":"English","publisher":"MDPI","doi":"10.3390/w14121853","usgsCitation":"Carter, G., Kowalski, K., and Eggleston, M., 2022, Turbidity and estimated phosphorus retention in a reconnected Lake Erie coastal wetland: Water, v. 14, no. 2, 1853, 12 p., https://doi.org/10.3390/w14121853.","productDescription":"1853, 12 p.","ipdsId":"IP-110303","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":447485,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w14121853","text":"Publisher Index Page"},{"id":435812,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5C3B","text":"USGS data release","linkHelpText":"Total phosphorus and water flux at a restored hydrologic connection at Ottawa National Wildlife Refuge in 2013 and 2014"},{"id":402325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Crane Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.24014663696289,\n 41.59772934193236\n ],\n [\n -83.17886352539062,\n 41.59772934193236\n ],\n [\n -83.17886352539062,\n 41.64764694964725\n ],\n [\n -83.24014663696289,\n 41.64764694964725\n ],\n [\n -83.24014663696289,\n 41.59772934193236\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Glenn 0000-0001-6630-7513","orcid":"https://orcid.org/0000-0001-6630-7513","contributorId":292490,"corporation":false,"usgs":false,"family":"Carter","given":"Glenn","email":"","affiliations":[],"preferred":false,"id":844792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":844793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eggleston, Michael 0000-0003-1068-3290","orcid":"https://orcid.org/0000-0003-1068-3290","contributorId":204833,"corporation":false,"usgs":true,"family":"Eggleston","given":"Michael","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":844794,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232327,"text":"70232327 - 2022 - Water storage decisions and consumptive use may constrain ecosystem management under severe sustained drought","interactions":[],"lastModifiedDate":"2022-10-17T15:32:14.964305","indexId":"70232327","displayToPublicDate":"2022-06-08T07:45:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Water storage decisions and consumptive use may constrain ecosystem management under severe sustained drought","docAbstract":"Drought has impacted the Colorado River basin for the past 20 years and is predicted to continue. In response, decisions about how much water should be stored in large reservoirs and how much water can be consumptively used will be necessary. These decisions have the potential to limit riverine ecosystem management options through the effect water-supply decisions have on reservoir elevations. We used projected hydrology and river temperatures to compare the outcome of combinations of water storage scenarios and consumptive use limits on metrics associated with ecosystem management of the Colorado River in Grand Canyon. Ecosystem management metrics included the ability to implement designer flows, temperature suitability for fishes, and fragmentation. We compared current water management operations to prioritizing storage in either Lake Mead or Lake Powell combined with three levels of consumptive use. Projected reservoir levels limited environmental flow delivery and increased fragmentation regardless of where water was stored if consumptive use was not limited. Warmer river temperatures associated with low reservoir levels are likely, creating suitable conditions for non-native species of concern, such as smallmouth bass. Water storage decisions provided variability and management flexibility, but water storage was less important when less water was available, highlighting the importance of keeping water in the system to provide flexibility for achieving ecosystem goals.
Mechanistic river models capable of simulating hydrodynamics and stream temperature are valuable tools for investigating thermal conditions and their relation to streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In the Willamette River Basin in northwestern Oregon, a two-dimensional, hydrodynamic water-quality model (CE‑QUAL‑W2) has been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature. By simulating the managed releases of water and various temperatures from the large Willamette Valley Project dams upstream of the modeling domain, these models can be used to investigate riverine temperature conditions and their relation to streamflow to determine where and when conditions are most challenging for threatened fish populations and how dam operations and flow management can affect and optimize thermal conditions in the river.
The original models were initially developed to simulate conditions in spring–autumn of 2001 and 2002. This report documents (1) the upgrade of the river models to CE‑QUAL‑W2 version 4.2 and (2) the update of those models to simulate conditions that occurred from March through October of 2011, 2015, and 2016. These years were selected to represent a range of climatic and hydrologic conditions in the Willamette River Basin, including a “cool, wet” year (2011), a “hot, dry” year (2015), and a “normal” year (2016). Six submodels comprise the modeling system updated in this report; each submodel can be run independently or run with the others as a system. These models include the Coast Fork and Middle Fork Willamette River submodel, which includes the Coast Fork and Middle Fork Willamette Rivers, the Row River, and Fall Creek; the McKenzie River submodel, which includes the South Fork McKenzie River downstream of Cougar Dam and the McKenzie River from its confluence with the South Fork McKenzie River to its mouth; the South Santiam River submodel, which comprises the South Santiam River from Foster Dam to the Santiam River; the North Santiam and Santiam River submodel, which includes the Santiam River and the North Santiam River downstream of Big Cliff Dam; the Upper Willamette River submodel, which includes the Willamette River from Eugene to Salem; and the Middle Willamette River submodel, which includes the Willamette River from Salem to Willamette Falls near Oregon City.
The models included in this report were originally developed, calibrated, and documented by other researchers. As part of the model updates described here, some model parameters were adjusted to improve stability and decrease runtime. Boundary conditions including meteorological, hydrologic, and thermal parameters were developed and updated for model years 2011, 2015, and 2016. In many cases, the data sources used to drive the 2001 and 2002 models were no longer available, which required the use of new data sources, the determination of a proxy record, or the development of appropriate estimation techniques. Goodness-of-fit statistics for the updated models show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 °C and often nearing 0.5 °C, depending on the individual submodel, and a reasonably low bias. The subdaily mean error for the South Santiam River submodel produced the highest bias of any of the submodels. Goodness-of-fit statistics indicate that the results may be biased cool (ranging from -0.43 °C in 2016 to -0.80 °C in 2011 for subdaily results), but the only water temperature data available for comparison on the South Santiam River is itself estimated, and those estimates are known to be too high in summer. Depending on future modeling needs, that submodel may warrant further refinement, along with additional data collection to properly define and minimize any model bias.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221017","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Rounds, S.A., and Buccola, N.L., 2022, Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon: U.S. Geological Survey Open-File Report 2022–1017, 73 p., https://doi.org/10.3133/ofr20221017.","productDescription":"Report: x, 73 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119723","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401872,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.XML"},{"id":401871,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1017/images"},{"id":401815,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225035","text":"SIR 2022-5035 —","linkHelpText":"The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids"},{"id":401814,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225034","text":"SIR 2022-5034 —","linkHelpText":"Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon"},{"id":501762,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113157.htm","linkFileType":{"id":5,"text":"html"}},{"id":401754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1017/coverthb.jpg"},{"id":401755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1017"},{"id":401756,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908DXKH","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for the Willamette River and major tributaries below U.S. Army Corps of Engineers dams—2011, 2015, and 2016"},{"id":401813,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225006","text":"SIR 2022-5006 —","linkHelpText":"Tracking heat in the Willamette River system, Oregon"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.134765625,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The Milk and St. Mary Rivers are international waterways straddling the United States and Canada and traversing four Tribal Nations before draining into the Missouri and South Saskatchewan Rivers respectively. Management of water resources in the region is challenged by the complexity of stakeholder interests, the limitations of existing management infrastructure, and by a limited characterization of the long-term streamflow and hydroclimatic variability across the area. We used existing records of natural streamflow to investigate the relationships between seasonal climate variability and differences in the timing and volume of flow from the headwaters to the prairie tributaries. Then, using a network of tree-ring chronologies to reconstruct records of past streamflow, we assessed whether drought risk relates to these sub-basin specific differences and if drought events experienced during the observational period are representative of those that have occurred over the long-term. Observed climate-flow relationships suggest that outside of the mountain headwaters, where precipitation dominates the hydrograph, streamflow variability on lower reaches of the Milk River is particularly sensitive to winter temperatures. This sensitivity was reflected by severe drought conditions over the prairies during the 2000s, implying potentially large future flow reductions with warming. The streamflow reconstructions show sub-basin specific drought risks that also imply greater temperature driven drought severities across the prairie tributaries. Within the mountain and foothill sub-basins numerous past drought episodes exceed the magnitude and duration of observational period events, which implies the potential for future water supply management challenges stemming from severe, long-duration droughts coupled with the negative hydrologic effects of warmer temperatures.
Groundwater levels have declined since the 1940s in the Wailuku area of central Maui, Hawai‘i, on the eastern flank of West Maui volcano, mainly in response to increased groundwater withdrawals. Available data since the 1980s also indicate a thinning of the freshwater lens and an increase in chloride concentrations of pumped water from production wells. These trends, combined with projected increases in demand for groundwater in central Maui, have led to concerns over groundwater availability and have highlighted a need to improve general understanding of the hydrologic effects of proposed groundwater withdrawals in the Waihe‘e, ‘Īao, and Waikapū areas of central Maui.
A numerical groundwater model was constructed to simulate the flow and salinity of groundwater in central Maui. The model simulates the effects of changes in groundwater withdrawals and recharge on water levels, freshwater-lens thicknesses, and chloride concentrations of pumped water from production wells. The model incorporates updated water-budget estimates of groundwater recharge from infiltration and direct recharge, seepage in stream channels, and inflow from inland areas. Mean annual groundwater recharge from infiltration and direct recharge was estimated using a daily water-budget model and the most current data, including the distributions of monthly rainfall and potential evapotranspiration, for the study area for nine historical periods from 1926 through 2012: 1926–69, 1970–79, 1980–84, 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, and 2010–12. The water-budget model also estimated groundwater recharge based on one hypothetical scenario that used 1980–2010 rainfall and 2017 land cover. For the nine historical periods, estimated recharge from infiltration and direct recharge within the area of the groundwater model ranged from 30.4 million gallons per day (Mgal/d) during 2010–12 to 98.7 Mgal/d during 1926–69. Variability in recharge during these periods mainly reflects changes in rainfall and irrigation over time. Between 2010 and 2014, streamflow restoration in previously diverted streams resulted in an estimated increase in recharge from seepage in stream channels of about 12.5 Mgal/d. Average groundwater inflow of about 39.6 Mgal/d from inland, dike-intruded areas to the main area of interest was estimated from an existing island-wide numerical groundwater-flow model, which is at a larger scale and incorporates a greater number of simplifying assumptions.
The numerical groundwater model developed for this study was calibrated to 1926–2012 transient water levels, vertical salinity profiles, and chloride concentrations of water pumped by production wells in the study area. The model was then used to evaluate one future recharge and six selected withdrawal scenarios, developed in consultation with the Maui Department of Water Supply, in terms of long-term changes in water level and 50-percent ocean-water salinity surface. The groundwater model was also used to simulate the future salinity of water withdrawn by existing and proposed production wells. The simulations were run to steady-state conditions, providing an estimate of the long-term effects of changes in withdrawal and recharge on the groundwater resource. Results of the simulated future withdrawal scenarios indicate that, relative to 2017–18 rates, the scenarios’ long-term effect of increased withdrawals ultimately leads to lower water levels and a higher 50-percent ocean-water salinity surface indicating a thinning of the freshwater lens. Results also indicate that the increased withdrawals produce some groundwater with chloride concentration below 250 milligrams per liter and some groundwater with higher chloride concentration. The amount of drawdown near production wells and the quality of water withdrawn from production wells is dependent on the rate and spatial distribution of the withdrawals.
The model was also used to evaluate how groundwater availability may be affected for a drier recharge scenario based on a published study of future climate. Model results of the future recharge scenario indicate that the rate of groundwater recharge is a controlling factor for (1) water levels, (2) the 50-percent ocean-water salinity surface, and (3) the quality of water withdrawn from production wells in the Wailuku area. Coupled with reduced groundwater recharge (with all other factors remaining equal), the modeled future withdrawals in the scenario would tend to cause lower water levels, a higher 50-percent ocean-water salinity surface, and increased salinity of water withdrawn from production wells.
The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the long-term hydrologic effects of additional groundwater withdrawals in central Maui. The model has several limitations, including its non-uniqueness and inability to account for local-scale heterogeneities. Short-term effects of changes in recharge and withdrawals—and optimization of pumping rates to meet increased demand for water with acceptable salinity—are possible conditions for future simulation analyses.
Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Regional groundwater recharge commonly is estimated using a threshold-type water-budget approach in which groundwater recharge is assumed to occur when water in the plant-root zone exceeds the soil’s moisture storage capacity. A water budget of the plant-soil system accounts for water inputs (rainfall, fog interception, irrigation, septic-system leachate, and other inputs), water outputs (runoff, evaporation, transpiration, and recharge), and changes in stored water during a specified time interval. Water budgets can be computed on any desired interval, including annual, monthly, daily, and subdaily intervals. In general, uncertainty in recharge estimates is expected to be lower using daily or subdaily intervals relative to monthly and annual intervals. Average recharge rates computed over a period of a year or multiple years are commonly determined from water budgets computed using a daily computation interval capable of capturing rainfall and land-cover changes during the period.
This report documents the Water-budget Accounting for Tropical Regions Model, or WATRMod, code that can be used to estimate spatially variable, daily water-budget components in tropical-island and other appropriate settings. The purpose of this report is to provide descriptions of WATRMod’s (1) approach to computing a daily water budget, (2) represented processes, (3) limitations, and (4) execution procedure, input requirements, output files, and example files. The model computes a daily water budget for each hydrologically independent subarea within the overall study area. A subarea is defined by its climatic, soil, land-cover, and human-related (for example, adding irrigation or other water) characteristics. The water-budget model can represent processes including rainfall, fog interception, irrigation, septic-system leachate, direct recharge that bypasses the plant-soil system, runoff, canopy evaporation in forested areas, evapotranspiration, and groundwater recharge. The water-budget model can represent either one of the following different accounting orders: (1) accounting for loss of water by evapotranspiration before accounting for recharge, and (2) accounting for recharge before accounting for evapotranspiration. WATRMod’s limitations include: (1) uncharacterized, subdaily transient changes in water inputs and outputs from the plant-soil system, (2) unrepresented precipitation in the form of snow and sublimation, and (3) routing runoff from one subarea to an adjacent subarea that is not directly represented.
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Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818