Bobcats (Lynx rufus) are terrestrial mammals that also inhabit tree islands (i.e., topographically elevated patches of forested land) embedded in the subtropical Everglades wetlands, which serve as a dry refuge habitat during the wet season in this region of Florida, USA. The Comprehensive Everglades Restoration Plan seeks to restore Everglades water flow to pre-drainage conditions, but little is known about how water levels or other landscape-level factors may influence mammalian occurrence, such as bobcats, on the tree islands in this ecosystem. We used game camera records and occupancy modeling to test for effects of static habitat variables and dynamic hydrologic variables. We hypothesized that deep water levels would limit the accessibility of tree islands to bobcats; therefore, we predicted that bobcat occupancy would decline with higher water levels. We also tested for the effect of an expanding invasive snake (i.e., Burmese python [Python molarus bivittatus]) using output from a model constructed to predict density and spread of Burmese pythons across southern Florida. We hypothesized that increases in Burmese pythons on the landscape would influence the food resources of bobcats, resulting in reduced bobcat occupancy at higher predicted densities of pythons. We built detection histories using 1,855 bobcat images from game cameras set on 87 tree islands in an Everglades conservation area from 2005–2019. Bobcat occupancy was significantly diminished when predicted Burmese python densities exceeded approximately 3 Burmese pythons/km2. Bobcat occupancy probability also increased with tree-island density around the focal tree island. Although water depth and hydroperiod surrounding tree islands appeared in our top 3 candidate models, the hydrologic variables had weak effects on bobcat occupancy. Our results suggest that while hydrologic dynamics may play a role, the invasive Burmese python has stronger influences on bobcat occupancy of tree islands in this Everglades conservation area.
Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2023.102882","usgsCitation":"DeAngelo, J., Shervais, J., Glen, J.M., Nielson, D., Garg, S., Dobson, P., Gasperikova, E., Sonnenthal, E., Liberty, L.M., Siler, D.L., and Evans, J., 2024, Geothermal Play Fairway Analysis, Part 2: GIS methodology: Geothermics, v. 117, 102882, 13 p., https://doi.org/10.1016/j.geothermics.2023.102882.","productDescription":"102882, 13 p.","ipdsId":"IP-148320","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":440975,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2023.102882","text":"Publisher Index Page"},{"id":423833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shervais, John W.","contributorId":237914,"corporation":false,"usgs":false,"family":"Shervais","given":"John W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":890649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nielson, Dennis","contributorId":237918,"corporation":false,"usgs":false,"family":"Nielson","given":"Dennis","affiliations":[{"id":47642,"text":"DOSECC Exploration Services","active":true,"usgs":false}],"preferred":false,"id":890651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garg, Sabodh","contributorId":193564,"corporation":false,"usgs":false,"family":"Garg","given":"Sabodh","email":"","affiliations":[],"preferred":false,"id":890652,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dobson, Patrick","contributorId":193558,"corporation":false,"usgs":false,"family":"Dobson","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":890653,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gasperikova, Erika","contributorId":193561,"corporation":false,"usgs":false,"family":"Gasperikova","given":"Erika","affiliations":[],"preferred":false,"id":890654,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sonnenthal, Eric","contributorId":146807,"corporation":false,"usgs":false,"family":"Sonnenthal","given":"Eric","affiliations":[],"preferred":false,"id":890655,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liberty, Lee M. 0000-0003-2793-8173","orcid":"https://orcid.org/0000-0003-2793-8173","contributorId":332607,"corporation":false,"usgs":false,"family":"Liberty","given":"Lee","email":"","middleInitial":"M.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":890656,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Siler, Drew Lorenz 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":303226,"corporation":false,"usgs":false,"family":"Siler","given":"Drew","email":"","middleInitial":"Lorenz","affiliations":[{"id":65720,"text":"Geologica Geothermal Group, LLC.","active":true,"usgs":false}],"preferred":false,"id":890657,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Evans, James P.","contributorId":332609,"corporation":false,"usgs":false,"family":"Evans","given":"James P.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":890658,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70273232,"text":"70273232 - 2024 - Chapter 24 - Resilience-based challenges and opportunities for fisheries management in Anthropocene rivers","interactions":[],"lastModifiedDate":"2025-12-22T15:28:45.761049","indexId":"70273232","displayToPublicDate":"2023-12-01T09:20:59","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Chapter 24 - Resilience-based challenges and opportunities for fisheries management in Anthropocene rivers","docAbstract":"Few pristine rivers remain worldwide, as they are among the most anthropogenically modified ecosystems. We suggest the geomorphology, hydrology and ecology of Anthropocene rivers are fundamentally different from historical natural rivers. These changes challenge conventional fisheries management practices, suggesting the tools supporting fisheries management may require expansion so that strategies match the scope and scale of present-day problems. We believe that resilience-thinking concepts offer substantial benefits for fisheries managers in Anthropocene rivers. When viewing resilience as a property of an ecosystem, the focus should be increasing the capacity of the system to self-organise and adapt to withstand regime shifts from internal and external disturbances. As an approach, a resilience-based perspective favours managing for sustainability and stewardship of fisheries by placing an emphasis on enhancing the capacity of complex systems to cope with dynamic change. Three case studies presented herein use resilience thinking to highlight challenges and opportunities for fisheries management in Anthropocene rivers from Europe, North America and Australia. Ultimately, a resilience approach to fisheries management emphasises increasing the ecological, institutional and societal capacities to deal with change, whether those changes be hydroclimatic, geomorphic, biological or social, to sustain desirable subsistence, recreational and commercial fisheries.
","largerWorkTitle":"Resilience and Riverine Landscapes","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-91716-2.00005-4","usgsCitation":"DeBoer, J., Bouska, K.L., Wolter, C., and Thoms, M.C., 2024, Chapter 24 - Resilience-based challenges and opportunities for fisheries management in Anthropocene rivers, chap. of Resilience and Riverine Landscapes, p. 491-517, https://doi.org/10.1016/B978-0-323-91716-2.00005-4.","productDescription":"27 p.","startPage":"491","endPage":"517","ipdsId":"IP-146916","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":497867,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeBoer, Jason A.","contributorId":336872,"corporation":false,"usgs":false,"family":"DeBoer","given":"Jason A.","affiliations":[{"id":80890,"text":"Illinois Natural History Survey (INHS)","active":true,"usgs":false}],"preferred":false,"id":952805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":952806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolter, Christian","contributorId":364518,"corporation":false,"usgs":false,"family":"Wolter","given":"Christian","affiliations":[{"id":18001,"text":"Leibniz Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":952807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thoms, Martin C. 0000-0002-8074-0476","orcid":"https://orcid.org/0000-0002-8074-0476","contributorId":145710,"corporation":false,"usgs":false,"family":"Thoms","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":16205,"text":"Riverine Landscapes Research Laboratory, University of New England, NSW, Australia","active":true,"usgs":false}],"preferred":false,"id":952808,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250875,"text":"70250875 - 2024 - Glacial vicariance and secondary contact shape demographic histories in a freshwater mussel species complex","interactions":[],"lastModifiedDate":"2024-02-07T17:19:43.793353","indexId":"70250875","displayToPublicDate":"2023-11-28T09:38:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2333,"text":"Journal of Heredity","active":true,"publicationSubtype":{"id":10}},"title":"Glacial vicariance and secondary contact shape demographic histories in a freshwater mussel species complex","docAbstract":"Characterizing the mechanisms influencing the distribution of genetic variation in aquatic species can be difficult due to the dynamic nature of hydrological landscapes. In North America’s Central Highlands, a complex history of glacial dynamics, long-term isolation, and secondary contact have shaped genetic variation in aquatic species. Although the effects of glacial history have been demonstrated in many taxa, responses are often lineage- or species-specific and driven by organismal ecology. In this study, we reconstruct the evolutionary history of a freshwater mussel species complex using a suite of mitochondrial and nuclear loci to resolve taxonomic and demographic uncertainties. Our findings do not support Pleurobema rubrum as a valid species, which is proposed for listing as threatened under the U.S. Endangered Species Act. We synonymize P. rubrum under Pleurobema sintoxia—a common and widespread species found throughout the Mississippi River Basin. Further investigation of patterns of genetic variation in P. sintoxia identified a complex demographic history, including ancestral vicariance and secondary contact, within the Eastern Highlands. We hypothesize these patterns were shaped by ancestral vicariance driven by the formation of Lake Green and subsequent secondary contact after the last glacial maximum. Our inference aligns with demographic histories observed in other aquatic taxa in the region and mirrors patterns of genetic variation of a freshwater fish species (Erimystax dissimilis) confirmed to serve as a parasitic larval host for P. sintoxia. Our findings directly link species ecology to observed patterns of genetic variation and may have significant implications for future conservation and recovery actions of freshwater mussels.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jhered/esad075","usgsCitation":"Johnson, N., Henderson, A.R., Jones, J.W., Beaver, C., Ahlstedt, S.A., Dinkins, G.R., Eckert, N., Endries, M.J., Garner, J.T., Harris, J.L., Hartfield, P.D., Hubbs, D.W., Lane, T.W., McGregor, M.A., Moles, K.R., Morrison, C., Wagner, M.D., Williams, J.D., and Smith, C.H., 2024, Glacial vicariance and secondary contact shape demographic histories in a freshwater mussel species complex: Journal of Heredity, v. 115, no. 1, p. 72-85, https://doi.org/10.1093/jhered/esad075.","productDescription":"14 p.","startPage":"72","endPage":"85","ipdsId":"IP-154056","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441002,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jhered/esad075","text":"Publisher Index 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Because it entails various combinations of physical processes arising from the interactions of water, air, and solid particles in a porous medium, preferential flow is highly complex. Major research is needed to improve the ability to understand, quantify, model, and predict preferential flow. Toward a solution, a combination of diverse experimental measurements at multiple scales, from laboratory scale to mesoscale, has been implemented to detect and quantify preferential paths in carbonate and karstic unsaturated zones. This involves integration of information from (1) core samples, by means of mercury intrusion porosimeter, evaporation, quasi-steady centrifuge and dewpoint potentiometer laboratory methods, to investigate the effect of pore-size distribution on hydraulic characteristics and the potential activation of preferential flow, (2) field plot experiments with artificial sprinkling, to visualize preferential pathways related to secondary porosity, through use of geophysical measurements, and (3) mesoscale evaluation of field data through episodic master recession modeling of episodic recharge. This study demonstrates that preferential flow processes operate from core scale to two different field scales and impact on the qualitative and quantitative groundwater status, by entailing fast flow with subsequent effects on recharge rate and contaminant mobilizing. The presented results represent a rare example of preferential flow detection and numerical modeling by reducing underestimation of the recharge and contamination risks.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10040-023-02733-3","usgsCitation":"Caputo, M.C., De Carlo, L., Masciale, R., Perkins, K., Turturro, A., and Nimmo, J.R., 2024, Detection and quantification of preferential flow using artificial rainfall with multiple experimental approaches: Hydrogeology Journal, v. 32, p. 467-485, https://doi.org/10.1007/s10040-023-02733-3.","productDescription":"19 p.","startPage":"467","endPage":"485","ipdsId":"IP-154640","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488207,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-023-02733-3","text":"Publisher Index Page"},{"id":484496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","city":"Bari","otherGeospatial":"Apulia Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 16.69243585627035,\n 41.22008353121049\n ],\n [\n 16.723263851427802,\n 41.048118236977714\n ],\n [\n 17.078664904300638,\n 40.82955430051331\n ],\n [\n 18.547099758451623,\n 40.035404755129974\n ],\n [\n 18.558702660409736,\n 40.23218241073464\n ],\n [\n 18.044813946689686,\n 40.80608860459688\n ],\n [\n 16.69243585627035,\n 41.22008353121049\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","noUsgsAuthors":false,"publicationDate":"2023-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Caputo, Maria Clementina","contributorId":298645,"corporation":false,"usgs":false,"family":"Caputo","given":"Maria","email":"","middleInitial":"Clementina","affiliations":[{"id":64641,"text":"CNR-IRSA","active":true,"usgs":false}],"preferred":false,"id":932984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Carlo, Lorenzo","contributorId":298644,"corporation":false,"usgs":false,"family":"De Carlo","given":"Lorenzo","email":"","affiliations":[{"id":64641,"text":"CNR-IRSA","active":true,"usgs":false}],"preferred":false,"id":932985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masciale, Rita","contributorId":353110,"corporation":false,"usgs":false,"family":"Masciale","given":"Rita","affiliations":[{"id":64641,"text":"CNR-IRSA","active":true,"usgs":false}],"preferred":false,"id":932986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":932987,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turturro, Antonietta Celeste","contributorId":353112,"corporation":false,"usgs":false,"family":"Turturro","given":"Antonietta Celeste","affiliations":[{"id":64641,"text":"CNR-IRSA","active":true,"usgs":false}],"preferred":false,"id":932988,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":932989,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259508,"text":"70259508 - 2024 - Hydrologic, water operations, reservoir temperature, river temperature, sediment transport, habitat, and fish population modeling for the Trinity River Water Management Plan","interactions":[],"lastModifiedDate":"2024-10-10T16:48:39.581259","indexId":"70259508","displayToPublicDate":"2023-10-13T10:11:28","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":18744,"text":"Modeling Report","active":true,"publicationSubtype":{"id":4}},"seriesNumber":"Plan Project no. 251008","title":"Hydrologic, water operations, reservoir temperature, river temperature, sediment transport, habitat, and fish population modeling for the Trinity River Water Management Plan","docAbstract":"Humboldt County is developing a Water Management Plan that will describe a range of proposed annual releases from Trinity Reservoir consistent with the 1959 water delivery contract between Humboldt County and the U.S. Bureau of Reclamation (Reclamation). The 1959 contract states that Reclamation shall release not less than an annual quantity of 50,000 acre-feet into the Trinity River for the beneficial use of Humboldt County and other downstream users (Contract Water).
The Water Management Plan will outline how Contract Water should be released for the benefit of fisheries in the Trinity River and lower Klamath River, with the primary goal of expanding a harvestable surplus of Tribal, recreational, and commercial fisheries. A set of annual Contract Water release scenarios were developed during five workshops conducted in 2022 and 2023 with interested parties including Humboldt County, state and federal resource agencies, tribal representatives, Reclamation, and the U.S. Department of the Interior Solicitor’s office. A suite of modeling and technical tools was used to analyze annual conditions with and without Contract Water releases.
This Modeling Report describes the modeling tools used to assess Contract Water release scenarios, including CalSim II, HEC-5Q, RBM10, sediment transport models, Chinook Salmon habitat models, and the Stream Salmonid Simulator. Results from all models are summarized to provide a comparative overview of modeled release scenarios to modeled baseline conditions.
Mean annual Contract Water release scenarios ranged from 50,000 acre-feet to 170,000 acre-feet, and varied in timing, magnitude, and duration, though all releases were made between October and April. As shown in Table ES-1, a key finding of this modeling report is Contract Water releases that had the greatest modeled increase in Chinook Salmon abundance relative to baseline conditions included those that released 50,000 acre-feet in the fall period from October through December as pulse flows or baseflows, and those that released 170,000 acre-feet from October through April as a combination of pulse flows and baseflows. Modeled beneficial effects on populations were primarily due to either (1) increases in habitat area during the spawning life stage in October through December, which decreased redd superimposition (e.g., the process of a later arriving spawner building a redd on top of an existing redd) and improved egg survival, or (2) increases in flow during the fry emergence and juvenile rearing life stage in March through April, which increased the fry and parr carrying capacity (e.g., the upper limit for the number of fry or parr that a habitat unit can support) of individual habitat units.
Another key finding of this report is all Contract Water scenarios that released at least 50,000 acre-feet annually from Trinity Reservoir had similar effects on Trinity Reservoir storage, Central Valley Project (CVP) storage, CVP contract water deliveries, and Sacramento River water temperatures. Whether these scenarios were released annually as a fall baseflow, fall pulse flow, spring pulse flow, or spring baseflow, they all resulted in similar storage patterns in Trinity Reservoir – an annual reduction in storage relative to the baseline that was relatively small in wetter years and larger in drier years. As a result of lower Trinity Storage levels, Trinity River Division (TRD) exports to the CVP were reduced. Because the timing of exports is similar each year, reaching a peak in July through September, the reduction to exports occurred at the same time each year, independent of Contract Water release timing, resulting in similar storage, CVP delivery, and water temperature effects in the Sacramento River basin portion of the CVP. The water temperature effects on the Sacramento River were limited to the months of July and August, relatively minor, and were primarily attributed to changes in storage, release magnitude, and release temperature from Lake Shasta, and not due explicitly to inflows from the TRD.
","language":"English","publisher":"Stantec Consulting Services Inc.","usgsCitation":"Plumb, J., Perry, R., and Stantec Consulting Services Inc., 2024, Hydrologic, water operations, reservoir temperature, river temperature, sediment transport, habitat, and fish population modeling for the Trinity River Water Management Plan: Modeling Report Plan Project no. 251008, xi, 111 p.","productDescription":"xi, 111 p.","ipdsId":"IP-154221","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":462767,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://humboldtgov.org/DocumentCenter/","linkFileType":{"id":5,"text":"html"}},{"id":462795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Humboldt County","otherGeospatial":"Trinity River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.10894911119672,\n 41.54543340405891\n ],\n [\n -124.10894911119672,\n 40.712352880278644\n ],\n [\n -123.18492172676612,\n 40.712352880278644\n ],\n [\n -123.18492172676612,\n 41.54543340405891\n ],\n [\n -124.10894911119672,\n 41.54543340405891\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":915539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":915540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stantec Consulting Services Inc.","contributorId":345093,"corporation":true,"usgs":false,"organization":"Stantec Consulting Services Inc.","id":915623,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249964,"text":"70249964 - 2024 - Recent, widespread nitrate decreases may be linked to persistent dissolved organic carbon increases in headwater streams recovering from past acidic deposition","interactions":[],"lastModifiedDate":"2023-11-09T12:37:16.746256","indexId":"70249964","displayToPublicDate":"2023-10-11T06:36:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Recent, widespread nitrate decreases may be linked to persistent dissolved organic carbon increases in headwater streams recovering from past acidic deposition","docAbstract":"Long-term monitoring of water quality responses to natural and anthropogenic perturbation of watersheds informs policies for managing natural resources. Dissolved organic carbon (DOC) and nitrate (NO3−) in streams draining forested landscapes provide valuable information on ecosystem function due to their biogeochemical reactivity and solubility in water. Here we evaluate a 20-year record (2001−2021) of biweekly stream-water samples (n > 3000) and continuous discharge in three forested catchments in the Adirondack region of New York to investigate and interpret long-term trends in DOC and NO3− concentrations. Results from the intensively monitored catchments were compared with data from synoptic surveys of streams throughout the Adirondack region. A weighted regressions on time, discharge, and season (WRTDS) model, used to estimate daily flow-normalized concentrations, determined that DOC increased by ~30 to 50 % while NO3− decreased by ~50 to 70 % over the study period. The large amount of data from catchments with different soil properties permitted us to assess the relative effects of hydrology, season, and land cover factors on temporal trends in DOC and NO3− concentrations. We found weak evidence of climatic forcing of long-term increases in DOC, and instead contend that declining ionic strength in precipitation linked to declining anthropogenic acid deposition is driving DOC trends in stream waters. Nitrate concentrations were more variable but clearly decreased in recent years possibly related to declining N deposition. The recent increase in DOC:NO3− in all catchments indicates a major shift in stream stoichiometry that reflects changes in ecosystem functioning that may have important biogeochemical implications for terrestrial as well as aquatic ecosystems.
Widespread hydrologic alterations have simplified in-stream habitats in rivers globally, driving population declines and extirpations of many native fishes. Here, we examine how rapid geomorphic change in a historically degraded desert river has influenced habitat diversification and ecosystem persistence. In 2010, a large reach of the degraded and simplified lower San Rafael River (SRR), Utah, was impacted by the formation of a valley plug and began to shift from a homogenous, single-thread channel to a complex, multi-threaded riverscape. We combined field measurements and drone-collected imagery to document changes in fish habitat due to the valley plug. Our results demonstrate that in 2021, the affected reach was more diverse than any other stream reach along the SRR, containing 641% more diverse habitat (e.g., pools, riffles, and backwaters) than what was measured in 2015. The plug reach also retained water for periods beyond what was expected during seasonal drying, with the total extent of inundation within the riverscape increasing by over 2800%. Since the formation of the valley plug, riparian habitat has increased by 230% and channel networks have expanded to more than 50 distinct channels throughout the zone of influence. Our results provide evidence of successful self-restoration in a formerly highly degraded reach of desert river, and encourage new methods of desert river restoration. We aim to inform the use of large-scale, disruptive restoration actions like intentional channel occlusions, with the goal of mitigating the impacts of simplification and increasing habitat persistence in the face of exacerbated aridity in the desert Southwest.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.4213","usgsCitation":"Remiszewski, T.T., Budy, P., and Macfarlane, W., 2024, Expansive, positive changes to fish habitat diversity following the formation of a valley plug in a degraded desert river: River Research and Applications, v. 40, no. 1, p. 116-128, https://doi.org/10.1002/rra.4213.","productDescription":"13 p.","startPage":"116","endPage":"128","ipdsId":"IP-147695","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441167,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.4213","text":"Publisher Index Page"},{"id":429658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"San Rafael River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.65926854658869,\n 39.15654774664799\n ],\n [\n -110.65926854658869,\n 38.689875846653166\n ],\n [\n -110.09441178024811,\n 38.689875846653166\n ],\n [\n -110.09441178024811,\n 39.15654774664799\n ],\n [\n -110.65926854658869,\n 39.15654774664799\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Remiszewski, Tansy T.","contributorId":337428,"corporation":false,"usgs":false,"family":"Remiszewski","given":"Tansy","email":"","middleInitial":"T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":902416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macfarlane, William W.","contributorId":337429,"corporation":false,"usgs":false,"family":"Macfarlane","given":"William W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":902418,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251046,"text":"70251046 - 2024 - Using geospatial analysis to guide marsh restoration in Chesapeake Bay and beyond","interactions":[],"lastModifiedDate":"2024-01-19T13:20:31.871283","indexId":"70251046","displayToPublicDate":"2023-09-13T07:19:02","publicationYear":"2024","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":"Using geospatial analysis to guide marsh restoration in Chesapeake Bay and beyond","docAbstract":"Coastal managers are facing imminent decisions regarding the fate of coastal wetlands, given ongoing threats to their persistence. There is a need for objective methods to identify which wetland parcels are candidates for restoration, monitoring, protection, or acquisition due to limited resources and restoration techniques. Here, we describe a new spatially comprehensive data set for Chesapeake Bay salt marshes, which includes the unvegetated-vegetated marsh ratio, elevation metrics, and sediment-based lifespan. Spatial aggregation across regions of the Bay shows a trend of increasing deterioration with proximity to the seaward boundary, coherent with conceptual models of coastal landscape response to sea-level rise. On a smaller scale, the signature of deterioration is highly variable within subsections of the Bay: fringing, peninsular, and tidal river marsh complexes each exhibit different spatial patterns with regards to proximity to the seaward edge. We then demonstrate objective methods to use these data for mapping potential management options on to the landscape, and then provide methods to estimate lifespan and potential changes in lifespan in response to restoration actions as well as future sea level rise. We account for actions that aim to increase sediment inventories, revegetate barren areas, restore hydrology, and facilitate salt marsh migration into upland areas. The distillation of robust geospatial data into simple decision-making metrics, as well as the use of those metrics to map decisions on the landscape, represents an important step towards science-based coastal management.
Spring-fed wetlands within arid and semiarid systems are hotspots for endemism and distribution of rare plants. Interactions among groundwater and the geomorphic and climatic features of the setting control the abiotic conditions, particularly soil salinity and moisture, that support these plants. However, water uncertainty and land use change challenge the persistence of conditions necessary to support rare plant communities. Wetland management can be implemented to sustain abiotic processes that support rare plant communities, but key information is needed to guide management practices. In this study, we evaluate the relationships of rare plants to abiotic conditions in a managed spring-fed arid wetland. Soil salinity and moisture conditions were monitored and related to the presence and abundance of rare plants within management units. Soil salinity and moisture variability were related to groundwater dynamics near springs, but wetland management influenced variability in seasonally flooded areas. Permanently saturated conditions and low soil salinities during the spring season supported higher plant diversity and the presence and greater abundance of rare plants. Rare plant presence and abundance were negatively related to low soil moisture, particularly in the summer. Results indicate that increases in soil salinity during the early establishment of plants may affect their distribution and abundance, an important management consideration in arid landscapes and hydrologically altered systems. Our findings inform the restoration and management of rare plant communities and contribute to the management of spring-fed arid wetlands.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.14011","usgsCitation":"Cantu de Leija, A., and King, S.L., 2024, Relationships among rare plant communities and abiotic conditions in managed spring-fed arid wetlands: Restoration Ecology, v. 32, no. 6, e14011, 15 p., https://doi.org/10.1111/rec.14011.","productDescription":"e14011, 15 p.","ipdsId":"IP-149609","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499291,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.14011","text":"Publisher Index Page"},{"id":432950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","county":"Chavez County","otherGeospatial":"Bitter Lake National wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.36484598013773,\n 33.516209003994106\n ],\n [\n -104.440890439482,\n 33.51572504071022\n ],\n [\n -104.44147093153808,\n 33.40385436306539\n ],\n [\n -104.36542647219379,\n 33.40385436306539\n ],\n [\n -104.36484598013773,\n 33.516209003994106\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Cantu de Leija, Antonio","contributorId":341010,"corporation":false,"usgs":false,"family":"Cantu de Leija","given":"Antonio","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":907794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907795,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252092,"text":"70252092 - 2024 - MODFLOW as a configurable multi-model hydrologic simulator","interactions":[],"lastModifiedDate":"2024-03-14T11:52:46.995688","indexId":"70252092","displayToPublicDate":"2023-09-01T06:47:51","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"MODFLOW as a configurable multi-model hydrologic simulator","docAbstract":"MODFLOW 6 is the latest in a line of six “core” versions of MODFLOW released by the U.S. Geological Survey. The MODFLOW 6 architecture supports incorporation of additional hydrologic processes, in addition to groundwater flow, and allows interaction between processes. The architecture supports multiple model instances and multiple types of models within a single simulation, a flexible approach to formulating and solving the equations that represent hydrologic processes, and recent advances in interoperability, which allow MODFLOW to be accessed and controlled by external programs. The present version of MODFLOW 6 consolidates popular capabilities available in MODFLOW variants, such as the unstructured grid support in MODFLOW-USG, the Newton-Raphson formulation in MODFLOW-NWT, and the support for partitioned stress boundaries in MODFLOW-CDSS. The flexible multi-model capability allows users to configure MODFLOW 6 simulations to represent the local-grid refinement (LGR) capabilities available in MODFLOW-LGR, the multi-species transport capabilities in MT3DMS, and the coupled variable-density capabilities available in SEAWAT. This paper provides a new, holistic and integrated overview of simulation capabilities made possible by the MODFLOW 6 architecture, and describes how ongoing and future development can take advantage of the program architecture to integrate new capabilities in a way that is minimally invasive and automatically compatible with the existing MODFLOW 6 code.
Flooding is a dominant physical process that drives the form and function of river-floodplain ecosystems. Efficiently characterizing flooding dynamics can be challenging, especially over geographically broad areas or at spatial and temporal scales relevant for ecosystem management activities. Here, we empirically evaluated a low-complexity geospatial model of floodplain inundation in six study segments of the Upper Mississippi River System (UMRS) by pairing spatially extensive, temporally limited and spatially limited, temporally extensive sampling designs. We found little evidence of systematic bias in model performance although discrepancies between model predictions and empirical data did occur locally. Assessments of model predictions revealed low segment-wide discrepancies of wetted extent under contrasting flow conditions and agreement for inundation event detection and duration. Model performance for predicting event frequency and duration was similar among sites expected to exhibit contrasting patterns of hydrologic connectivity with the main channel. Our results suggest that low-complexity models can efficiently characterize a critical physical process across geographically broad, complex river-floodplain ecosystems. Such tools have the potential for advancing scientific understanding of landscape-scale ecological patterns and for prioritizing management actions in large, complex river-floodplain ecosystems like the UMRS.
Effective groundwater management is critical to future environmental, ecological, and social sustainability and requires accurate estimates of groundwater withdrawals. Unfortunately, these estimates are not readily available in most areas due to physical, regulatory, and social challenges. Here, we compare four different approaches for estimating groundwater withdrawals for agricultural irrigation. We apply these methods in a groundwater-irrigated region in the state of Kansas, USA, where high-quality groundwater withdrawal data are available for evaluation. The four methods represent a broad spectrum of approaches: (1) the hydrologically-based Water Table Fluctuation method (WTFM); (2) the demand-based SALUS crop model; (3) estimates based on satellite-derived evapotranspiration (ET) data from OpenET; and (4) a landscape hydrology model which integrates hydrologic- and demand-based approaches. The applicability of each approach varies based on data availability, spatial and temporal resolution, and accuracy of predictions. In general, our results indicate that all approaches reasonably estimate groundwater withdrawals in our region, however, the type and amount of data required for accurate estimates and the computational requirements vary among approaches. For example, WTFM requires accurate groundwater levels, specific yield, and recharge data, whereas the SALUS crop model requires adequate information about crop type, land use, and weather. This variability highlights the difficulty in identifying what data, and how much, are necessary for a reasonable groundwater withdrawal estimate, and suggests that data availability should drive the choice of approach. Overall, our findings will help practitioners evaluate the strengths and weaknesses of different approaches and select the appropriate approach for their application.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13336","usgsCitation":"Brookfield, A.E., Zipper, S., Kendall, A., Ajami, H., and Deines, J.M., 2024, Estimating groundwater pumping for irrigation: A method comparison: Groundwater, v. 62, no. 1, p. 15-33, https://doi.org/10.1111/gwat.13336.","productDescription":"19 p.","startPage":"15","endPage":"33","ipdsId":"IP-180562","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":492078,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13336","text":"Publisher Index Page"},{"id":491893,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","county":"Sheridan County, Thomas County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100.9,\n 39.6\n ],\n [\n -100.9,\n 39.2\n ],\n [\n -100.3,\n 39.2\n ],\n [\n -100.3,\n 39.6\n ],\n [\n -100.9,\n 39.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","issue":"1","noUsgsAuthors":true,"publicationDate":"2023-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Brookfield, Andrea E.","contributorId":202677,"corporation":false,"usgs":false,"family":"Brookfield","given":"Andrea","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":942441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":942442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, Anthony D.","contributorId":357745,"corporation":false,"usgs":false,"family":"Kendall","given":"Anthony D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":942443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajami, Hoori 0000-0001-6883-7630","orcid":"https://orcid.org/0000-0001-6883-7630","contributorId":303806,"corporation":false,"usgs":false,"family":"Ajami","given":"Hoori","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":942444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deines, Jillian M. 0000-0002-4279-8765","orcid":"https://orcid.org/0000-0002-4279-8765","contributorId":303808,"corporation":false,"usgs":false,"family":"Deines","given":"Jillian","email":"","middleInitial":"M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":942445,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239326,"text":"70239326 - 2024 - Soil elevation change in mangrove forests and marshes of the greater Everglades: A regional synthesis of surface elevation table-marker horizon (SET-MH) data","interactions":[],"lastModifiedDate":"2024-08-26T13:58:39.390067","indexId":"70239326","displayToPublicDate":"2022-12-20T07:04:56","publicationYear":"2024","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":"Soil elevation change in mangrove forests and marshes of the greater Everglades: A regional synthesis of surface elevation table-marker horizon (SET-MH) data","docAbstract":"Coastal wetlands adapt to rising seas via feedbacks that build soil elevation, which lead to wetland stability. However, accelerated rates of sea-level rise can exceed soil elevation gain, leading to wetland instability and loss. Thus, there is a pressing need to better understand regional and landscape variability in rates of wetland soil elevation change. Here, we conducted a regional synthesis of surface elevation change data from mangrove forests and coastal marshes in the iconic Greater Everglades region of south Florida (USA). We integrated data from 51 sites in which a total of 122 surface elevation table-marker horizon (SET-MH) stations were installed. Several of these sites have been periodically monitored since the 1990s and are among the oldest SET-MH datasets in the world. Rates of surface elevation change ranged from −9.8 to 15.2 mm year−1, indicating some wetlands are keeping pace with sea-level rise while others are at risk of submergence and conversion to open water. Vertical accretion rates ranged from 0.6 to 12.9 mm year−1, and subsurface change rates ranged from −13.5 to 8.6 mm year−1. Rates of surface elevation change were positively related to subsurface change but not vertical accretion. There were no significant relationships between rates of surface elevation change and elevation (NAVD 88) or rates of sea-level rise. Site-specific examples indicate that hurricanes, plant productivity, hydrologic exchange, and proximity to sediment and nutrient inputs are critical but confounding drivers of surface elevation change dynamics in the Greater Everglades region. Collectively, our results reinforce the value of long-term SET-MH data that incorporate spatial variability for advancing understanding of surface elevation change dynamics in coastal wetlands.
Mormon Lake, elevation 2166 m with maximum historic surface area of 31.4 km2, lies in a forested endorheic basin covering 103 km2. It is the largest unaltered freshwater body on the 337,000 km2 Colorado Plateau. Prehistorical (before AD 1878) highstands were ca. 9 and 24 m relative to depocenter datum. These levels likely occurred during four multidecadal episodes of cool, wet conditions between ca. 3.55 and 0.20 ka BP. Maximum historical levels (early 1900s) were up to 7.9 m, whereas modern (post-1941) levels were frequently zero or relatively low. Historical climate records indicate reconstructed lake levels correlate directly with annual precipitation and inversely with temperature. Early highstands were associated with above average precipitation and the lowest temperatures of the 116 yr record. The lake receded after 1941; thereafter, frequent drying and low-water levels resulted from recurrent drought and steadily increasing temperatures. Consequently, a wet episode from the 1970s to the 1990s had precipitation like the early 1900s, but highstands were only ca. 3.8 m. The historical lake-level chronology is consistent with changes of hydrologic balance predicted by climate models, that is, reduced effective precipitation (precipitation minus evaporation). These changes, particularly aridification, apparently began in the 1970s or earlier. Global oceanic and atmospheric climate modulate lake levels and regional hydroclimate.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2020.92","usgsCitation":"Hereford, R., and Amoroso, L., 2024, Historical and prehistorical water levels of Mormon Lake, Arizona as a measure of climate change on the southwest Colorado Plateau, USA: Quaternary Research, v. 100, p. 32-51, https://doi.org/10.1017/qua.2020.92.","productDescription":"20 p.","startPage":"32","endPage":"51","ipdsId":"IP-113940","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":464625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Mormon Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.48876598336788,\n 34.98966103819039\n ],\n [\n -111.48876598336788,\n 34.906130634842924\n ],\n [\n -111.42028354514014,\n 34.906130634842924\n ],\n [\n -111.42028354514014,\n 34.98966103819039\n ],\n [\n -111.48876598336788,\n 34.98966103819039\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"100","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hereford, Richard 0000-0002-0892-7367 rhereford@usgs.gov","orcid":"https://orcid.org/0000-0002-0892-7367","contributorId":3620,"corporation":false,"usgs":true,"family":"Hereford","given":"Richard","email":"rhereford@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amoroso, Lee 0000-0003-1342-7487","orcid":"https://orcid.org/0000-0003-1342-7487","contributorId":346805,"corporation":false,"usgs":false,"family":"Amoroso","given":"Lee","affiliations":[],"preferred":false,"id":919935,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70247895,"text":"70247895 - 2023 - Ancient infrastructure offers sustainable agricultural solutions to dryland farming","interactions":[],"lastModifiedDate":"2024-01-09T19:11:38.354524","indexId":"70247895","displayToPublicDate":"2023-12-29T11:48:23","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"11","title":"Ancient infrastructure offers sustainable agricultural solutions to dryland farming","docAbstract":"For 1000 years, human populations in dryland regions of the North American Southwest (NAS) extensively constructed diverse forms of agricultural infrastructure, including canals, linear rock alignments, check dams, stock ponds, and other earthworks and rock structures. The long-term hydrological impacts of these and the demographic and socio-political drivers of construction and maintenance have yet to be fully documented or vetted. This paper summarizes existing knowledge attained from the United Stated portion of the NAS, but a lot is still unknown about Northwest Mexico. There remain outstanding questions related to understanding how ancient agriculture might improve modern adaptability and resilience. The detailed ecological and topographical variability of this arid landscape illustrates the essential need for infrastructure in maintaining water and managing the impacts of climate change on the hydrological cycle. We describe pros and cons of different types of infrastructure and examine socio-environmental trade-offs between robustness and vulnerability produced by reliance on infrastructure, drawing from existing literature to examine timescales longer than a human lifespan. The development of historically-informed management approaches to increase dryland climate resilience benefits from incorporating constraints and opportunities mediated by past landscape modifications. We present a plan for leveraging existing knowledge, available science, and potential, to extend our knowledge base and further explore causal relationships.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Soil and drought: Basic processes","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Routledge Taylor & Francis Group.","doi":"10.1201/b22954-11","usgsCitation":"Pailes, M.C., Norman, L., Baisan, C.H., Meko, D., Gauthier, N.E., Villanueva-Diaz, J., Dean, J., Martinez, J., Kessler, N.V., and Towner, R., 2023, Ancient infrastructure offers sustainable agricultural solutions to dryland farming, chap. 11 of Soil and drought: Basic processes, 24 p., https://doi.org/10.1201/b22954-11.","productDescription":"24 p.","ipdsId":"IP-146591","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":441333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1201/b22954-11","text":"Publisher Index Page"},{"id":424232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Lal, Rattan","contributorId":295331,"corporation":false,"usgs":false,"family":"Lal","given":"Rattan","email":"","affiliations":[{"id":63842,"text":"Ohio State University, CFAES Rattan Lal Center for Carbon Management and Sequestration, Columbus, OH 43210, USA","active":true,"usgs":false}],"preferred":false,"id":891784,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Pailes, Matthew C.","contributorId":328650,"corporation":false,"usgs":false,"family":"Pailes","given":"Matthew","email":"","middleInitial":"C.","affiliations":[{"id":78439,"text":"University of Oklahoma, Department of Anthropology, Norman, OK, USA","active":true,"usgs":false}],"preferred":false,"id":880901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":880902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baisan, Christopher H.","contributorId":204187,"corporation":false,"usgs":false,"family":"Baisan","given":"Christopher","email":"","middleInitial":"H.","affiliations":[{"id":28236,"text":"Univ of Arizona","active":true,"usgs":false}],"preferred":false,"id":880903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meko, David 0000-0002-5171-2724","orcid":"https://orcid.org/0000-0002-5171-2724","contributorId":296029,"corporation":false,"usgs":false,"family":"Meko","given":"David","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":880904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gauthier, Nicolas E.","contributorId":328652,"corporation":false,"usgs":false,"family":"Gauthier","given":"Nicolas","email":"","middleInitial":"E.","affiliations":[{"id":78442,"text":"University of Florida, Florida Museum of Natural History, USA","active":true,"usgs":false}],"preferred":false,"id":880906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Villanueva-Diaz, Jose","contributorId":328654,"corporation":false,"usgs":false,"family":"Villanueva-Diaz","given":"Jose","email":"","affiliations":[{"id":78444,"text":"Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias (INIFAP), Departamento de Dendrocronología, Mexico","active":true,"usgs":false}],"preferred":false,"id":880908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dean, Jeff","contributorId":328651,"corporation":false,"usgs":false,"family":"Dean","given":"Jeff","email":"","affiliations":[{"id":78441,"text":"University of Arizona, Laboratory of Tree-Ring Research, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":880905,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martinez, Jupiter","contributorId":328653,"corporation":false,"usgs":false,"family":"Martinez","given":"Jupiter","email":"","affiliations":[{"id":78443,"text":"Instituto Nacional de Antropología e Historia, Centro (INAH) Sonora, Mexico| ","active":true,"usgs":false}],"preferred":false,"id":880907,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kessler, Nicholas V","contributorId":328655,"corporation":false,"usgs":false,"family":"Kessler","given":"Nicholas","email":"","middleInitial":"V","affiliations":[{"id":78445,"text":"University of Arizona, School of Geography, Development Tucson, AZ USA","active":true,"usgs":false}],"preferred":false,"id":880909,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Towner, Ron","contributorId":328656,"corporation":false,"usgs":false,"family":"Towner","given":"Ron","email":"","affiliations":[{"id":78445,"text":"University of Arizona, School of Geography, Development Tucson, AZ USA","active":true,"usgs":false}],"preferred":false,"id":880910,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70250565,"text":"sir20235110 - 2023 - Evaluation of stream capture related to groundwater pumping, Lower Humboldt River Basin, Nevada","interactions":[],"lastModifiedDate":"2026-01-30T19:04:03.266175","indexId":"sir20235110","displayToPublicDate":"2023-12-29T09:26:16","publicationYear":"2023","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":"2023-5110","displayTitle":"Evaluation of Stream Capture Related to Groundwater Pumping, Lower Humboldt River Basin, Nevada","title":"Evaluation of stream capture related to groundwater pumping, Lower Humboldt River Basin, Nevada","docAbstract":"The Humboldt River Basin is the only river basin that is contained entirely within the State of Nevada. The effect of groundwater pumping on the Humboldt River is not well understood. Tools are needed to determine stream capture and manage groundwater pumping in the Humboldt River Basin. The objective of this study is to estimate capture and storage change caused by groundwater withdrawals in the lower Humboldt River Basin that can provide the Nevada State Engineer with data and information needed to manage groundwater and surface-water resources.
A numerical groundwater flow model was developed for the purpose of estimating stream capture from pre-2016 and future pumping as well as for any location of potential future pumping within the lower Humboldt River Basin. This model was developed using MODFLOW-NWT to represent the lower Humboldt River Basin hydrologic system, including Humboldt River; Rye Patch Reservoir; groundwater evapotranspiration; pumping from municipal, agricultural, mining, and domestic wells; and agricultural drains. Aquifer properties were calibrated using results from numerous single- and multi-well aquifer tests (Nadler, 2020) and through the process of model calibration.
Historical capture was estimated for 1960–2016 and predictive capture for the system was projected 100 years into the future (2017–2116) based on historical pumping patterns. Stream capture and drain capture are relatively low for the historical and predictive periods. During the historical period, increased pumping during dry years caused increased connections with capture sources and less water sourced to wells from aquifer storage. Storage and groundwater levels generally recovered during subsequent wet years. Overall, storage change has been the main source of water to wells in the lower Humboldt River Basin, followed by groundwater evapotranspiration capture. During the predictive period, pumping is projected to remain constant and capture 9 percent of stream water after 100 years.
Capture and storage change maps were created to visualize spatial variability in potential capture and storage change through time and to provide a database of results that can be used to manage groundwater and surface-water resources. These maps show that potential stream capture would be a minor source of water to wells located across most of the simulated area, except for locations close to the Humboldt River and Rye Patch Reservoir. Drains also would be a minor potential source of water to wells except for those directly adjacent to the drains. In general, the potential supply of water to wells is storage-dominated and over time groundwater evapotranspiration-dominated in the agricultural area.
Capture difference maps were generated to visualize where potential capture results might have greater limitations associated with nonlinear flow processes, such as head-dependent boundary conditions. Higher capture differences indicate larger capture map bias and therefore greater capture map uncertainty due to the inability of capture maps to account for nonlinear flow processes. Stream capture differences are highest directly adjacent to the river but are otherwise minimal. Drain capture differences are highest in the region of the agricultural drain network but are otherwise minimal. The Humboldt River, Rye Patch Reservoir, and drains introduce very little nonlinearity to the model, and their associated capture map bias is minimal. Potential groundwater evapotranspiration capture introduces a fair amount of nonlinearity to the model and has the potential to result in significant, localized groundwater evapotranspiration capture map bias over time. Groundwater evapotranspiration capture differences are the result of higher pumping rates lowering the water table below the root zone faster than lower pumping rates and essentially removing groundwater evapotranspiration as a potential source of capture faster than lower pumping rates. Wells that can no longer source their supply through groundwater evapotranspiration capture then generally source more of their water from storage. Thus, storage change bias increases over time as well.
Capture prediction uncertainty due to parameter estimation was evaluated using a covariance matrix adaptation-evolution strategy. One hundred Monte Carlo realizations of model parameters were applied to the model to assess capture uncertainty at 13 grid cell locations within the model domain. In general, results indicated that greater capture uncertainty for a given source (river, drains, or evapotranspiration) is associated with proximity of a pumping well to that source. The magnitude of maximum capture fraction uncertainties after 100 years of pumping for stream capture, drain capture, groundwater evapotranspiration capture, and storage change were plus or minus (±) 0.17, ±0.10, ±0.20, and ±0.22, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235110","collaboration":"Prepared in cooperation with the Nevada Division of Water Resources","usgsCitation":"Nadler, C.A., Rybarski, S.C., and Pham, H., 2023, Evaluation of stream capture related to groundwater pumping, Lower Humboldt River Basin, Nevada: U.S. Geological Survey Scientific Investigations Report 2023–5110, 77 p., https://doi.org/10.3133/sir20235110.","productDescription":"Report: x, 77 p.; Data Release","numberOfPages":"77","onlineOnly":"Y","ipdsId":"IP-093899","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":499384,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115938.htm","linkFileType":{"id":5,"text":"html"}},{"id":423640,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99DN2R1","text":"USGS Data Release","description":"Nadler, C.A., Rybarski, S.C., and Pham, H., 2023, MODFLOW-NWT model and supplementary data used to characterize effects of pumping in Lovelock Valley, Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/P99DN2R1.","linkHelpText":"MODFLOW-NWT Model and Supplementary Data Used to Characterize Effects of Pumping in Lovelock Valley, Nevada"},{"id":423639,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235110/full"},{"id":423635,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5110/covrthb.jpg"},{"id":423637,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5110/sir20235110.xml","linkFileType":{"id":8,"text":"xml"}},{"id":423636,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5110/sir20235110.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":423638,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5110/images"}],"country":"United States","state":"Nevada","otherGeospatial":"Lower Humboldt River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.0,\n 40.5\n ],\n [\n -119.0,\n 39.5\n ],\n [\n -118.0,\n 39.5\n ],\n [\n -118.0,\n 40.5\n ],\n [\n -119.0,\n 40.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701
Sea level rise is leading to the rapid migration of marshes into coastal forests and other terrestrial ecosystems. Although complex biophysical interactions likely govern these ecosystem transitions, projections of sea level driven land conversion commonly rely on a simplified “threshold elevation” that represents the elevation of the marsh-upland boundary based on tidal datums alone. To determine the influence of biophysical drivers on threshold elevations, and their implication for land conversion, we examined almost 100,000 high-resolution marsh-forest boundary elevation points, determined independently from tidal datums, alongside hydrologic, ecologic, and geomorphic data in the Chesapeake Bay, the largest estuary in the U.S. located along the mid-Atlantic coast. We find five-fold variations in threshold elevation across the entire estuary, driven not only by tidal range, but also salinity and slope. However, more than half of the variability is unexplained by these variables, which we attribute largely to uncaptured local factors including groundwater discharge, microtopography, and anthropogenic impacts. In the Chesapeake Bay, observed threshold elevations deviate from predicted elevations used to determine sea level driven land conversion by as much as the amount of projected regional sea level rise by 2050. These results suggest that local drivers strongly mediate coastal ecosystem transitions, and that predictions based on elevation and tidal datums alone may misrepresent future land conversion.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JG007525","usgsCitation":"Molino, G., Carr, J., Ganju, N., and Kirwan, M., 2023, Biophysical drivers of coastal treeline elevation: JGR Biogeosciences, v. 128, no. 12, e2023JG007525, 18 p., https://doi.org/10.1029/2023JG007525.","productDescription":"e2023JG007525, 18 p.","ipdsId":"IP-152726","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jg007525","text":"Publisher Index Page"},{"id":424278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.8511875475028,\n 39.673022111699964\n ],\n [\n -76.8511875475028,\n 36.994029518343055\n ],\n [\n -75.03985116290059,\n 36.994029518343055\n ],\n [\n -75.03985116290059,\n 39.673022111699964\n ],\n [\n -76.8511875475028,\n 39.673022111699964\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Molino, Grace 0000-0001-7345-8619","orcid":"https://orcid.org/0000-0001-7345-8619","contributorId":292186,"corporation":false,"usgs":false,"family":"Molino","given":"Grace","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":891909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":891910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":891911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirwan, Mathew 0000-0002-0658-3038","orcid":"https://orcid.org/0000-0002-0658-3038","contributorId":333093,"corporation":false,"usgs":false,"family":"Kirwan","given":"Mathew","email":"","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":891912,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250566,"text":"cir1516 - 2023 - Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","interactions":[],"lastModifiedDate":"2025-08-07T21:10:28.947951","indexId":"cir1516","displayToPublicDate":"2023-12-22T07:00:34","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1516","displayTitle":"Integrated Science Strategy for Assessing and Monitoring Water Availability and Migratory Birds for Terminal Lakes Across the Great Basin, United States","title":"Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","docAbstract":"In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin.
The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change.
Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources.
Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands.
The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert).
Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats.
The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level.
The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1516","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Frus, R.J., Aldridge, C.L., Casazza, M.L., Eagles-Smith, C.A., Herring, G., Hynek, S.A., Jones, D.K., Kemp, S.K., Marston, T.M., Morris, C.M., Naranjo, R.C., Nell, C.S., O’Leary, D.R., Overton, C.T., Pulver, B.A., Reichert, B.E., Rumsey, C.A., Schuster, R., and Smith, C.D., 2023, Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States (ver. 1.1, May 2025): U.S. Geological Survey Circular 1516, 80 p., https://doi.org/10.3133/cir1516.","productDescription":"Report: v, 68 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-150954","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":493768,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115888.htm","linkFileType":{"id":5,"text":"html"}},{"id":486001,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1516/versionHistory.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version history"},{"id":423645,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q9LQ4B","text":"USGS data release","description":"USGS data release","linkHelpText":"Protected areas database of the United States (PAD-US) 3.0"},{"id":423641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1516/coverthb.jpg"},{"id":423642,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1516/cir1516.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1516"},{"id":423644,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G5CGA7","text":"USGS data release","description":"USGS data release","linkHelpText":"Bibliography of hydrological and ecological research in the Great Basin terminal lakes, USA"},{"id":423646,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1516/images"},{"id":423647,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1516/cir1516.XML"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah, Wyoming","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.12391771230867,\n 44.77405073422017\n ],\n [\n -121.23711112053633,\n 42.97675607274502\n ],\n [\n -120.58454292500758,\n 41.114625765489706\n ],\n [\n -120.53050233969739,\n 39.38852576977999\n ],\n [\n -121.00002831582353,\n 38.53773263098702\n ],\n [\n -116.23219239369243,\n 34.14172761189964\n ],\n [\n -115.35960273905562,\n 33.921557217133085\n ],\n [\n -115.48689980188553,\n 34.74795954290249\n ],\n [\n -116.28333189096784,\n 36.47975443280677\n ],\n [\n -115.18568355055748,\n 36.991906804073\n ],\n [\n -114.24156554808329,\n 36.95599163233307\n ],\n [\n -113.37134736473482,\n 37.12638077251309\n ],\n [\n -110.81542598426338,\n 37.47470809636182\n ],\n [\n -109.75571598007943,\n 37.95141366251099\n ],\n [\n -109.25899321449629,\n 41.77121949987571\n ],\n [\n -109.56993210264781,\n 42.456264038882864\n ],\n [\n -111.91699262765405,\n 42.330119018284336\n ],\n [\n -115.47461542510021,\n 41.37630387146504\n ],\n [\n -117.71290028552804,\n 42.12092395037371\n ],\n [\n -119.12391771230867,\n 44.77405073422017\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: December 23, 2023; Version 1.1: April 2025","contact":"Director, Forest and Rangeland Ecosystem Science Center
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Director, Utah Water Science Center
U.S. Geological Survey
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Salt Lake City, Utah 84119-2047
The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. Drinking-water supplies throughout the basin were obtained primarily from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project.
An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. As of water year 2022, the network consisted of 120 wells and piezometers at 54 locations. The USGS, in cooperation with the ABCWUA, the New Mexico Office of the State Engineer, and Bernalillo County, measures water levels at the wells and piezometers in the network; this report, prepared in cooperation with the ABCWUA, presents water-level data collected by USGS personnel at the sites through water year 2022 (October 1, 2021, through September 30, 2022). Water-level data that were collected in previous water years from wells that were later discontinued were published in previous USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1186","issn":"2771-9448","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Bell, M.T., and Montero, N.Y., 2023, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2022: U.S. Geological Survey Data Report 1186, 42 p., https://doi.org/10.3133/dr1186.","productDescription":"Report: iv, 42 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-153179","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":423823,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"U.S. Geological Survey National Water Information System database"},{"id":423820,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1186/dr1186.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1186 XML"},{"id":423818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1186/coverthb.jpg"},{"id":423819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1186/dr1186.pdf","size":"3.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1186"},{"id":423821,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1186/full","linkFileType":{"id":5,"text":"html"},"description":"DR 1186 HTML"},{"id":423822,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1186/images"},{"id":499558,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115709.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.82700159405645,\n 34.09776221662605\n ],\n [\n -105.91538050030636,\n 34.09776221662605\n ],\n [\n -105.91538050030636,\n 36.30588569471621\n ],\n [\n -107.82700159405645,\n 36.30588569471621\n ],\n [\n -107.82700159405645,\n 34.09776221662605\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
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Monroe County is in southeastern West Virginia, encompassing an area of 474 square miles. The area consists of karst and siliciclastic aquifers of Ordovician, Silurian, Devonian, and Mississippian age and is in parts of two physiographic provinces: the Valley and Ridge Province to the east of Peters Mountain, and the Appalachian Plateau Province to the west of Peters Mountain. This study was developed in response to inquiries from the Monroe County Commission requesting assessment of the water resources of the county to better understand the quantity of the county’s groundwater resources, for both current [2023] and future demand, and to provide information to support protection and management of the county’s valuable groundwater resources.
Various products were developed for this study that provide knowledge with respect to water availability and contamination susceptibility of the karst aquifers within the county. U.S. Geological Survey (USGS) geologists conducted extensive geologic mapping in support of the project, producing (1) a countywide bedrock geologic map, (2) a countywide hydrogeologic map, and (3) a light detection and ranging (lidar)-derived countywide digital elevation model and associated sinkhole map. A significant part of this work was to map in detail the Greenbrier Group at the formation level, which prior to this study had only partially been completed. The report also includes (4) a description of the lithologic units identified as part of the geologic mapping process.
U.S. Geological Survey hydrologists completed several additional products for the hydrology part of the effort, including development of (1) a countywide potentiometric surface (water-table) map, (2) a countywide base-flow stream assessment, (3) countywide water-budget estimates, (4) well log surveys for 15 wells to better understand subsurface controls on groundwater flow within the study area, (5) two groundwater tracer tests to better refine the groundwater divide from the northern and southern parts of the karst aquifer in Monroe County; and finally, based on all available data collected for the study including the potentiometric surface map, geologic map, current [2023] and legacy fluorometric groundwater tracer tests, and base-flow stream assessments, (6) groundwater-basin delineations were reassessed for principal groundwater basins within the Greenbrier aquifer.
In Monroe County, four principal hydrogeologic settings produce large yields of water for residential, agricultural, and other uses. The most relied upon water-bearing zone with respect to current [2023] public water supply is from springs along Peters Mountain. These springs are derived from intervals of fractured sandstone and resultant alluvial deposits. Groundwater flows downslope through these permeable alluvial deposits and discharges at the contact with less permeable strata, such as the Reedsville Shale. The second most relied upon water-bearing zone in Monroe County is within the karstic Greenbrier Group aquifer, in which the basal Hillsdale Limestone overlies the less permeable Maccrady Shale. This geologic contact between the Hillsdale Limestone and Maccrady Shale is not only targeted as a source of water for agricultural supply but also is targeted as a source of water for residential supply. The third most relied upon water-bearing zone is composed of shallow perched aquifers within the Greenbrier Group. The discontinuous nature of these perched aquifers makes mapping their extent impossible, but they are related to permeable geologic strata, such as karstified limestones with solutionally enhanced permeability that overlies less permeable shale or chert bedrock. During geologic mapping of the county, several of these perched aquifers were documented in the Pickaway, Union, and Alderson Limestones. A fourth zone consists of springs from Ordovician carbonates at the base of Peters Mountain, which are influenced by sinking streams as well as upwelling along faults. In terms of water quantity, the most sustainable springs are those having deeper-sourced flows.
Public supplies are a principal source of water used for residential and commercial supply in the region, accounting for 0.49 million gallons per day (Mgal/d) of fresh-water withdrawals (0.14 Mgal/d of groundwater and 0.35 Mgal/d of surface water) for residential and commercial use and serving 6,645 individuals (49.2 percent of the population). An estimated 6,861 people, (50.8 percent of the population) primarily rely on private wells or other unregulated sources, such as springs, and withdraw 0.55 Mgal/d of groundwater for their residential use. Public water supply in the region is primarily (71.4 percent) derived from springs and augmented by stream withdrawals (backup sources mainly during low-flow periods), with the remaining portion (28.6 percent) derived from groundwater withdrawals from wells. For rural residents, however, 100 percent of their withdrawals are derived from groundwater (wells or springs).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235121","isbn":"978-1-4113-4541-6","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection, the West Virginia Department of Health & Human Resources, and the Monroe County Commission","usgsCitation":"Kozar, M.D., Doctor, D.H., Jones, W.K., Chien, N., Cox, C.E., Orndorff, R.C., Weary, D.J., Weaver, M.R., McAdoo, M.A., and Parker, M., 2023, Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia: U.S. Geological Survey Scientific Investigations Report 2023–5121, 82 p., https://doi.org/10.3133/sir20235121.","productDescription":"Report: xii, 81 p.; 4 Appendixes, 5 Data Releases","numberOfPages":"81","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-153904","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center 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Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
Riparian vegetation varies along hydrologic gradients, along which inundation and drought tend to be inversely correlated. Differentiating effects of inundation and drought on plant distributions is critical for predicting impacts of changes to baseflows and designing flow patterns to achieve vegetation objectives in regulated river systems. To this end, we conducted a greenhouse experiment where we decreased, increased, or maintained constant water levels experienced by a suite of riparian plant species. We related changes in new root growth and stomatal conductance under experimental conditions to species hydrologic niches in the field, specifically the median elevation at which they occur above the channel, along the regulated Colorado River in Grand Canyon. We found a significant negative relationship between root growth response to experimental inundation with increasing elevation above the channel in the field, and a negative response of stomatal conductance to inundation among the most xeric-adapted species. Drought responses were idiosyncratic with respect to hydrologic niche, and instead seemed to vary in relation to clonality and rooting depth. Several Salicaceae tree species that are uncommon along regulated rivers exhibited consistently negative responses to both drought and inundation relative to other species, which may explain their rarity. The results of this study suggest that riparian plant distributions along hydrologic gradients have been shaped primarily by current and past levels of inundation. However, future anticipated declines in the water table are likely to produce species-specific responses based on drought tolerance that may in part be predicted from the results of this experiment.