To better understand the effects of climate change on streamflow, the hydrologic response to both temperature and precipitation needs to be examined at the mesoscale. New York State provides a hydrologically diverse mesoscale region, where sub-regional clusters of watersheds may respond differently to changes in temperature and in seasonal precipitation rates. Connections between streamflow and climate were examined for 97 gaging stations across the state and surrounding areas, for a historical period of 56 years of daily average streamflow. Gages were grouped into clusters if their mean annual discharge rates were strongly correlated to one another. Within each cluster, sharp temporal changes in discharge, or change points, were identified. These change points clustered both spatially and by flow regime, with low, medium, and high flows increasing around 1970 for much of the state consistent with other studies in the region. A step increase in Catskill low flows in 2003 coincides with increases in summer precipitation, and is consistent with a positive correlation between summer precipitation and annual low flows. Our results support previous studies that have shown that streamflow at this mesoscale is strongly tied to precipitation, and the strength of that connection is modulated by land cover, geographic position, and seasonal moisture conditions. Across the state, the winter-spring center of volume date has moved earlier along with increasing January streamflow rates, the result of warmer winter temperatures and an increased proportion of precipitation as rain. The transition to a post-1970s pluvial period also coincided with more frequent peak over threshold flows statewide, and this wetter period has continued to the present day.
The sustainability of ground-source geothermal systems can be severely impacted by microbially mediated clogging processes. Biofouling of water wells by hydrous ferric oxide is a widespread problem. Although the mechanisms and critical environmental factors associated with clogging development are widely recognized, effects of mixing processes within the wells and time scales for clogging processes are not well characterized. Here we report insights from a joint hydrological, geochemical, and metagenomics characterization of a geothermal doublet in which hydrous ferric oxide and hydrous manganese oxide deposits had formed as a consequence of mixing shallow groundwater containing dissolved oxygen and nitrate with deeper, anoxic groundwater containing dissolved iron (FeII) and manganese (MnII). Metagenomics identify distinct bacteria consortia in the pumping well oxic and anoxic zones, including autotrophic iron-oxidizing bacteria. Batch mixing experiments and geochemical kinetics modeling of the associated reactions indicate that FeII and MnII oxidation are slow compared to the residence time of water in the pumping well; however, adsorption of FeII and MnII by accumulated hydrous ferric oxide and hydrous manganese oxide in the well bore and pump riser provides “infinite” time for surface-catalyzed oxidation and a convenient source of energy for iron-oxidizing bacteria, which colonize the surfaces and also catalyze oxidation. Thus, rapid clogging is caused by mixing-induced redox reactions and is exacerbated by microbial activity on accumulated hydrous oxide surfaces.
","language":"English","publisher":"American Chemical Society Publications","doi":"10.1021/acs.est.9b00453","usgsCitation":"Burte, L., Cravotta, C.A., Bethencourt, L., Farasin, J., Pedrot, M., Dufresne, A., Gerard, M., Baranger, C., Le Borgne, T., and Aquilina, L., 2019, Kinetic study on clogging of a geothermal pumping well triggered by mixing-induced biogeochemical reactions: Environmental Science & Technology, v. 53, no. 10, p. 5848-5857, https://doi.org/10.1021/acs.est.9b00453.","productDescription":"10 p.","startPage":"5848","endPage":"5857","ipdsId":"IP-104719","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":467656,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://insu.hal.science/insu-02123861","text":"External Repository"},{"id":365077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"France","city":"Orleans","volume":"53","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Burte, Luc","contributorId":216592,"corporation":false,"usgs":false,"family":"Burte","given":"Luc","email":"","affiliations":[{"id":39481,"text":"OSUR-UMR6118 Géosciences Rennes, Université de Rennes 1 and Centre National de la Recherche Scientifique, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":765125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":216591,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles","suffix":"III","email":"","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bethencourt, Lorine","contributorId":216593,"corporation":false,"usgs":false,"family":"Bethencourt","given":"Lorine","email":"","affiliations":[{"id":39481,"text":"OSUR-UMR6118 Géosciences Rennes, Université de Rennes 1 and Centre National de la Recherche Scientifique, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":765126,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farasin, Julien","contributorId":216594,"corporation":false,"usgs":false,"family":"Farasin","given":"Julien","email":"","affiliations":[{"id":39481,"text":"OSUR-UMR6118 Géosciences Rennes, Université de Rennes 1 and Centre National de la Recherche Scientifique, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":765127,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pedrot, Mathieu","contributorId":216595,"corporation":false,"usgs":false,"family":"Pedrot","given":"Mathieu","email":"","affiliations":[{"id":39481,"text":"OSUR-UMR6118 Géosciences Rennes, Université de Rennes 1 and Centre National de la Recherche Scientifique, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":765128,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dufresne, Alexis","contributorId":216596,"corporation":false,"usgs":false,"family":"Dufresne","given":"Alexis","email":"","affiliations":[{"id":39482,"text":"Ecobio-UMR 6553, Université de Rennes 1 and Centre National de la Recherche Scientifique, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":765129,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gerard, Marie-Francoise","contributorId":216597,"corporation":false,"usgs":false,"family":"Gerard","given":"Marie-Francoise","email":"","affiliations":[{"id":39481,"text":"OSUR-UMR6118 Géosciences Rennes, Université de Rennes 1 and Centre National de la Recherche Scientifique, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":765130,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baranger, Catherine","contributorId":216598,"corporation":false,"usgs":false,"family":"Baranger","given":"Catherine","email":"","affiliations":[{"id":39483,"text":"Antea Group, ZAC du Moulin 803 boulevard Duhamel du Monceau, Olivet, France","active":true,"usgs":false}],"preferred":false,"id":765131,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Le Borgne, Tanguy","contributorId":216599,"corporation":false,"usgs":false,"family":"Le Borgne","given":"Tanguy","email":"","affiliations":[{"id":39481,"text":"OSUR-UMR6118 Géosciences Rennes, Université de Rennes 1 and Centre National de la Recherche Scientifique, Rennes, France","active":true,"usgs":false}],"preferred":false,"id":765132,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Aquilina, Luc 0000-0001-9875-6436","orcid":"https://orcid.org/0000-0001-9875-6436","contributorId":215171,"corporation":false,"usgs":false,"family":"Aquilina","given":"Luc","email":"","affiliations":[{"id":39190,"text":"Université de Rennes","active":true,"usgs":false}],"preferred":false,"id":765133,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70202350,"text":"sir20185105 - 2019 - Hydrologic Influences on Water Levels at Three Oaks Recreation Area, Crystal Lake, Illinois, April 14 through September 27, 2016","interactions":[],"lastModifiedDate":"2019-04-30T12:50:01","indexId":"sir20185105","displayToPublicDate":"2019-04-29T15:30:00","publicationYear":"2019","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":"2018-5105","displayTitle":"Hydrologic Influences on Water Levels at Three Oaks Recreation Area, Crystal Lake, Illinois, April 14 through September 27, 2016","title":"Hydrologic Influences on Water Levels at Three Oaks Recreation Area, Crystal Lake, Illinois, April 14 through September 27, 2016","docAbstract":"Hydrologic influences on water levels were investigated at Three Oaks Recreation Area (TORA), a former sand-and-gravel quarry converted into recreational lakes in Crystal Lake, Illinois. From 2009 to 2015, average water levels in the lakes declined nearly 4 feet. It was not clear if these declines were related to variations in weather (precipitation or evaporation) or other hydrologic influences such as municipal supply pumping or nearby quarry operations. Data were collected using three approaches to determine the possibility of such hydrologic influences. First, water levels were collected at 15 minute intervals at three wells equipped with pressure transducers from April 14 through September 27, 2016. The continuous data allowed assessment of lake and well water level responses to precipitation, pumping influences, and quarry operations. Second, a single-day synoptic water-level survey was completed to create a water table map to determine groundwater flow directions. Third, single-well aquifer tests (slug tests) were completed on the three data-collection wells to estimate the aquifer’s horizontal hydraulic conductivity. Collectively, these data were used to determine the velocity and volume of water entering and exiting TORA.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20185105","collaboration":"Prepared in cooperation with the City of Crystal Lake, Illinois","usgsCitation":"Gahala, A.M., 2019, Hydrologic influences on water levels at Three Oaks Recreation Area, Crystal Lake, Illinois, April 14 through September 27, 2016: U.S. Geological Survey Scientific Investigations Report 2019–5105, 22 p., https://doi.org/10.3133/sir20185105.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082111","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":437479,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SA4LZZ","text":"USGS data release","linkHelpText":"Water level test data for groundwater monitoring wells near Three Oaks Recreational Area, Crystal Lake, Illinois"},{"id":362987,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5b801758e4b05f6e32194c4b","text":"USGS data release","description":"USGS data release","linkHelpText":"Water Level Test Data for Groundwater Monitoring Wells Near Three Oaks Recreational Area, Crystal Lake, Illinois"},{"id":362986,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5105/sir20185105.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5105"},{"id":362985,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5105/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Crystal Lake","otherGeospatial":"Three Oaks Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.32527160644531,\n 42.165184775416826\n ],\n [\n -88.23446273803711,\n 42.165184775416826\n ],\n [\n -88.23446273803711,\n 42.226610675467626\n ],\n [\n -88.32527160644531,\n 42.226610675467626\n ],\n [\n -88.32527160644531,\n 42.165184775416826\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, Wisconsin 53562
Surface debris covers much of the western portion of the McMurdo Ice Shelf and has a strong influence on the local surface albedo and energy balance. Differential ablation between debris-covered and debris-free areas creates an unusual heterogeneous surface of topographically low, high-ablation, and topographically raised (‘pedestalled’), low-ablation areas. Analysis of Landsat and MODIS satellite imagery from 1999 to 2018, alongside field observations from the 2016/2017 austral summer, shows that pedestalled relict lakes (‘pedestals’) form when an active surface meltwater lake that develops in the summer, freezes-over in winter, resulting in the lake-bottom debris being masked by a high-albedo, superimposed, ice surface. If this ice surface fails to melt during a subsequent melt season, it experiences reduced surface ablation relative to the surrounding debris-covered areas of the ice shelf. We propose that this differential ablation, and resultant hydrostatic and flexural readjustments of the ice shelf, causes the former supraglacial lake surface to become increasingly pedestalled above the lower topography of the surrounding ice shelf. Consequently, meltwater streams cannot flow onto these pedestalled features, and instead divert around them. We suggest that the development of pedestals has a significant influence on the surface-energy balance, hydrology and flexure of the ice shelf.
During 2015–17, the U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service (Forest Service), carried out a study to characterize the hydrology and water chemistry in two study areas within the Daniel Boone National Forest. One study area was within the Rock Creek drainage and the other study area included the Wildcat and Addison Branch drainages. Both study areas historically were mined for coal prior to the Surface Mining Control and Reclamation Act of 1977 and contain abandoned coal mine sites that have since been the focus of remediation efforts. Synoptic surveys of streamflow and water-quality properties (water temperature, pH, specific conductance, and dissolved oxygen) of Rock Creek were done during November 2015 and May 2016, and surveys of Wildcat and Addison Branches were done during June 2016 and May 2017. Streamflow measurements were used to quantify contributions from tributaries and to compute streamflow gain and loss in designated reaches. Discrete measurements of water temperature, pH, specific conductance, and dissolved oxygen were used to evaluate conditions during a short timeframe and for comparison between study areas. Study designs for the two study areas differed because there was an operating streamgage on Rock Creek near Yamacraw, Kentucky (station number 03410590) where streamflow and water-quality properties (water temperature, specific conductance, pH, dissolved oxygen, and turbidity) were monitored continuously, while Addison and Wildcat Branches were ungaged. Several hydrograph separation methods were used to estimate base flow and runoff at the Rock Creek gage. These data will be used by the Forest Service to evaluate the current (2018) conditions and plan remediation efforts.
The water quality at Rock Creek was less affected by acid mine drainage (AMD) than the Wildcat or Addison Branches. Appreciable losing reaches, where water flowed underground, were identified in both study areas. All losing reaches coincided with karst topography. Streamflow increased in areas with openings to underground mine tunnels, known as portals.
Six hydrograph separation methods (Base-flow index [BFI; standard and modified], HYSEP [fixed interval, sliding interval, and local minimum], and PART) were applied to daily mean streamflow collected from August 2015 to August 2017 at station number 03410590. The hydrograph separation methods partition total streamflow into base flow and streamflow that originated from surface runoff. Base flow typically reacts slowly to precipitation infiltration and is largely sustained by groundwater discharge. The estimated daily base flow and runoff made with the different separation methods are not highly different. On average, base flow accounted for more total streamflow than surface runoff during the study period, irrespective of method.
Water temperature, pH, dissolved oxygen, specific conductance, and turbidity values were measured from July 2016 through July 2017 with a continuous monitor installed at station number 03410590. Nearly neutral pH values that ranged from 6.8 to 7.9 standard units likely limited metal solubility in the surface water. The continuous specific conductance values ranged between 30 and 259 microsiemens per centimeter at 25 degrees Celsius. The previous remediation efforts are likely continuing to improve the effect of AMD in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195006","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Forest Service ","usgsCitation":"Cherry, M.A., 2019, Streamflow gain and loss, hydrograph separation, and water quality of abandoned mine lands in the Daniel Boone National Forest, eastern Kentucky, 2015–17: U.S. Geological Survey Scientific Investigations Report 2019–5006, 36 p., https://doi.org/10.3133/sir20195006.","productDescription":"Report: viii, 36 p.;Data Release","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091989","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":363195,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5006/sir20195006.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5006"},{"id":363196,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FX78D9","text":"USGS data release","description":"USGS data release","linkHelpText":"Streamflow and water-quality data for selected streams in the Daniel Boone National Forest, eastern Kentucky, 2015–17"},{"id":363194,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5006/coverthb.jpg"}],"country":"United States","state":"Kentucky","otherGeospatial":"Daniel Boone National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.67437744140625,\n 36.63536611993544\n ],\n [\n -84.20333862304688,\n 36.63536611993544\n ],\n [\n -84.20333862304688,\n 37.004746084814784\n ],\n [\n -84.67437744140625,\n 37.004746084814784\n ],\n [\n -84.67437744140625,\n 36.63536611993544\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
9818 Bluegrass Parkway
Louisville, KY 40299
We assess monthly temperature and precipitation data produced by four statistically based techniques that were used to downscale general circulation models (GCMs) in the Climate Model Intercomparison Program Phase 5 (CMIP5) (Taylor et al., 2012). We drive a simple water-balance model with the downscaled data to demonstrate the effect of the methods on the cold season hydrology of three, snow dominated regions in the western U.S. Independent of substantial variation among the GCM simulations over the regions (maximum range of ~3.5 °C and 50% change in precipitation), the four methods produce disparate high resolution representations of the magnitude and spatial patterns of future temperature and precipitation simulated by the models that range for up to ~3 °C and 30% change in precipitation that propagate into the hydrologic simulations. Temperature-dependent snowfall, accumulation, and melt in the model are sensitive to how atmospheric lapse rates are applied in the gridded observations that are used to remove the bias in raw GCM temperatures. By the end of the century the same downscaling method (Bias Corrected Spatial Disaggregation) yields a loss of cold-season snowpack of 34% over the Greater Yellowstone Area under a constant lapse rate ( 6.5°C km-1), whereas spatially variable lapse rates nearly double the loss to 66%, highlighting the roll of both lapse rates and high elevation stations in the bias correction dataset. The two newest downscaling methods (Multivariate Adaptive Constructed Analogs and Localized Constructed Analogs) preserve the magnitude of change simulated GCMs better than the other methods and the produce comparable hydrologic projections. Because the downscaled data from the methods vary spatially and by GCM, the downscaled data should be evaluated carefully as part of the process of using downscaled climate products to drive hydrological models over the area of interest.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR023458","usgsCitation":"Alder, J.R., and Hostetler, S.W., 2019, The dependence of hydroclimate projections in snow‐dominated regions of the western United States on the choice of statistically downscaled climate data: Water Resources Research, v. 55, no. 3, p. 2279-2300, https://doi.org/10.1029/2018WR023458.","productDescription":"22 p.","startPage":"2279","endPage":"2300","ipdsId":"IP-097120","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":437482,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O9EB1C","text":"USGS data release","linkHelpText":"Data Release for The dependence of hydroclimate projections in snow-dominated regions of the western U.S. on the choice of statistically downscaled climate data"},{"id":363240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana,Nevada, New Mexico, Oregon, Washington, Wyoming","otherGeospatial":"Columbia River Basin, Greater Yellowstone Area, Sierra Nevada, Upper Colorado Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.33300781249999,\n 34.66935854524543\n ],\n [\n -104.80957031249999,\n 34.66935854524543\n ],\n [\n -104.80957031249999,\n 48.69096039092549\n ],\n [\n -121.33300781249999,\n 48.69096039092549\n ],\n [\n -121.33300781249999,\n 34.66935854524543\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":761576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":761577,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203191,"text":"70203191 - 2019 - Geomorphic change and biogeomorphic feedbacks in a dryland river: The Little Colorado River, Arizona, USA","interactions":[],"lastModifiedDate":"2019-04-26T17:20:45","indexId":"70203191","displayToPublicDate":"2019-04-24T17:11:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic change and biogeomorphic feedbacks in a dryland river: The Little Colorado River, Arizona, USA","docAbstract":"The Little Colorado River in Arizona, U.S.A. has undergone substantial geomorphic change since the early 1900s. We analyzed hydrologic and geomorphic data at different spatial and temporal scales to determine the type, magnitude, and rate of geomorphic change that has occurred since the early 20th century. Since the 1920s, there have been 4 alternating periods of high and low total-annual flow. Peak-flow magnitude, however, has progressively declined. In some reaches, the channel has narrowed between 72 and 88% since the 1930s. Increases in sinuosity in wide alluvial valleys have resulted in reductions in channel slope by ~21 to 32%; channel bed aggradation up to 1.4 m has also occurred in some reaches. Newly developed floodplains have been colonized by dense stands of vegetation that appear to have stabilized these surfaces. Large, long duration floods may cause some channel widening, and meander migration, however, these floods are infrequent, and narrowing resumes shortly thereafter. Channel narrowing, increases in sinuosity, decreases in slope, and increases in vegetative roughness appear to have caused biogeomorphic feedbacks, thereby exacerbating sediment deposition, and disrupting flood conveyance. In recent decades, there has been an increase in the travel time of floods up to ~100% compared to floods of the 1940s and 1950s, and this has likely led to increased flood attenuation, contributing to decreases in peak-flow magnitude. The progressive increase in water development in parts of the basin has also likely played some role in the progressive declines in peak flow over the duration of the study.
","language":"English","publisher":"The Geological Society of America","doi":"10.1130/B35047.1","usgsCitation":"Dean, D.J., and Topping, D.J., 2019, Geomorphic change and biogeomorphic feedbacks in a dryland river: The Little Colorado River, Arizona, USA: GSA Bulletin, Repository Item: 2019158; 23 p., https://doi.org/10.1130/B35047.1.","productDescription":"Repository Item: 2019158; 23 p.","ipdsId":"IP-099021","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437486,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XPWIBM","text":"USGS data release","linkHelpText":"Geomorphic Change Data for the Little Colorado River, Arizona, USA"},{"id":363278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Little Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.412353515625,\n 35.54116627999815\n ],\n [\n -107.830810546875,\n 35.54116627999815\n ],\n [\n -107.830810546875,\n 37.13404537126446\n ],\n [\n -111.412353515625,\n 37.13404537126446\n ],\n [\n -111.412353515625,\n 35.54116627999815\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dean, David J. 0000-0003-0203-088X djdean@usgs.gov","orcid":"https://orcid.org/0000-0003-0203-088X","contributorId":215067,"corporation":false,"usgs":true,"family":"Dean","given":"David","email":"djdean@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":761569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":761570,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202839,"text":"sir20195022 - 2019 - Calibration of Precipitation-Runoff Modeling System (PRMS) to simulate prefire and postfire hydrologic response in the upper Rio Hondo Basin, New Mexico","interactions":[],"lastModifiedDate":"2019-04-26T14:47:08","indexId":"sir20195022","displayToPublicDate":"2019-04-24T13:17:01","publicationYear":"2019","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":"2019-5022","displayTitle":"Calibration of Precipitation-Runoff Modeling System (PRMS) to Simulate Prefire and Postfire Hydrologic Response in the Upper Rio Hondo Basin, New Mexico","title":"Calibration of Precipitation-Runoff Modeling System (PRMS) to simulate prefire and postfire hydrologic response in the upper Rio Hondo Basin, New Mexico","docAbstract":"The Precipitation-Runoff Modeling System (PRMS) is widely used to simulate the effects of climate, topography, land cover, and soils on landscape-level hydrologic responses and streamflow. The U.S. Geological Survey (USGS), in cooperation with the New Mexico Department of Homeland Security and Emergency Management, developed procedures to apply the PRMS model to simulate the effects of fire on hydrologic responses.
A PRMS model was built of the upper Rio Hondo Basin from the headwaters to approximately 19 miles downstream from the USGS streamgage Rio Hondo above Chavez Canyon near Hondo, New Mexico, by using 24 hydrologic response units (HRUs), or hydrologically similar subareas, from the National Hydrologic Model. A quasi-graphical user interface was created to easily query and analyze published PRMS sensitivity-analysis data. Simulation of mean daily streamflow was most sensitive to parameters related to snowmelt or infiltration throughout the upper Rio Hondo Basin. In the basin’s eastern and northern HRUs, flashiness and timing of streamflow were most sensitive to interflow; in many western-basin HRUs (higher elevations), flashiness of streamflow was most sensitive to soil moisture parameters, and timing of streamflow was most sensitive to infiltration and evapotranspiration parameters.
The PRMS model was calibrated for the fire-affected North Fork Eagle Creek subwatershed by comparing modeled to observed daily streamflow for the nonfrozen (May through October) period for a prefire and postfire time period. The prefire model was calibrated for the period 2007–12 before the 2012 fire, and the postfire model was calibrated for a 2-year (2014–15) period after the fire. Model parameterization combined manual adjustment of 8 parameters on the basis of prior knowledge and automated adjustment of the most sensitive parameters by using the Let Us Calibrate interface. A gridded, daily precipitation dataset that captured the spatial heterogeneity across the study watershed was used as the precipitation input for calibration. Model performance was assessed as satisfactory by using standard statistical measures for prefire and postfire periods.
The calibrated model was run by using data from a single precipitation gage to better represent the effect of localized, extreme storms on postfire hydrologic response. The calibrated models for prefire and postfire conditions simulated streamflows with greater consistency than the uncalibrated model for the corresponding (prefire or postfire) period of hydrographic record. The effect of fire on streamflow was found to be primarily a shift from streamflow dominated by base flow prior to fire to streamflow dominated by surface runoff after fire.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195022","collaboration":"Prepared in cooperation with the New Mexico Department of Homeland Security and Emergency Management","usgsCitation":"Douglas-Mankin, K.R., and Moeser, C.D., 2019, Calibration of Precipitation-Runoff Modeling System (PRMS) to simulate prefire and postfire hydrologic response in the upper Rio Hondo Basin, New Mexico: U.S. Geological Survey Scientific Investigations Report 2019–5022, 25 p., https://doi.org/10.3133/sir20195022.","productDescription":"Report: vi, 25 p.; Data Release","numberOfPages":"36","ipdsId":"IP-094970","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":363146,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KD1X7Q","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Model input and output for prefire and postfire hydrologic simulations in the Upper Rio Hondo Basin, New Mexico using the Precipitation-Runoff Modeling System (PRMS)"},{"id":363157,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5022/coverthb2.jpg"},{"id":363145,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5022/sir20195022.pdf","text":"Report","size":"2.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5022"}],"country":"United States","state":"New Mexico","county":"Lincoln County, Otero County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.83610534667969,\n 33.33741240611175\n ],\n [\n -105.74203491210938,\n 33.33741240611175\n ],\n [\n -105.74203491210938,\n 33.465816745730024\n ],\n [\n -105.83610534667969,\n 33.465816745730024\n ],\n [\n -105.83610534667969,\n 33.33741240611175\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd NE
Albuquerque, New Mexico 87113
Adaptive management has been applied to problems with multiple conflicting objectives in various natural resources settings to learn how management actions affect divergent values regarding system response. Hydropower applications have only recently begun to emerge in the field, yet in the specific example reported herein, stakeholders invested in determining the best management alternatives for attainment of a suite of objectives outlined in a long-term adaptive management program below R.L. Harris Dam, a large, privately owned dam in Alabama. Stakeholders convened an objective-setting workshop to engage a governance structure and developed a decision support model to determine appropriate actions that optimized stakeholder values. The process led to implemented change in dam operation inclusive of incorporating hypothetical responses in system parameters to management. To account for the iterative loop of adaptive management, yearly monitoring of state variables that approximated many stakeholder objectives was performed from 2005 to 2016 and data collected were incorporated into the decision model. Specific analysis of fish and macroinvertebrate population responses indicated a less than satisfactory response for some stakeholders to the flow-management changes at the dam. Uncertainty regarding the best management to provide adequate hydrologic and thermal habitats for fauna and boatable days for recreationists still exists. The project led to a Federal Energy Regulatory Commission process for renewing the license to operate the dam (beginning in 2018); adaptive management could be a viable path forward to ensure stakeholder satisfaction related to new management options.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191026","collaboration":"Prepared in cooperation with the Alabama Department of Conservation and Natural Resources, Alabama Power Company, U.S. Fish and Wildlife Service, and R.L. Harris Dam Adaptive Management Stakeholders","usgsCitation":"Irwin, E.R., ed., 2019, Adaptive management of flows from R.L. Harris Dam (Tallapoosa River, Alabama)—Stakeholder process and use of biological monitoring data for decision making: U.S. Geological Survey Open-File Report 2019–1026, 93 p., https://doi.org/10.3133/ofr20191026.","productDescription":"Report: x, 93 p.; 4 Appendixes; 1 Table","numberOfPages":"108","onlineOnly":"Y","ipdsId":"IP-096592","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":363058,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_A2.pdf","text":"Appendix A2","size":"302 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix A2","linkHelpText":"– Initial Bayesian Belief Network (2005), Training Cases and Learned Networks (2005–16)"},{"id":363057,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_A1.pdf","text":"Appendix A1","size":"1.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix A1","linkHelpText":"– Transcripts from the Adaptive Management Workshop, April 30–May 1, 2003"},{"id":363061,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_table_C2.1.pdf","text":"Table C2.1","size":"198 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Table C2.1","linkHelpText":"– Sum of total observations for each macroinvertebrate taxon at all sites, listed alphabetically by class, order, family and taxon"},{"id":363060,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_B.pdf","text":"Appendix B","size":"296 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix B","linkHelpText":"– R code used to conduct metapopulation analyses"},{"id":363056,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026.pdf","text":"Report","size":"5.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026"},{"id":363053,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1026/coverthb3.jpg"},{"id":363059,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1026/ofr20191026_appendix_A3.pdf","text":"Appendix A3","size":"112 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1026 Appendix A3","linkHelpText":"– Charter of the R.L. Harris Stakeholders Board"}],"country":"United States","state":"Alabama","otherGeospatial":"Tallapoosa River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.7208251953125,\n 32.93953889877841\n ],\n [\n -85.48324584960936,\n 32.93953889877841\n ],\n [\n -85.48324584960936,\n 33.6283419913718\n ],\n [\n -85.7208251953125,\n 33.6283419913718\n ],\n [\n -85.7208251953125,\n 32.93953889877841\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alabama Cooperative Fish and Wildlife Research Unit
School of Forestry and Wildlife Sciences
Auburn University
602 Duncan Dr.
Auburn, AL 36849–5418
A binational study was initiated to update statistical equations that are used to estimate the magnitude and frequency of peak flows on streams in Manitoba and Ontario, Canada, and Minnesota that are contained within the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada. Hydraulic engineers use peak streamflow data to inform designs of bridges, culverts, and dams, and water managers use peak streamflow data to inform regulation and planning activities. However, long-term streamflow measurements are available at few locations along the more than 20,000 miles of stream/ditch networks within the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada.
Estimates of peak-flow magnitudes for 66.7-, 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities equivalent to annual flood-frequency recurrence intervals of 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals, respectively, are presented for 49 streamgages in Minnesota and adjacent areas in the Province of Ontario, Canada, based on data collected through water year 2013. Peak-flow frequency information was subsequently used in regression analyses to develop equations relating peak flows for selected recurrence intervals to various basin and climatic characteristics.
The study area includes 49 streamgages located in the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada, and is represented by southern portions of the Canadian Provinces of Manitoba (2 percent) and Ontario (56 percent) and the northern portion of the U.S. State of Minnesota (42 percent). The study area was represented by three regions that were defined in previous studies in the U.S. State of Minnesota and another in the Canadian Province of Ontario. The two Minnesota regions A and B were developed using a multiple regression method and hydrologic landscape units were used to validate regions in Minnesota. The Ontario region A was developed using a multiple regression method and standardized residuals from the 100-year recurrence intervals.
Canadian maximum instantaneous peak-flow data were converted from a calendar year to a water year (October 1 to September 30) and where the annual maximum instantaneous peak-flow value was not available in HYDAT, the Sangal method was applied to known average daily flow values to estimate an annual maximum instantaneous peak-flow value. Geographic information system software was used to calculate eight characteristics investigated as potential explanatory variables in the regression analyses.
The procedure for estimating peak-flow frequency for selected exceedance probabilities for a specific ungaged site depends on whether the site is near a streamgage on the same stream or is on an ungaged stream. For an ungaged site near a streamgage on the same stream, the drainage-area ratio method can be used. For an ungaged site on an ungaged stream, the regional regression equations developed for this study should be used.
All equations presented in this study will be incorporated into StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey. StreamStats allows users to obtain streamflow statistics, basin characteristics, and other information for user-selected locations on streams through an interactive map.
Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Historical training and operational activities at Joint Base Cape Cod (JBCC) on western Cape Cod, Massachusetts, have resulted in the release of contaminants into an underlying glacial aquifer that is the sole source of water to the surrounding communities. Remedial systems have been installed to contain and remove contamination from the aquifer. Groundwater withdrawals for public supply are expected to increase as the region continues to urbanize. Increases in water-supply withdrawals and wastewater return flow likely will affect the hydrologic system around JBCC and could affect the transport of any contamination that may remain in the aquifer following remediation of contamination from the JBCC. The U.S. Geological Survey, in cooperation with the Air Force Civil Engineer Center, developed a numerical, steady-state regional model of the Sagamore flow lens on western Cape Cod and evaluated the potential effects of future (2030) groundwater withdrawals on water levels, streamflows, hydraulic gradients, and advective transport near the JBCC.
The aquifer consists generally of sandy sediments underlain by impermeable bedrock and is bounded laterally by a freshwater/saltwater interface. Data on the altitude of the bedrock surface, position of the freshwater/saltwater interface, lithology of the aquifer, spatial distribution of recharge, and hydrologic boundaries were incorporated into the three-dimensional, finite-difference groundwater flow model.
Some inputs into the numerical model—aquifer properties, leakances, and recharge—are represented as parameters to facilitate estimation of optimal parameter values in an inverse calibration. A hybrid parameterization scheme, with both zones of piecewise constancy and pilot points, is used to represent hydraulic conductivity; other adjustable parameters include recharge, boundary leakance, and porosity. Data on water levels, the distribution of subsurface contamination, and groundwater ages were compiled, evaluated, and used to develop observations of long-term average hydraulic gradients and advective-transport patterns. These observations of steady-state hydrologic conditions were combined with the parameterized groundwater model in an inverse calibration to estimate model parameters that best fit the observations.
Current (2010) and future (2030) conditions were simulated in the calibrated model to characterize the groundwater flow system and to determine potential effects of increased groundwater withdrawals on advective-transport patterns at the JBCC. Groundwater flow and advective transport are radially outward from a water-table divide in the northern part of the JBCC; flow diverges from the divide toward all points of the compass. Most groundwater flow and contaminant transport occur in shallow parts of the aquifer. On average, about one-half of the groundwater flux occurs in the shallowest 20 percent of the saturated thickness; shallow flow is even more predominant near streams and lakes. Projected (2030) increases in groundwater withdrawals decrease water levels by a maximum of about 1.2 feet in the northern part of the JBCC; drawdowns exceeding 1 foot generally are limited to areas near the largest increases in withdrawals, such as in the northern part of the JBCC, near Long Pond in Falmouth, and in eastern Barnstable. Streamflow decreases average about 6 percent; the largest decreases are in areas with the largest drawdowns. Changes in hydraulic-gradient directions at the water table exceed 1 degree in about 13 percent of the aquifer, generally near groundwater divides where gradient magnitudes are small and near large groundwater withdrawals. Predictions of advective transport from randomly selected locations at the water table are similar for current (2010) and future (2030) groundwater withdrawals. The results indicate that projected increases in groundwater withdrawals affect water levels and streamflows, but effects on hydraulic gradients and advective transport at the JBCC likely are small.
Several underlying assumptions inherent in the model, including observations and weights used in the calibration, representation of local-scale heterogeneity, and simulation of the freshwater/saltwater interface, could affect model calibration and predictions; these assumptions were evaluated with alternative models and alternative inverse calibrations. Eight alternative calibrations were performed in which different, but reasonable, observations and weights were used. The preferred calibrated model had the best overall fit to the observations.
Fine-grained silty sediments occur in many parts of the aquifer, and silt lenses can locally affect hydraulic gradients. A set of alternative models in which silts were represented with different correlation distances and hydraulic conductivities indicated that explicitly representing silt lenses could affect model calibration but that the implicit representation of local-scale heterogeneity may be sufficient at the regional scale to represent regional-scale hydraulic gradients. For the coastal boundary, two alternative models representing silty and sandy seabeds and their associated interface positions were developed to test the importance of the assumed coastal-boundary condition. The two alternative models resulted in different predictions of streamflow—streamflows increase with smaller (silty) seabed leakances. However, predictions of advective transport, particularly near the JBCC, generally were similar between the alternative and preferred calibrated models, indicating that the seabed leakance and associated interface position at the coastal boundary does not affect simulations of advective transport in inland parts of the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185139","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Walter, D.A., McCobb, T.D., and Fienen, M.N., 2019, Use of a numerical model to simulate the hydrologic system and transport of contaminants near Joint Base Cape Cod, western Cape Cod, Massachusetts: U.S. Geological Survey Scientific Investigations Report 2018–5139, 98 p., https://doi.org/10.3133/sir20185139.","productDescription":"Report: xi, 98 p.; Data Release","numberOfPages":"114","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077209","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":362939,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8XCT ","text":"USGS data release ","description":"USGS data release ","linkHelpText":"MODFLOW–2005 and MODPATH Used to Simulate the Hydrologic System and Transport of Contaminants Near Joint Base Cape Cod, Western Cape Cod, Massachusetts"},{"id":437495,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8XCT","text":"USGS data release","linkHelpText":"MODFLOW2005 and MODPATH used to simulate the hydrologic system and transport contaminants near Joint Base Cape Cod, Western Cape Cod, Massachusetts"},{"id":362937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5139/coverthb2.jpg"},{"id":362938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5139/sir20185139.pdf","text":"Report","size":"43.8 MB ","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5139"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.026611328125,\n 41.21172151054787\n ],\n [\n -69.840087890625,\n 41.21172151054787\n ],\n [\n -69.840087890625,\n 42.21224516288584\n ],\n [\n -71.026611328125,\n 42.21224516288584\n ],\n [\n -71.026611328125,\n 41.21172151054787\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
When rainfall is lower than normal over an extended period, streamflows decline, groundwater levels fall, and hydrological drought can occur. Droughts can reduce the water available for societal needs, such as public and private drinking-water supplies, farming, and industry, and for ecological health, such as maintenance of water quality and natural ecosystems. Recent droughts in the northeastern United States have highlighted the need for new scientific tools to forecast the probability of future droughts so water managers and the public can be better prepared for these events when they happen. Two recent U.S. Geological Survey (USGS) studies provide tools that can forecast the probabilities of summer droughts for streams and the probabilities of groundwater-level declines below specified targets or thresholds. These tools provide promising methods for identifying and anticipating probable streamflow and groundwater droughts specific to the northeastern United States. USGS Water Science Centers in the northeastern United States have acted together to use these methods for numerous streamflow gages and groundwater-level monitoring wells, and to make the results of the analyses available on the world wide web. This fact sheet describes the drought forecasting techniques used in a study to predict droughts for streamflow and groundwater in the northeastern United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193015","usgsCitation":"Austin, S.H., and Dudley, R.W., 2019, Drought forecasting for streams and groundwaters in northeastern United States: U.S. Geological Survey Fact Sheet 2019–3015, 4 p., https://doi.org/10.3133/fs20193015.","productDescription":"Document: 4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-102976","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":362991,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3015/coverthb.jpg"},{"id":362992,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3015/fs20193015.pdf","text":"Report","size":"7.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3015"}],"country":"United States","state":"Connecticut, Delaware, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.88134765625,\n 36.06686213257888\n ],\n [\n -74.37744140625,\n 36.35052700542763\n ],\n [\n -72.4658203125,\n 40.51379915504413\n ],\n [\n -69.697265625,\n 41.42625319507269\n ],\n [\n -70.20263671875,\n 43.43696596521823\n ],\n [\n -66.5771484375,\n 44.62175409623324\n ],\n [\n -68.7744140625,\n 47.90161354142077\n ],\n [\n -80.88134765625,\n 42.52069952914966\n ],\n [\n -80.88134765625,\n 36.06686213257888\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
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. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 resulted in an increased demand for water in areas within the basin. Drinking-water supplies throughout the basin were obtained solely 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. The network currently (2017) consists of 122 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the ABCWUA and the New Mexico Office of the State Engineer, currently (2017) measures and reports water levels from the 122 wells and piezometers in the network; this report presents water-level data collected by USGS personnel at those 122 sites through water years 2016 and 2017 (October 1, 2015, through September 30, 2017). Water levels that were collected from wells in previous water years were published in previous USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1113","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Beman, J.E., Ritchie, A.B., and Galanter, A.E., 2019, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2017 (ver. 1.1, August 2021): U.S. Geological Survey Data Series 1113, 39 p., https://doi.org/10.3133/ds1113.","productDescription":"iii, 39 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-106011","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":362978,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1113/coverthb2.jpg"},{"id":388366,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1113/ds1113.pdf","text":"Report","size":"5.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1113"},{"id":388367,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/1113/versionHist.txt","text":"Version History","size":"575 B","linkFileType":{"id":2,"text":"txt"},"description":"DS 1113 Version History"}],"country":"United States","state":"New Mexico","otherGeospatial":"Albuquerque Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.57812499999999,\n 33.710632271492095\n ],\n [\n -106.14990234375,\n 33.710632271492095\n ],\n [\n -106.14990234375,\n 35.764343479667176\n ],\n [\n -107.57812499999999,\n 35.764343479667176\n ],\n [\n -107.57812499999999,\n 33.710632271492095\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: August 2021","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Hurricane Irma skirted the northern coasts of the U.S. Virgin Islands and Puerto Rico, with maximum sustained winds of 185 miles per hour (mi/h) on September 6, 2017. The hurricane first made landfall in Florida near Cudjoe Key, in the lower Florida Keys, with maximum sustained winds of 130 mi/h on September 10, 2017. The hurricane made a second Florida landfall on Marco Island, Florida, with maximum sustained winds of 115 mi/h on September 10, 2017. The U.S. Geological Survey (USGS), in cooperation with Federal Emergency Management Agency, deployed a temporary monitoring network of water-level and barometric pressure sensors at 249 locations along the Puerto Rico, Florida, Georgia, and South Carolina coasts to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by the hurricane. Immediately following the passage of Hurricane Irma, the sensors were retrieved, and the data were disseminated on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#IrmaSeptember2017). The storm-tide peak data values were verified by comparing data from hydrologic recorders and nearby high-water marks (HWMs). Following the hurricane, 508 independent HWM locations were flagged and surveyed relative to the North American Vertical Datum of 1988, National Geodetic Vertical Datum of 1929, or a local datum along the southeastern U.S. coast, and to Puerto Rico Vertical Datum of 2002 in Puerto Rico. Most HWMs were in Florida because of the path of the hurricane. The data from the Hurricane Irma storm-tide network are available on a provisional basis in tab-delimited, American Standard Code for Information Interchange (ASCII) format and Network Common Data Form (NetCDF) format by site for each sensor by using the USGS Flood Event Viewer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191013","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Byrne, M.J., Sr., and Dickman, M.R., 2019, Monitoring storm tide and flooding from Hurricane Irma along the U.S. Virgin Islands, Puerto Rico, and the Southeastern United States, September 2017 (ver. 1.1, July 2019): U.S. Geological Survey Open-File Report 2019–1013, 35 p., https://doi.org/10.3133/ofr20191013.","productDescription":"vi, 35 p.","numberOfPages":"46","onlineOnly":"N","ipdsId":"IP-095711","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":365693,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1013/ofr20191013.pdf","text":"Report","size":"9.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1013"},{"id":365694,"rank":2,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2019/1013/versionHist.txt","text":"Version History","size":"1.00 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2019–1013 Version History"},{"id":365697,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1013/coverthb2.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.9892578125,\n 24.00632619875113\n ],\n [\n -79.4970703125,\n 24.00632619875113\n ],\n [\n -79.4970703125,\n 32.0639555946604\n ],\n [\n -88.9892578125,\n 32.0639555946604\n ],\n [\n -88.9892578125,\n 24.00632619875113\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.02734375,\n 16.04581345375217\n ],\n [\n -63.45703124999999,\n 16.04581345375217\n ],\n [\n -63.45703124999999,\n 20.96143961409684\n ],\n [\n -68.02734375,\n 20.96143961409684\n ],\n [\n -68.02734375,\n 16.04581345375217\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 16, 2019; Version 1.1: July 25, 2019 ","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559