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At least 325 records · Page 18Linked to original sources
USGS2009

Nutrient Trends in Streams and Rivers of the United States, 1993-2003

Trends in streamflow and concentrations and loads of total phosphorus, total nitrogen, and nitrate were determined for the period from 1993 to 2003 in selected streams and ricers of the United States. Flow-adjusted trends in concentration (the trends that would have occurred in the absence of natural chances in streamflow), non-flow-adjusted trends in concentration (the trends resulting from both natural and human factors), and trends in load (trends in the nutrient mass transported downstream) were determined, and the results were examined spatially to determine whether a consistent pattern of trends occurred across groups of sites at multiple locations. Relations between the trends and changes in nutrient sources and streamflow are examined. See document for complete abstract.

Scientific Investigations Report↗
USGS2009

Magnitude and frequency of rural floods in the southeastern United States, 2006: Volume 1, Georgia

A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in Georgia, South Carolina, and North Carolina that are not substantially affected by regulation, tidal fluctuations, or urban development. Annual peak-flow data through September 2006 were analyzed for 943 streamgaging stations having 10 or more years of data on rural streams in Georgia, South Carolina, North Carolina, and adjacent parts of Alabama, Florida, Tennessee, and Virginia. Flood-frequency estimates were computed for the 943 stations by fitting the logarithms of annual peak flows for each station to a Pearson Type III distribution. As part of the computation of flood-frequency estimates for these streamgaging stations, a new value for the generalized-skew coefficient was developed by using a Bayesian generalized least-squares regression model. Additionally, basin characteristics for the streamgaging stations were computed by using a geographical information system and automated computer algorithms. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged basins in Georgia, South Carolina, and North Carolina. Flood-frequency estimates and basin characteristics for 828 stream-gaging stations were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for Georgia, South Carolina, and North Carolina. The final predictive equations are all functions of drainage area and percentage of the drainage basin within each hydrologic region. Average standard errors of prediction for these regression equations range from 34.5 to 47.7 percent.

Georgia↗
USGS2009

Planning for an uncertain future - Monitoring, integration, and adaptation

The 6.7 billion human inhabitants of the earth have the ability to drastically alter ecosystems and the populations of species that have taken eons to evolve. By better understanding how our actions affect the environment, we stand a better chance of designing successful strategies to manage ecosystems sustainably. Toward this end, the Third Interagency Conference on Research in the Watersheds (ICRW) was convened in Estes Park, CO, on September 8-11, 2008. The Conference provided a forum to present adaptive management as a practical tool for learning how to manage complex ecosystems more sustainably. Further complexity introduced by spatially variable and continuously changing environmental drivers favors this management approach because of its emphasis on adaptation in response to changing conditions or ineffective actions. For climate change in particular, an adaptive approach can more effectively accommodate the uncertainty in future climate scenarios. Scenarios compiled by the Intergovernmental Panel on Climate Change are built on distinct economic, energy, and societal models. The scenarios predict potential changes in greenhouse gases, temperature, precipitation, and atmospheric aerosols, which would have direct or indirect impacts on the timing, volume, and quality of runoff, vegetation, snowpack, stream temperature, groundwater, thawing permafrost, and icecaps. Through presentations and field trips, researchers and stakeholders described how their findings and issues fit into the adaptive management 'learning by doing' paradigm of Assess > Design > Implement > Monitor > Evaluate > Adjust > Assess.

Scientific Investigations Report↗
USGS2009

Flood of April 2007 and flood-frequency estimates at streamflow-gaging stations in western Connecticut

A spring nor’easter affected the East Coast of the United States from April 15 to 18, 2007. In Connecticut, rainfall varied from 3 inches to more than 7 inches. The combined effects of heavy rainfall over a short duration, high winds, and high tides led to widespread flooding, storm damage, power outages, evacuations, and disruptions to traffic and commerce. The storm caused at least 18 fatalities (none in Connecticut). A Presidential Disaster Declaration was issued on May 11, 2007, for two counties in western Connecticut—Fairfield and Litchfield. This report documents hydrologic and meteorologic aspects of the April 2007 flood and includes estimates of the magnitude of the peak discharges and peak stages during the flood at 28 streamflow-gaging stations in western Connecticut. These data were used to perform flood-frequency analyses. Flood-frequency estimates provided in this report are expressed in terms of exceedance probabilities (the probability of a flood reaching or exceeding a particular magnitude in any year). Flood-frequency estimates for the 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, and 0.002 exceedance probabilities (also expressed as 50-, 20-, 10-, 4-, 2-, 1-, and 0.2- percent exceedance probability, respectively) were computed for 24 of the 28 streamflow-gaging stations. Exceedance probabilities can further be expressed in terms of recurrence intervals (2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence interval, respectively). Flood-frequency estimates computed in this study were compared to the flood-frequency estimates used to derive the water-surface profiles in previously published Federal Emergency Management Agency (FEMA) Flood Insurance Studies. The estimates in this report update and supersede previously published flood-frequency estimates for streamflowgaging stations in Connecticut by incorporating additional years of annual peak discharges, including the peaks for the April 2007 flood. In the southwest coastal region of Connecticut, the April 2007 peak discharges for streamflow-gaging stations with records extending back to 1955 were the second highest peak discharges on record; the 1955 annual peak discharges are the highest peak discharges in the station records. In the Housatonic and South Central Coast Basins, the April 2007 peak discharges for streamflow-gaging stations with records extending back to 1930 or earlier ranked between the fourth and eighth highest discharges on record, with the 1936, 1938, and 1955 floods as the largest floods in the station records. The peak discharges for the April 2007 flood have exceedance probabilities ranging between 0.10 to 0.02 (a 10- to 2-percent chance of being exceeded in a given year, respectively) with the majority (80 percent) of the stations having exceedance probabilities between 0.10 to 0.04. At three stations—Norwalk River at South Wilton, Pootatuck River at Sandy Hook, and Still River at Robertsville—the April 2007 peak discharges have an exceedance probability of 0.02. Flood-frequency estimates made after the April 2007 flood were compared to flood-frequency estimates used to derive the water-surface profiles (also called flood profiles) in FEMA Flood Insurance Studies developed for communities. In general, the comparison indicated that at the 0.10 exceedance probability (a 10-percent change of being exceeded in a given year), the discharges from the current (2007) flood-frequency analysis are larger than the discharges in the FEMA Flood Insurance Studies, with a median change of about +10 percent. In contrast, at the 0.01 exceedance probability (a 1-percent change of being exceeded in a year), the discharges from the current flood-frequency analysis are smaller than the discharges in the FEMA Flood Insurance Studies, with a median change of about -13 percent. Several stations had more than + 25 percent change in discharges at the 0.10 exceedance probability and are in the following communities: Winchester (Still River at Robertsville, +50 percent change); Hamden (Mill River near Hamden, +46 percent change); Woodbury (Weekeepeemee River at Hotchkissville, +29 percent change); and Newtown (Pootatuck River at Sandy Hook , +28 percent change). Although the majority of the streamflow-gaging stations had discharges at the 0.01 exceedance probability smaller than in the Flood Insurance Studies, the (2007) flood-frequency estimates were larger than in the Flood Insurance Studies for stations in the following communities: Hamden (Mill River near Hamden, +53 percent change); Thomaston (Naugatuck River at Thomaston, +27 percent change); Newtown (Pootatuck River at Sandy Hook, +18 percent change); and Wallingford (Quinnipiac River at Wallingford, +13 percent change). The 1-percent exceedance probability (100-year flood) elevations at streamflow-gaging stations exceeded the FEMA projected 100-year flood elevations by more than +0.5 feet in two Flood Insurance Studies in the communities of Wallingford (Quinnipiac River at Wallingford, +0.6 feet change) and Hamden (Mill River near Hamden, + 2.3 feet change).

Connecticut↗
USGS2009

Magnitude and Frequency of Rural Floods in the Southeastern United States, 2006: Volume 3, South Carolina

A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in South Carolina, Georgia, and North Carolina that are not substantially affected by regulation, tidal fluctuations, or urban development. Annual peak-flow data through September 2006 were analyzed for 943 streamgaging stations having 10 or more years of data on rural streams in South Carolina, Georgia, North Carolina, and adjacent parts of Alabama, Florida, Tennessee, and Virginia. Flood-frequency estimates were computed for the 943 stations by fitting the logarithms of annual peak flows for each station to a Pearson Type III distribution. As part of the computation of flood-frequency estimates for the stations, a new value for the generalized skew coefficient was developed using a Bayesian generalized least-squares regression model. Additionally, basin characteristics for these stations were computed by using a geographical information system and automated computer algorithms. Exploratory regression analyses using ordinary least-squares regression completed on the initial database of 943 gaged stations resulted in defining five hydrologic regions for South Carolina, Georgia, and North Carolina. Stations with drainage areas less than 1 square mile were removed from the database, and a procedure to examine for basin redundancy (based on drainage area and periods of record) also resulted in the removal of some stations from the regression database. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged basins in Georgia, South Carolina, and North Carolina. Flood-frequency estimates and basin characteristics for 828 streamgaging stations were combined to form the final database used in the regional regression analysis. The final predictive equations are all functions of drainage area and percentage of the drainage basin within each hydrologic region. Average errors of prediction for these regression equations range from 34.0 to 47.7 percent. Peak-flow records at 25 regulated stations were assessed to determine if a flood-frequency analysis was appropriate. Based on those assessments, flood-frequency estimates are provided for three regulated stations. Annual peak-flow data are provided for the regulated stations in an appendix.

South Carolina↗
USGS2009

A Multitracer Approach to Detecting Wastewater Plumes from Municipal Injection Wells in Nearshore Marine Waters at Kihei and Lahaina, Maui, Hawaii

Municipal wastewater plumes discharging from aquifer to ocean were detected by nearshore wading surveys at Kihei and Lahaina, on the island of Maui in Hawaii. Developed in cooperation with the Hawaii State Department of Health, the survey methodology included instrument trolling to detect submarine groundwater discharge, followed by analysis of water and macroalgae for a suite of chemical and isotopic constituents that constitute a 'multitracer' approach. Surveys were conducted May 6-28, 2008, during fair-weather conditions and included: (1) wading and kayak trolling with a multiparameter water-quality sonde, (2) marine water-column sampling, and (3) collection of benthic algae samples. Instrument trolling helped guide the water sampling strategy by providing dense, continuous transects of water properties on which groundwater discharge zones could be identified. Water and algae samples for costly chemical and isotopic laboratory analyses were last to be collected but were highly diagnostic of wastewater presence and nutrient origin because of low detection levels and confirmation across multiple tracers. Laboratory results confirmed the presence of wastewater constituents in marine water-column samples at both locales and showed evidence of modifying processes such as denitrification and mixing of effluent with surrounding groundwater and seawater. Carbamazepine was the most diagnostic pharmaceutical, detected in several marine water-column samples and effluent at both Kihei and Lahaina. Heavy nitrogen-isotope compositions in water and algae were highly diagnostic of effluent, particularly where enriched to even heavier values than effluent source compositions by denitrification. Algae provided an added advantage of time-integrating their nitrogen source during growth. The measured Kihei plume coincided almost exactly with prior model predictions, but the Lahaina plume was detected well south of the expected direct path from injection wells to shore and may be guided by a buried valley fill from an ancestral course of Honokowai Stream. Nutrient concentrations in upland wells at Lahaina were comparable to concentrations in wastewater but originate instead from agricultural fertilizers. A key factor in detecting and mapping the wastewater plumes was sampling very close to shore (mostly within 20 m or so) and in very shallow water (mostly 0.5 to 2 m depth). Effluent probably discharges somewhat offshore as well, although prior attempts to detect an injected fluorescent tracer at Lahaina in the 1990s were inconclusive, having focused farther offshore in water mostly 10-30 m deep. Sampling of benthic porewater and algae would offer the best chances for further effluent detection and mapping offshore, and sampling of onland monitor wells could provide additional understanding of geochemical processes that take place in the effluent plumes and bring about some degree of natural attenuation of nutrients.

Scientific Investigations Report↗
USGS2010

Field Surveys of Rare Plants on Santa Cruz Island, California, 2003-2006: Historical Records and Current Distributions

Santa Cruz Island is the largest of the northern Channel Islands located off the coast of California. It is owned and managed as a conservation reserve by The Nature Conservancy and the Channel Islands National Park. The island is home to nine plant taxa listed in 1997 as threatened or endangered under the federal Endangered Species Act, because of declines related to nearly 150 years of ranching on the island. Feral livestock were removed from the island as a major conservation step, which was part of a program completed in early 2007 with the eradication of pigs and turkeys. For the first time in more than a century, the rare plants of Santa Cruz Island have a chance to recover in the wild. This study provides survey information and living plant materials needed for recovery management of the listed taxa. We developed a database containing information about historical collections of the nine taxa and used it to plan a survey strategy. Our objectives were to relocate as many of the previously known populations as possible, with emphasis on documenting sites not visited in several decades, sites that were poorly documented in the historical record, and sites spanning the range of environmental conditions inhabited by the taxa. From 2003 through 2006, we searched for and found 39 populations of the taxa, indicating that nearly 80 percent of the populations known earlier in the 1900s still existed. Most populations are small and isolated, occupying native-dominated habitat patches in a highly fragmented and invaded landscape; they are still at risk of declining through population losses. Most are not expanding beyond the edges of their habitat patches. However, most taxa appeared to have good seed production and a range of size classes in populations, indicating a good capacity for plant recruitment and population growth in these restricted sites. For these taxa, seed collection and outplanting might be a good strategy to increase numbers of populations for species recovery. Several taxa have particular problems evidenced by lack of fruit set, very small population sizes, or unstable habitats. We collected seeds of all but two taxa for seed banking, and live cuttings of two clonal shrubs for cultivation at the Santa Barbara Botanic Garden. The survey data, seeds and cuttings provide a baseline and a foundation for planning, conducting, and tracking recovery of the nine federally listed plant taxa of Santa Cruz Island.

Scientific Investigations Report↗
USGS2010

Flood of April and May 2008 in Northern Maine

Severe flooding occurred in Aroostook and Penobscot Counties in northern Maine between April 28 and May 1, 2008, and was most extreme in the town of Fort Kent. Peak streamflows in northern Aroostook County were the result of a persistent heavy snowpack that caused high streamflows when it quickly melted during the third week of April 2008. Snowmelt was followed by from two to four inches of rainfall over a 2-day period in northern Maine. Peak water-surface elevations resulting from the flood were obtained from 13 continuous-record streamgages and 63 surveyed high-water marks in Aroostook and Penobscot Counties. Peak streamflows were obtained from 20 sites on 15 streams through stage/discharge rating curves or hydraulic flow models. Peak water-surface elevations and streamflows were the highest ever recorded at seven continuous-record streamgages, which had between 25 and 84 years of record in northern Aroostook County. The annual exceedance probability (the percent chance of exceeding the streamflow recorded during the April/May 2008 flood during any given year) at six streamgages in northern Maine was equal to or less than 1 percent. Data from flood-insurance studies published by the Federal Emergency Management Agency were available for five of the locations analyzed for the April/May 2008 flood and were compared to streamflows and observed peak water-surface elevations from the 2008 flood. Water-surface elevations that would be expected given the observed flow as applied to the effective flood insurance studies ranged from between 1 and 4 feet from the water-surface elevations observed during the 2008 flood. Differences were likely the result of up to 30 years of additional data for the calculation of recurrence intervals and the fact that hydraulic models used for the models had not previously been calibrated to a flood of this magnitude.

Scientific Investigations Report↗
USGS2010

Flood-depth frequency relations for rural streams in Alabama, 2003

Equations have been defined for estimating the depth of water for floods having a 67-, 50-, 20-, 10-, 4-, 2-, and 1-percent chance exceedance on rural streams in Alabama. Multiple regression analyses of streamgage data were used to define the equations. Eight basin and climatic characteristics that were computed by using a geographical information system were evaluated as independent variables to determine their statistical significance for the dependent variable, flood depth. Drainage area was the most statistically significant independent variable tested. Addition of other significant variables did not decrease the standard error of prediction by more than 2 percent. Regression relations, for four different hydrologic regions, were developed to estimate flood depth for rural, ungaged streams as a function of the basin drainage area. These relations are based on computed depths that correspond to the flood magnitude and frequency for 164 streamgages in Alabama and 42 streamgages in adjacent States having at least 10 years of consecutive record. These relations utilize observed flood data collected through 2003. The geologic, physiographic, and climatic variability affecting flood depth is reflected in the constant (intercept) and exponent (slope) for each regional regression equation. Average standard errors of prediction for these regression equations range from 18 to 38 percent.

Scientific Investigations Report↗
USGS2010

Flood study of the Suncook River in Epsom, Pembroke, and Allenstown, New Hampshire, 2009

On May 15, 2006, a breach in the riverbank caused an avulsion in the Suncook River in Epsom, NH. The breach in the riverbank and subsequent avulsion changed the established flood zones along the Suncook River; therefore, a new flood study was needed to reflect this change and aid in flood recovery and restoration. For this flood study, the hydrologic and hydraulic analyses for the Suncook River were conducted by the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency. This report presents water-surface elevations and profiles determined using the U.S. Army Corps of Engineers one-dimensional Hydrologic Engineering Center River Analysis System model, also known as HEC-RAS. Steady-state water-surface profiles were developed for the Suncook River from its confluence with the Merrimack River in the Village of Suncook (in Allenstown and Pembroke, NH) to the upstream corporate limit of the town of Epsom, NH (approximately 15.9 river miles). Floods of magnitudes that are expected to be equaled or exceeded once on the average during any 2-, 5-, 10-, 25-, 50-, 100-, or 500-year period (recurrence interval) were modeled using HEC-RAS. These flood events are referred to as the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year floods and have a 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent chance, respectively, of being equaled or exceeded during any year. The 10-, 50-, 100-, and 500-year flood events are important for flood-plain management, determination of flood-insurance rates, and design of structures such as bridges and culverts. The analyses in this study reflect flooding potentials that are based on existing conditions in the communities of Epsom, Pembroke, and Allenstown at the time of completion of this study (2009). Changes in the 100-year recurrence-interval flood elevation from the 1979 flood study were typically less than 2 feet with the exception of a location 900 feet upstream from the avulsion that, because of backwater from the dams in the abandoned channel, was 12 feet higher in the 1979 flood study than in this study.

Scientific Investigations Report↗
USGS2011

Magnitude and frequency of floods for rural streams in Florida, 2006

Methods for estimating the magnitude of floods for selected percent chance exceedance probabilities are presented for ungaged streams in Florida that are not sub stantially affected by regulation, channelization, or urban development. Flood-frequency flows also are presented for 275 Florida streamgages used in the regional regression analysis. Regression relations used generalized least-squares regression techniques to estimate flood magnitude and frequency on ungaged streams as a function of basin drainage area and a storage factor. These regression equations were developed for four different hydrologic regions in Florida. The flood regions were delineated based on plotted residuals, previous flood-frequency studies, and geologic, physiographic, and drainage-area maps. The methods used in this report are based on flood-frequency characteristics for 305 streamgages including 275 in Florida and 30 in the adjacent states of Georgia and Alabama, all having at least 10 years of record through September 2006. For the larger streams outside the limits of the regression equations-the Apalachicola River and Suwannee River at Ellaville and below-the report includes graphical relations of peak flow to drainage area.

Scientific Investigations Report↗
USGS2011

Peak-flow characteristics of Virginia streams

Peak-flow annual exceedance probabilities, also called probability-percent chance flow estimates, and regional regression equations are provided describing the peak-flow characteristics of Virginia streams. Statistical methods are used to evaluate peak-flow data. Analysis of Virginia peak-flow data collected from 1895 through 2007 is summarized. Methods are provided for estimating unregulated peak flow of gaged and ungaged streams. Station peak-flow characteristics identified by fitting the logarithms of annual peak flows to a Log Pearson Type III frequency distribution yield annual exceedance probabilities of 0.5, 0.4292, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 for 476 streamgaging stations. Stream basin characteristics computed using spatial data and a geographic information system are used as explanatory variables in regional regression model equations for six physiographic regions to estimate regional annual exceedance probabilities at gaged and ungaged sites. Weighted peak-flow values that combine annual exceedance probabilities computed from gaging station data and from regional regression equations provide improved peak-flow estimates. Text, figures, and lists are provided summarizing selected peak-flow sites, delineated physiographic regions, peak-flow estimates, basin characteristics, regional regression model equations, error estimates, definitions, data sources, and candidate regression model equations. This study supersedes previous studies of peak flows in Virginia.

Virginia↗
USGS2012

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

Urban development alters important physical, chemical, and biological processes that define urban stream ecosystems. An approach was developed for quantifying the effects of these processes on aquatic biota, and then linking those effects to endpoints that can be used for environmental management. These complex, interacting systems are challenging to model from a scientific standpoint. A desirable model clearly shows the system, simulates the interactions, and ultimately predicts results of management actions. Traditional regression techniques that calculate empirical relations between pairs of environmental factors do not capture the interconnected web of multiple stressors, but urban development effects are not yet understood at the detailed scales required to make mechanistic modeling approaches feasible. Therefore, in contrast to a fully deterministic or fully statistical modeling approach, a Bayesian network model provides a hybrid approach that can be used to represent known general associations between variables while acknowledging uncertainty in predicted outcomes. It does so by quantifying an expert-elicited network of probabilistic relations between variables. Advantages of this modeling approach include (1) flexibility in accommodating many model specifications and information types; (2) efficiency in storing and manipulating complex information, and to parameterize; and (3) transparency in describing the relations using nodes and arrows and in describing uncertainties with discrete probability distributions for each variable. In realization of the aforementioned advantages, a Bayesian network model was constructed to characterize the effect of urban development on aquatic macroinvertebrate stream communities through three simultaneous, interacting ecological pathways affecting stream hydrology, habitat, and water quality across watersheds in the Northeastern United States. This model incorporates both empirical data and expert knowledge to calculate the probabilities of attaining desired aquatic ecosystem conditions under different urban stress levels, environmental conditions, and management options. Ecosystem conditions are characterized in terms of standardized Biological Condition Gradient (BCG) management endpoints. This approach to evaluating urban development-induced perturbations in watersheds integrates statistical and mechanistic perspectives, different information sources, and several ecological processes into a comprehensive description of the system that can be used to support decision making. The completed model can be used to infer which management actions would lead to the highest likelihood of desired BCG tier achievement. For example, if best management practices (BMP) were implemented in a highly urbanized watershed to reduce flashiness to medium levels and specific conductance to low levels, the stream would have a 70-percent chance of achieving BCG Tier 3 or better, relative to a 24-percent achievement likelihood for unmanaged high urban land cover. Results are reported probabilistically to account for modeling uncertainty that is inherent in sources such as natural variability and model simplification error.

Scientific Investigations Report↗
USGS2012

Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio

Digital flood-inundation maps for selected reaches of South Fork Licking River, Raccoon Creek, North Fork Licking River, and the Licking River in Licking County, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the following USGS streamgages: South Fork Licking River at Heath, Ohio (03145173); Raccoon Creek below Wilson Street at Newark, Ohio (03145534); North Fork Licking River at East Main Street at Newark, Ohio (03146402); and Licking River near Newark, Ohio (03146500). The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. As part of the flood-warning streamflow network, the USGS re-installed one streamgage on North Fork Licking River, and added three new streamgages, one each on North Fork Licking River, South Fork Licking River, and Raccoon Creek. Additionally, the USGS upgraded a lake-level gage on Buckeye Lake. Data from the streamgages and lake-level gage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating steady-state step-backwater models to selected, established streamgage rating curves. The step-backwater models then were used to determine water-surface-elevation profiles for up to 10 flood stages at a streamgage with corresponding streamflows ranging from approximately the 50 to 0.2-percent chance annual-exceedance probabilities for each of the 4 streamgages that correspond to the flood-inundation maps. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of Licking County showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. The USGS also developed an unsteady-flow model for a reach of South Fork Licking River for use by the NWS to enhance their ability to provide advanced flood warning in the region north of Buckeye Lake, Ohio. The unsteady-flow model was calibrated based on data from four flooding events that occurred from June 2008 to December 2011. Model calibration was approximate due to the fact that there were unmeasured inflows to the river that were not able to be considered during the calibration. Information on unmeasured inflow derived from NWS hydrologic models and additional flood-event data could enable the NWS to further refine the unsteady-flow model.

Ohio↗
USGS2013

Critical analysis of world uranium resources

The U.S. Department of Energy, Energy Information Administration (EIA) joined with the U.S. Department of the Interior, U.S. Geological Survey (USGS) to analyze the world uranium supply and demand balance. To evaluate short-term primary supply (0–15 years), the analysis focused on Reasonably Assured Resources (RAR), which are resources projected with a high degree of geologic assurance and considered to be economically feasible to mine. Such resources include uranium resources from mines currently in production as well as resources that are in the stages of feasibility or of being permitted. Sources of secondary supply for uranium, such as stockpiles and reprocessed fuel, were also examined. To evaluate long-term primary supply, estimates of uranium from unconventional and from undiscovered resources were analyzed. At 2010 rates of consumption, uranium resources identified in operating or developing mines would fuel the world nuclear fleet for about 30 years. However, projections currently predict an increase in uranium requirements tied to expansion of nuclear energy worldwide. Under a low-demand scenario, requirements through the period ending in 2035 are about 2.1 million tU. In the low demand case, uranium identified in existing and developing mines is adequate to supply requirements. However, whether or not these identified resources will be developed rapidly enough to provide an uninterrupted fuel supply to expanded nuclear facilities could not be determined. On the basis of a scenario of high demand through 2035, 2.6 million tU is required and identified resources in operating or developing mines is inadequate. Beyond 2035, when requirements could exceed resources in these developing properties, other sources will need to be developed from less well-assured resources, deposits not yet at the prefeasibility stage, resources that are currently subeconomic, secondary sources, undiscovered conventional resources, and unconventional uranium supplies. This report’s analysis of 141 mines that are operating or are being actively developed identifies 2.7 million tU of in-situ uranium resources worldwide, approximately 2.1 million tU recoverable after mining and milling losses were deducted. Sixty-four operating mines report a total of 1.4 million tU of in-situ RAR (about 1 million tU recoverable). Seventy-seven developing mines/production centers report 1.3 million tU in-situ Reasonably Assured Resources (RAR) (about 1.1 million tU recoverable), which have a reasonable chance of producing uranium within 5 years. Most of the production is projected to come from conventional underground or open pit mines as opposed to in-situ leach mines. Production capacity in operating mines is about 76,000 tU/yr, and in developing mines is estimated at greater than 52,000 tU/yr. Production capacity in operating mines should be considered a maximum as mines seldom produce up to licensed capacity due to operational difficulties. In 2010, worldwide mines operated at 70 percent of licensed capacity, and production has never exceeded 89 percent of capacity. The capacity in developing mines is not always reported. In this study 35 percent of developing mines did not report a target licensed capacity, so estimates of future capacity may be too low. The Organisation for Economic Co-operation and Development’s Nuclear Energy Agency (NEA) and International Atomic Energy Agency (IAEA) estimate an additional 1.4 million tU economically recoverable resources, beyond that identified in operating or developing mines identified in this report. As well, 0.5 million tU in subeconomic resources, and 2.3 million tU in the geologically less certain inferred category are identified worldwide. These agencies estimate 2.2 million tU in secondary sources such as government and commercial stockpiles and re-enriched uranium tails. They also estimate that unconventional uranium supplies (uraniferous phosphate and black shale deposits) may contain up to 7.6 million tU. Although unconventional resources are currently subeconomic, the improvement of extraction techniques or the production of coproducts may make extraction of uranium from these types of deposits profitable. A large undiscovered resource base is reported by these agencies, however this class of resource should be considered speculative and will require intensive exploration programs to adequately define them as mineable. These resources may all contribute to uranium supply that would fuel the world nuclear fleet well beyond that calculated in this report. Production of resources in both operating and developing uranium mines is subject to uncertainties caused by technical, legal, regulatory, and financial challenges that combined to create long timelines between deposit discovery and mine production. This analysis indicates that mine development is proceeding too slowly to fully meet requirements for an expanded nuclear power reactor fleet in the near future (to 2035), and unless adequate secondary or unconventional resources can be identified, imbalances in supply and demand may occur.

Scientific Investigations Report↗
USGS2014

Flood inundation maps and water-surface profiles for tropical storm Irene and selected annual exceedance probability floods for Flint Brook and the Third Branch White River in Roxbury, Vermont

Flint Brook, a tributary to the Third Branch White River in Roxbury, Vermont, has a history of flooding the Vermont Fish and Wildlife Department’s Roxbury Fish Culture Station (the hatchery) and surrounding infrastructure. Flooding resulting from tropical storm Irene on August 28–29, 2011, caused widespread destruction in the region, including extensive and costly damages to the State-owned hatchery and the transportation infrastructure in the Town of Roxbury, Vermont. Sections of State Route 12A were washed out, and several bridges and culverts on Oxbow Road, Thurston Hill Road, and the New England Central Railroad in Roxbury were heavily damaged. Record high peak-discharge estimates of 2,140 cubic feet per second (ft 3 /s) and 4,320 ft 3 /s were calculated for Flint Brook at its confluence with the Third Branch White River and for the Third Branch White River at about 350 feet (ft) downstream from the hatchery, respectively. The annual exceedance probabilities (AEPs) of the peak discharges for Flint Brook and the Third Branch White River were less than 0.2 percent (less than a one in 500 chance of occurring in a given year). Hydrologic and hydraulic analyses of Flint Brook and the Third Branch White River were done to investigate flooding at the hatchery in Roxbury and support efforts by the Federal Emergency Management Agency to assist State and local mitigation and reconstruction efforts. During the August 2011 flood, the majority of flow from Flint Brook (97 percent or 2,070 ft 3 /s) diverged from its primary watercourse due to a retaining wall failure immediately upstream of Oxbow Road and inundated the hatchery. Although a minor amount of flow from the Third Branch White River could have overtopped State Route 12A and spilled into the hatchery, the Third Branch White River did not cause flood damages or exacerbate flooding at the hatchery during the August 2011 flood. The Third Branch White River which flows adjacent to the hatchery does not flood the hatchery for the 10-, 2-, 1, or 0.2-percent annual exceedance probabilities. The simulated water-surface elevations for August 2011 flood equal the elevations of State Route 12A about 500 ft downstream of Thurston Hill Road adjacent to the troughs between the rearing ponds. Four flood mitigation alternatives being considered by the Vermont Agency of Transportation to improve the hydraulic performance of Flint Brook and reduce the risk of flooding at the hatchery include: (A) no changes to the infrastructure or existing alignment of Flint Brook (existing conditions [2014]), (B) structural changes to the bridges and the existing retaining wall along Flint Brook, (C) realignment of Flint Brook to flow along the south side of Oxbow Road to accommodate larger stream discharges, and (D) a diversion channel for flows greater than 1-percent annual exceedance probability. Although the 10-, 2-, and 1-percent AEP floods do not flood the hatchery under alternative A (no changes to the infrastructure), the 0.2-percent AEP flow still poses a flooding threat to the hatchery because flow will continue to overtop the existing retaining wall and flood the hatchery. Under the other mitigation alternatives (B, C, and D) that include some variation of structural changes to bridges, a retaining wall, and (or) channel, the peak discharges for the 10-, 2-, 1-, and 0.2-percent annual exceedance probabilities do not flood the hatchery. Water-surface profiles and flood inundation maps of the August 2011 flood and the 10-, 2-, 1-, and 0.2-percent AEPs for four mitigation alternatives were developed for Flint Brook and the Third Branch White River in the vicinity of the hatchery and can be used by the Federal, State, and local agencies to better understand the potential for future flooding at the hatchery.

Vermont↗
USGS2014

Flood-inundation maps and updated components for a flood-warning system or the City of Marietta, Ohio and selected communities along the Lower Muskingum River and Ohio River

Digital flood-inundation maps for lower reaches of the Muskingum River and a reach of the Ohio River in southeast Ohio were created by the U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District and the City of Marietta, Ohio. To complete the inundation maps, Ohio River and lower Muskingum River bathymetry was updated and two streamgages, one on the Ohio River upstream of Marietta near Sardis, Ohio, and one on the Muskingum River in Beverly, Ohio, were added as basic components of the flood-warning system. An updated hydraulic model component also led to the new flood-inundation maps. The maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent of flooding corresponding to water levels (stages) at one or more of the following USGS streamgages: Muskingum River at McConnelsville, Ohio (03150000); Muskingum River at Beverly, Ohio (03150500); and Ohio River at Marietta, Ohio (03150700). The maps can be used in conjunction with National Weather Service flood-forecast data to show areas of estimated flood inundation associated with forecasted flood-peak stages. Flood profiles for selected reaches were prepared by calibrating steady-state step-backwater models to selected streamgage rating curves. The step-backwater models were used to determine water-surface-elevation profiles for up to 12 flood stages at a streamgage with corresponding stream-flows ranging from approximately the 10- to 0.2-percent chance annual-exceedance probabilities for each of the 3 streamgages that correspond to the flood-inundation maps. Additional hydraulic modeling was used to account for the effects of backwater from the Ohio River on water levels in the Muskingum River. The computed longitudinal profiles of flood levels were used with a Geographic Information System digital elevation model (derived from light detection and ranging) to delineate flood-inundation areas. Digital maps showing flood-inundation areas overlain on digital orthophotographs were prepared for the selected floods.

Ohio↗
USGS2017

Estimation of low-flow statistics at ungaged sites on streams in the Lower Hudson River Basin, New York, from data in geographic information systems

A variety of watershed properties available in 2015 from geographic information systems were tested in regression equations to estimate two commonly used statistical indices of the low flow of streams, namely the lowest flows averaged over 7 consecutive days that have a 1 in 10 and a 1 in 2 chance of not being exceeded in any given year (7-day, 10-year and 7-day, 2-year low flows). The equations were based on streamflow measurements in 51 watersheds in the Lower Hudson River Basin of New York during the years 1958–1978, when the number of streamflow measurement sites on unregulated streams was substantially greater than in subsequent years. These low-flow indices are chiefly a function of the area of surficial sand and gravel in the watershed; more precisely, 7-day, 10-year and 7-day, 2-year low flows both increase in proportion to the area of sand and gravel deposited by glacial meltwater, whereas 7-day, 2-year low flows also increase in proportion to the area of postglacial alluvium. Both low-flow statistics are also functions of mean annual runoff (a measure of net water input to the watershed from precipitation) and area of swamps and poorly drained soils in or adjacent to surficial sand and gravel (where groundwater recharge is unlikely and riparian water loss to evapotranspiration is substantial). Small but significant refinements in estimation accuracy resulted from the inclusion of two indices of stream geometry, channel slope and length, in the regression equations. Most of the regression analysis was undertaken with the ordinary least squares method, but four equations were replicated by using weighted least squares to provide a more realistic appraisal of the precision of low-flow estimates. The most accurate estimation equations tested in this study explain nearly 84 and 87 percent of the variation in 7-day, 10-year and 7-day, 2-year low flows, respectively, with standard errors of 0.032 and 0.050 cubic feet per second per square mile. The equations use natural values of streamflow and watershed properties; logarithmic transformations yielded less accurate equations inconsistent with some conceptualized relationships.

New York↗