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Sample records for underground streamflow hydrograph

  1. An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri

    Science.gov (United States)

    Huizinga, Richard J.

    2014-01-01

    Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed.

  2. Hydrograph separation techniques in snowmelt-dominated watersheds

    Science.gov (United States)

    Miller, S.; Miller, S. N.

    2017-12-01

    This study integrates hydrological, geochemical, and isotopic data for a better understanding of different streamflow generation pathways and residence times in a snowmelt-dominated region. A nested watershed design with ten stream gauging sites recording sub-hourly stream stage has been deployed in a snowmelt-dominated region in southeastern Wyoming, heavily impacted by the recent bark beetle epidemic. LiDAR-derived digital elevation models help elucidate effects from topography and watershed metrics. At each stream gauging site, sub-hourly stream water conductivity and temperature data are also recorded. Hydrograph separation is a useful technique for determining different sources of runoff and how volumes from each source vary over time. Following previous methods, diurnal cycles from sub-hourly recorded streamflow and specific conductance data are analyzed and used to separate hydrographs into overland flow and baseflow components, respectively. A final component, vadose-zone flow, is assumed to be the remaining water from the total hydrograph. With access to snowmelt and precipitation data from nearby instruments, runoff coefficients are calculated for the different mechanisms, providing information on watershed response. Catchments are compared to understand how different watershed characteristics translate snowmelt or precipitation events into runoff. Portable autosamplers were deployed at two of the gauging sites for high-frequency analysis of stream water isotopic composition during peak flow to compare methods of hydrograph separation. Sampling rates of one or two hours can detect the diurnal streamflow cycle common during peak snowmelt. Prior research suggests the bark beetle epidemic has had little effect on annual streamflow patterns; however, several results show an earlier shift in the day of year in which peak annual streamflow is observed. The diurnal cycle is likely to comprise a larger percentage of daily streamflow during snowmelt in post

  3. How important is the spatiotemporal structure of a rainfall field when generating a streamflow hydrograph? An investigation using Reverse Hydrology

    Science.gov (United States)

    Kretzschmar, Ann; Tych, Wlodek; Beven, Keith; Chappell, Nick

    2017-04-01

    Flooding is the most widely occurring natural disaster affecting thousands of lives and businesses worldwide each year, and the size and frequency of flood-events are predicted to increase with climate change. The main input-variable for models used in flood prediction is rainfall. Estimating the rainfall input is often based on a sparse network of raingauges, which may or may not be representative of the salient rainfall characteristics responsible for generating of storm-hydrographs. A method based on Reverse Hydrology (Kretzschmar et al 2014 Environ Modell Softw) has been developed and is being tested using the intensively-instrumented Brue catchment (Southwest England) to explore the spatiotemporal structure of the rainfall-field (using 23 rain gauges over the 135.2 km2 basin). We compare how well the rainfall measured at individual gauges, or averaged over the basin, represent the rainfall inferred from the streamflow signal. How important is it to get the detail of the spatiotemporal rainfall structure right? Rainfall is transformed by catchment processes as it moves to streams, so exact duplication of the structure may not be necessary. 'True' rainfall estimated using 23 gauges / 135.2 km2 is likely to be a good estimate of the overall-catchment-rainfall, however, the integration process 'smears' the rainfall patterns in time, i.e. reduces the number of and lengthens rain-events as they travel across the catchment. This may have little impact on the simulation of stream-hydrographs when events are extensive across the catchment (e.g., frontal rainfall events) but may be significant for high-intensity, localised convective events. The Reverse Hydrology approach uses the streamflow record to infer a rainfall sequence with a lower time-resolution than the original input time-series. The inferred rainfall series is, however, able simulate streamflow as well as the observed, high resolution rainfall (Kretzschmar et al 2015 Hydrol Res). Most gauged catchments in

  4. HYDRORECESSION: A toolbox for streamflow recession analysis

    Science.gov (United States)

    Arciniega, S.

    2015-12-01

    Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.

  5. A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area

    Science.gov (United States)

    Asquith, William H.; Cleveland, Theodore G.; Roussel, Meghan C.

    2011-01-01

    Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational

  6. Multi-site Stochastic Simulation of Daily Streamflow with Markov Chain and KNN Algorithm

    Science.gov (United States)

    Mathai, J.; Mujumdar, P.

    2017-12-01

    A key focus of this study is to develop a method which is physically consistent with the hydrologic processes that can capture short-term characteristics of daily hydrograph as well as the correlation of streamflow in temporal and spatial domains. In complex water resource systems, flow fluctuations at small time intervals require that discretisation be done at small time scales such as daily scales. Also, simultaneous generation of synthetic flows at different sites in the same basin are required. We propose a method to equip water managers with a streamflow generator within a stochastic streamflow simulation framework. The motivation for the proposed method is to generate sequences that extend beyond the variability represented in the historical record of streamflow time series. The method has two steps: In step 1, daily flow is generated independently at each station by a two-state Markov chain, with rising limb increments randomly sampled from a Gamma distribution and the falling limb modelled as exponential recession and in step 2, the streamflow generated in step 1 is input to a nonparametric K-nearest neighbor (KNN) time series bootstrap resampler. The KNN model, being data driven, does not require assumptions on the dependence structure of the time series. A major limitation of KNN based streamflow generators is that they do not produce new values, but merely reshuffle the historical data to generate realistic streamflow sequences. However, daily flow generated using the Markov chain approach is capable of generating a rich variety of streamflow sequences. Furthermore, the rising and falling limbs of daily hydrograph represent different physical processes, and hence they need to be modelled individually. Thus, our method combines the strengths of the two approaches. We show the utility of the method and improvement over the traditional KNN by simulating daily streamflow sequences at 7 locations in the Godavari River basin in India.

  7. Preliminary stage and streamflow data at selected U.S. Geological Survey streamgages in Maine and New Hampshire for the flood of October 30–31, 2017

    Science.gov (United States)

    Kiah, Richard G.; Stasulis, Nicholas W.

    2018-03-08

    Rainfall from a storm on October 24–27, 2017, and Tropical Storm Philippe on October 29–30, created conditions that led to flooding across portions of New Hampshire and western Maine. On the basis of streamflow data collected at 30 selected U.S. Geological Survey (USGS) streamgages in the Androscoggin River, Connecticut River, Merrimack River, and Saco River Basins, the storms caused minor to moderate flooding in those basins on October 30–31, 2017. During the storms, the USGS deployed hydrographers to take discrete measurements of streamflow. The measurements were used to confirm the stage-to-streamflow relation (rating curve) at the selected USGS streamgages. Following the storms, hydrographers documented high-water marks in support of indirect measurements of streamflow. Seven streamgages with greater than 50 years of streamflow data recorded preliminary streamflow peaks within the top five for the periods of record. Twelve streamgages recorded preliminary peak streamflows greater than an estimate of the 100-year streamflow based on drainage area.

  8. Application of the Water Erosion Prediction Project (WEPP) Model to simulate streamflow in a PNW forest watershed

    Science.gov (United States)

    A. Srivastava; M. Dobre; E. Bruner; W. J. Elliot; I. S. Miller; J. Q. Wu

    2011-01-01

    Assessment of water yields from watersheds into streams and rivers is critical to managing water supply and supporting aquatic life. Surface runoff typically contributes the most to peak discharge of a hydrograph while subsurface flow dominates the falling limb of hydrograph and baseflow contributes to streamflow from shallow unconfined aquifers primarily during the...

  9. Streamflow characteristics and benthic invertebrate assemblages in streams across the western United States

    Science.gov (United States)

    Brasher, Anne M.D.; Konrad, Chris P.; May, Jason T.; Edmiston, C. Scott; Close, Rebecca N.

    2010-01-01

    Hydrographic characteristics of streamflow, such as high-flow pulses, base flow (background discharge between floods), extreme low flows, and floods, significantly influence aquatic organisms. Streamflow can be described in terms of magnitude, timing, duration, frequency, and variation (hydrologic regime). These characteristics have broad effects on ecosystem productivity, habitat structure, and ultimately on resident fish, invertebrate, and algae communities. Increasing human use of limited water resources has modified hydrologic regimes worldwide. Identifying the most ecologically significant hydrographic characteristics would facilitate the development of water-management strategies.Benthic invertebrates include insects, mollusks (snails and clams), worms, and crustaceans (shrimp) that live on the streambed. Invertebrates play an important role in the food web, consuming other invertebrates and algae and being consumed by fish and birds. Hydrologic alteration associated with land and water use can change the natural hydrologic regime and may affect benthic invertebrate assemblage composition and structure through changes in density of invertebrates or taxa richness (number of different species).This study examined associations between the hydrologic regime and characteristics of benthic invertebrate assemblages across the western United States and developed tools to identify streamflow characteristics that are likely to affect benthic invertebrate assemblages.

  10. Isotope-based partitioning of streamflow in the oil sands region, northern Alberta: Towards a monitoring strategy for assessing flow sources and water quality controls

    Directory of Open Access Journals (Sweden)

    J.J. Gibson

    2016-03-01

    Full Text Available Study region: This study is based on the rapidly developing Athabasca Oil Sands region, northeastern Alberta. Study focus: Hydrograph separation using stable isotopes of water is applied to partition streamflow sources in the Athabasca River and its tributaries. Distinct isotopic labelling of snow, rain, groundwater and surface water are applied to estimate the contribution of these sources to streamflow from analysis of multi-year records of isotopes in streamflow. New hydrological insights for the region: The results provide new insight into runoff generation mechanisms operating in six tributaries and at four stations along the Athabasca River. Groundwater, found to be an important flow source at all stations, is the dominant component of the hydrograph in three tributaries (Steepbank R., Muskeg R., Firebag R., accounting for 39–50% of annual streamflow. Surface water, mainly drainage from peatlands, is also found to be widely important, and dominant in three tributaries (Clearwater R., Mackay R., Ells R., accounting for 45–81% of annual streamflow. Fairly limited contributions from direct precipitation illustrate that most snow and rain events result in indirect displacement of pre-event water by fill and spill mechanisms. Systematic shifts in regional groundwater to surface-water ratios are expected to be an important control on spatial and temporal distribution of water quality parameters and useful for evaluating the susceptibility of rivers to climate and development impacts. Keywords: Stable isotopes, Hydrograph separation, Groundwater, Surface water, Snowmelt, Oil sands

  11. Shallow and Deep Groundwater Contributions to Ephemeral Streamflow Generation

    Science.gov (United States)

    Zimmer, M. A.; McGlynn, B. L.

    2016-12-01

    Our understanding of streamflow generation processes in low relief, humid landscapes is limited. To address this, we utilized an ephemeral-to-intermittent drainage network in the Piedmont region of the United States to gain new understanding about the drivers of ephemeral streamflow generation, stream-groundwater interactions, and longitudinal expansion and contraction of the stream network. We used hydrometric and chemical data collected within zero through second order catchments to characterize streamflow and overland, shallow soil, and deep subsurface flow across landscape positions. Results showed bi-directionality in stream-groundwater gradients that were dependent on catchment storage state. This led to annual groundwater recharge magnitudes that were similar to annual streamflow. Perched shallow and deep water table contributions shifted dominance with changes in catchment storage state, producing distinct stream hydrograph recession constants. Active channel length versus runoff followed a consistent relationship independent of storage state, but exhibited varying discharge-solute hysteresis directions. Together, our results suggest that temporary streams can act as both important groundwater recharge and discharge locations across the landscape, especially in this region where ephemeral drainage densities are among the highest recorded. Our results also highlight that the internal catchment dynamics that generate temporary streams play an important role in dictating biogeochemical fluxes at the landscape scale.

  12. U.S. Geological Survey groundwater toolbox, a graphical and mapping interface for analysis of hydrologic data (version 1.0): user guide for estimation of base flow, runoff, and groundwater recharge from streamflow data

    Science.gov (United States)

    Barlow, Paul M.; Cunningham, William L.; Zhai, Tong; Gray, Mark

    2015-01-01

    This report is a user guide for the streamflow-hydrograph analysis methods provided with version 1.0 of the U.S. Geological Survey (USGS) Groundwater Toolbox computer program. These include six hydrograph-separation methods to determine the groundwater-discharge (base-flow) and surface-runoff components of streamflow—the Base-Flow Index (BFI; Standard and Modified), HYSEP (Fixed Interval, Sliding Interval, and Local Minimum), and PART methods—and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater recharge from streamflow data. The Groundwater Toolbox is a customized interface built on the nonproprietary, open source MapWindow geographic information system software. The program provides graphing, mapping, and analysis capabilities in a Microsoft Windows computing environment. In addition to the four hydrograph-analysis methods, the Groundwater Toolbox allows for the retrieval of hydrologic time-series data (streamflow, groundwater levels, and precipitation) from the USGS National Water Information System, downloading of a suite of preprocessed geographic information system coverages and meteorological data from the National Oceanic and Atmospheric Administration National Climatic Data Center, and analysis of data with several preprocessing and postprocessing utilities. With its data retrieval and analysis tools, the Groundwater Toolbox provides methods to estimate many of the components of the water budget for a hydrologic basin, including precipitation; streamflow; base flow; runoff; groundwater recharge; and total, groundwater, and near-surface evapotranspiration.

  13. What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations

    Science.gov (United States)

    Betterle, A.; Radny, D.; Schirmer, M.; Botter, G.

    2017-12-01

    The spatial correlation of daily streamflows represents a statistical index encapsulating the similarity between hydrographs at two arbitrary catchment outlets. In this work, a process-based analytical framework is utilized to investigate the hydrological drivers of streamflow spatial correlation through an extensive application to 78 pairs of stream gauges belonging to 13 unregulated catchments in the eastern United States. The analysis provides insight on how the observed heterogeneity of the physical processes that control flow dynamics ultimately affect streamflow correlation and spatial patterns of flow regimes. Despite the variability of recession properties across the study catchments, the impact of heterogeneous drainage rates on the streamflow spatial correlation is overwhelmed by the spatial variability of frequency and intensity of effective rainfall events. Overall, model performances are satisfactory, with root mean square errors between modeled and observed streamflow spatial correlation below 10% in most cases. We also propose a method for estimating streamflow correlation in the absence of discharge data, which proves useful to predict streamflow regimes in ungauged areas. The method consists in setting a minimum threshold on the modeled flow correlation to individuate hydrologically similar sites. Catchment outlets that are most correlated (ρ>0.9) are found to be characterized by analogous streamflow distributions across a broad range of flow regimes.

  14. Phosphorus Export Model Development in a Terminal Lake Basin using Concentration-Streamflow Relationship

    Science.gov (United States)

    Jeannotte, T.; Mahmood, T. H.; Matheney, R.; Hou, X.

    2017-12-01

    Nutrient export to streams and lakes by anthropogenic activities can lead to eutrophication and degradation of surface water quality. In Devils Lake, ND, the only terminal lake in the Northern Great Plains, the algae boom is of great concern due to the recent increase in streamflow and consequent rise in phosphorus (P) export from prairie agricultural fields. However, to date, very few studies explored the concentration (c) -streamflow (q) relationship in the headwater catchments of the Devils Lake basin. A robust watershed-scale quantitative framework would aid understanding of the c-q relationship, simulating P concentration and load. In this study, we utilize c-q relationships to develop a simple model to estimate phosphorus concentration and export from two headwater catchments of different size (Mauvais Coulee: 1032 km2 and Trib 3: 160 km2) draining to Devils Lake. Our goal is to link the phosphorus export model with a physically based hydrologic model to identify major drivers of phosphorus export. USGS provided the streamflow measurements, and we collected water samples (filtered and unfiltered) three times daily during the spring snowmelt season (March 31, 2017- April 12, 2017) at the outlets of both headwater catchments. Our results indicate that most P is dissolved and very little is particulate, suggesting little export of fine-grained sediment from agricultural fields. Our preliminary analyses in the Mauvais Coulee catchment show a chemostatic c-q relationship in the rising limb of the hydrograph, while the recession limb shows a linear and positive c-q relationship. The poor correlation in the rising limb of the hydrograph suggests intense flushing of P by spring snowmelt runoff. Flushing then continues in the recession limb of the hydrograph, but at a more constant rate. The estimated total P load for the Mauvais Coulee basin is 193 kg/km2, consistent with other catchments of similar size across the Red River of the North basin to the east. We expect

  15. An Evaluation of Two Hydrograph Separation Methods of Potential Use in Regional Water Quality Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Huff, D.D.

    1999-01-01

    Streamflow data are more useful for evaluating hydrologic model results and studying water quality once baseflow and storm runoff have been separated. However, it is important to select an appropriate hydrograph separation method. They examined tow methods and evaluated their conceptual basis, ease of application, cost of data processing, and acceptability of results. they chose the quick flow hydrograph separation method, which is in use at the Coweeta Hydrologic Laboratory, because it gives acceptable results and is easy and inexpensive to use. For regional assessment, they anticipate that the Coweeta program will be useful as an aid in developing general quantitative relationships between changes in land use and the associated changes in surface runoff yield and water quality degradation.

  16. Hydrograph simulation models of the Hillsborough and Alafia Rivers, Florida: a preliminary report

    Science.gov (United States)

    Turner, James F.

    1972-01-01

    Mathematical (digital) models that simulate flood hydrographs from rainfall records have been developed for the following gaging stations in the Hillsborough and Alafia River basins of west-central Florida: Hillsborough River near Tampa, Alafia River at Lithia, and north Prong Alafia River near Keysville. These models, which were developed from historical streamflow and and rainfall records, are based on rainfall-runoff and unit-hydrograph procedures involving an arbitrary separation of the flood hydrograph. These models assume the flood hydrograph to be composed of only two flow components, direct (storm) runoff, and base flow. Expressions describing these two flow components are derived from streamflow and rainfall records and are combined analytically to form algorithms (models), which are programmed for processing on a digital computing system. Most Hillsborough and Alafia River flood discharges can be simulated with expected relative errors less than or equal to 30 percent and flood peaks can be simulated with average relative errors less than 15 percent. Because of the inadequate rainfall network that is used in obtaining input data for the North Prong Alafia River model, simulated peaks are frequently in error by more than 40 percent, particularly for storms having highly variable areal rainfall distribution. Simulation errors are the result of rainfall sample errors and, to a lesser extent, model inadequacy. Data errors associated with the determination of mean basin precipitation are the result of the small number and poor areal distribution of rainfall stations available for use in the study. Model inadequacy, however, is attributed to the basic underlying theory, particularly the rainfall-runoff relation. These models broaden and enhance existing water-management capabilities within these basins by allowing the establishment and implementation of programs providing for continued development in these areas. Specifically, the models serve not only as a

  17. On the Relationship Between Transfer Function-derived Response Times and Hydrograph Analysis Timing Parameters: Are there Similarities?

    Science.gov (United States)

    Bansah, S.; Ali, G.; Haque, M. A.; Tang, V.

    2017-12-01

    The proportion of precipitation that becomes streamflow is a function of internal catchment characteristics - which include geology, landscape characteristics and vegetation - and influence overall storage dynamics. The timing and quantity of water discharged by a catchment are indeed embedded in event hydrographs. Event hydrograph timing parameters, such as the response lag and time of concentration, are important descriptors of how long it takes the catchment to respond to input precipitation and how long it takes the latter to filter through the catchment. However, the extent to which hydrograph timing parameters relate to average response times derived from fitting transfer functions to annual hydrographs is unknown. In this study, we used a gamma transfer function to determine catchment average response times as well as event-specific hydrograph parameters across a network of eight nested watersheds ranging from 0.19 km2 to 74.6 km2 prairie catchments located in south central Manitoba (Canada). Various statistical analyses were then performed to correlate average response times - estimated using the parameters of the fitted gamma transfer function - to event-specific hydrograph parameters. Preliminary results show significant interannual variations in response times and hydrograph timing parameters: the former were in the order of a few hours to days, while the latter ranged from a few days to weeks. Some statistically significant relationships were detected between response times and event-specific hydrograph parameters. Future analyses will involve the comparison of statistical distributions of event-specific hydrograph parameters with that of runoff response times and baseflow transit times in order to quantity catchment storage dynamics across a range of temporal scales.

  18. Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

    Science.gov (United States)

    Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

    2012-01-01

    assimilation at any adjustment scale produces streamflow predictions with a spatial correlation structure more consistent with that of streamflow observations. We also describe diagnosing the complexity of the assimilation problem using the spatial correlation information associated with the streamflow process, and discuss the effect of timing errors in a simulated hydrograph on the performance of the data assimilation procedure.

  19. A new time-space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale

    Science.gov (United States)

    Takahiro Sayama; Jeffrey J. McDonnell

    2009-01-01

    Hydrograph source components and stream water residence time are fundamental behavioral descriptors of watersheds but, as yet, are poorly represented in most rainfall-runoff models. We present a new time-space accounting scheme (T-SAS) to simulate the pre-event and event water fractions, mean residence time, and spatial source of streamflow at the watershed scale. We...

  20. Streamflow ratings

    Science.gov (United States)

    Holmes, Robert R.; Singh, Vijay P.

    2016-01-01

    Autonomous direct determination of a continuous time series of streamflow is not economically feasible at present (2014). As such, surrogates are used to derive a continuous time series of streamflow. The derivation process entails developing a streamflow rating, which can range from a simple, single-valued relation between stage and streamflow to a fully dynamic one-dimensional model based on hydraulics of the flow.

  1. Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

    Science.gov (United States)

    Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

    2016-12-01

    Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

  2. Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

    Science.gov (United States)

    Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.

    2015-08-24

    Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

  3. Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques

    Science.gov (United States)

    Jain, Ashu; Srinivasulu, Sanaga

    2006-02-01

    This paper presents the findings of a study aimed at decomposing a flow hydrograph into different segments based on physical concepts in a catchment, and modelling different segments using different technique viz. conceptual and artificial neural networks (ANNs). An integrated modelling framework is proposed capable of modelling infiltration, base flow, evapotranspiration, soil moisture accounting, and certain segments of the decomposed flow hydrograph using conceptual techniques and the complex, non-linear, and dynamic rainfall-runoff process using ANN technique. Specifically, five different multi-layer perceptron (MLP) and two self-organizing map (SOM) models have been developed. The rainfall and streamflow data derived from the Kentucky River catchment were employed to test the proposed methodology and develop all the models. The performance of all the models was evaluated using seven different standard statistical measures. The results obtained in this study indicate that (a) the rainfall-runoff relationship in a large catchment consists of at least three or four different mappings corresponding to different dynamics of the underlying physical processes, (b) an integrated approach that models the different segments of the decomposed flow hydrograph using different techniques is better than a single ANN in modelling the complex, dynamic, non-linear, and fragmented rainfall runoff process, (c) a simple model based on the concept of flow recession is better than an ANN to model the falling limb of a flow hydrograph, and (d) decomposing a flow hydrograph into the different segments corresponding to the different dynamics based on the physical concepts is better than using the soft decomposition employed using SOM.

  4. Estimation of unaltered daily mean streamflow at ungaged streams of New York, excluding Long Island, water years 1961-2010

    Science.gov (United States)

    Gazoorian, Christopher L.

    2015-01-01

    The lakes, rivers, and streams of New York State provide an essential water resource for the State. The information provided by time series hydrologic data is essential to understanding ways to promote healthy instream ecology and to strengthen the scientific basis for sound water management decision making in New York. The U.S. Geological Survey, in cooperation with The Nature Conservancy and the New York State Energy Research and Development Authority, has developed the New York Streamflow Estimation Tool to estimate a daily mean hydrograph for the period from October 1, 1960, to September 30, 2010, at ungaged locations across the State. The New York Streamflow Estimation Tool produces a complete estimated daily mean time series from which daily flow statistics can be estimated. In addition, the New York Streamflow Estimation Tool provides a means for quantitative flow assessments at ungaged locations that can be used to address the objectives of the Clean Water Act—to restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.

  5. Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA

    Science.gov (United States)

    Rhea, Lee; Jarnagin, Taylor; Hogan, Dianna; Loperfido, J. V.; Shuster, William

    2015-01-01

    Understanding the efficacy of revised watershed management methods is important to mitigating the impacts of urbanization on streamflow. We evaluated the influence of land use change, primarily as urbanization, and stormwater control measures on the relationship between precipitation and stream discharge over an 8-year period for five catchments near Clarksburg, Montgomery County, Maryland, USA. A unit-hydrograph model based on a temporal transfer function was employed to account for and standardize temporal variation in rainfall pattern, and properly apportion rainfall to streamflow at different time lags. From these lagged relationships, we quantified a correction to the precipitation time series to achieve a hydrograph that showed good agreement between precipitation and discharge records. Positive corrections appeared to include precipitation events that were of limited areal extent and therefore not captured by our rain gages. Negative corrections were analysed for potential causal relationships. We used mixed-model statistical techniques to isolate different sources of variance as drivers that mediate the rainfall–runoff dynamic before and after management. Seasonal periodicity mediated rainfall–runoff relationships, and land uses (i.e. agriculture, natural lands, wetlands and stormwater control measures) were statistically significant predictors of precipitation apportionment to stream discharge. Our approach is one way to evaluate actual effectiveness of management efforts in the face of complicating circumstances and could be paired with cost data to understand economic efficiency or life cycle aspects of watershed management. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  6. Characteristics of peak streamflows and extent of inundation in areas of West Virginia and southwestern Virginia affected by flooding, June 2016

    Science.gov (United States)

    Austin, Samuel H.; Watson, Kara M.; Lotspeich, R. Russell; Cauller, Stephen J.; White , Jeremy S.; Wicklein, Shaun M.

    2017-11-17

    Heavy rainfall occurred across central and southern West Virginia in June 2016 as a result of repeated rounds of torrential thunderstorms. The storms caused major flooding and flash flooding in central and southern West Virginia with Kanawha, Fayette, Nicholas, and Greenbrier Counties among the hardest hit. Over the duration of the storms, from 8 to 9.37 inches of rain was reported in areas in Greenbrier County. Peak streamflows were the highest on record at 7 locations, and streamflows at 18 locations ranked in the top five for the period of record at U.S. Geological Survey streamflow-gaging stations used in this study. Following the storms, U.S. Geological Survey hydrographers identified and documented 422 high-water marks in West Virginia, noting location and height of the water above land surface. Many of these high-water marks were used to create flood-inundation maps for selected communities of West Virginia that experienced flooding in June 2016. Digital datasets of the inundation areas, mapping boundaries, and water depth rasters are available online.

  7. Simulation of streamflow in the McTier Creek watershed, South Carolina

    Science.gov (United States)

    Feaster, Toby D.; Golden, Heather E.; Odom, Kenneth R.; Lowery, Mark A.; Conrads, Paul; Bradley, Paul M.

    2010-01-01

    of model-fit efficiency index, Pearson's correlation coefficient, the root mean square error, the bias, and the mean absolute error. In addition, a number of graphical tools were used to assess how well the models captured the characteristics of the observed data at the Monetta and New Holland streamflow-gaging stations. The graphical tools included temporal plots of simulated and observed daily mean flows, flow-duration curves, single-mass curves, and various residual plots. The results indicated that TOPMODEL and GBMM generally produced simulations that reasonably capture the quantity, variability, and timing of the observed streamflow. For the periods modeled, the total volume of simulated daily mean flows as compared to the total volume of the observed daily mean flow from TOPMODEL was within 1 to 5 percent, and the total volume from GBMM was within 1 to 10 percent. A noticeable characteristic of the simulated hydrographs from both models is the complexity of balancing groundwater recession and flow at the streamgage when flows peak and recede rapidly. However, GBMM results indicate that groundwater recession, which affects the receding limb of the hydrograph, was more difficult to estimate with the spatially explicit curve number approach. Although the purpose of this report is not to directly compare both models, given the characteristics of the McTier Creek watershed and the fact that GBMM uses the spatially explicit curve number approach as compared to the variable-source-area concept in TOPMODEL, GBMM was able to capture the flow characteristics reasonably well.

  8. A comparative analysis of 9 multi-model averaging approaches in hydrological continuous streamflow simulation

    Science.gov (United States)

    Arsenault, Richard; Gatien, Philippe; Renaud, Benoit; Brissette, François; Martel, Jean-Luc

    2015-10-01

    This study aims to test whether a weighted combination of several hydrological models can simulate flows more accurately than the models taken individually. In addition, the project attempts to identify the most efficient model averaging method and the optimal number of models to include in the weighting scheme. In order to address the first objective, streamflow was simulated using four lumped hydrological models (HSAMI, HMETS, MOHYSE and GR4J-6), each of which were calibrated with three different objective functions on 429 watersheds. The resulting 12 hydrographs (4 models × 3 metrics) were weighted and combined with the help of 9 averaging methods which are the simple arithmetic mean (SAM), Akaike information criterion (AICA), Bates-Granger (BGA), Bayes information criterion (BICA), Bayesian model averaging (BMA), Granger-Ramanathan average variant A, B and C (GRA, GRB and GRC) and the average by SCE-UA optimization (SCA). The same weights were then applied to the hydrographs in validation mode, and the Nash-Sutcliffe Efficiency metric was measured between the averaged and observed hydrographs. Statistical analyses were performed to compare the accuracy of weighted methods to that of individual models. A Kruskal-Wallis test and a multi-objective optimization algorithm were then used to identify the most efficient weighted method and the optimal number of models to integrate. Results suggest that the GRA, GRB, GRC and SCA weighted methods perform better than the individual members. Model averaging from these four methods were superior to the best of the individual members in 76% of the cases. Optimal combinations on all watersheds included at least one of each of the four hydrological models. None of the optimal combinations included all members of the ensemble of 12 hydrographs. The Granger-Ramanathan average variant C (GRC) is recommended as the best compromise between accuracy, speed of execution, and simplicity.

  9. Streamflow depletion by wells--Understanding and managing the effects of groundwater pumping on streamflow

    Science.gov (United States)

    Barlow, Paul M.; Leake, Stanley A.

    2012-11-02

    Groundwater is an important source of water for many human needs, including public supply, agriculture, and industry. With the development of any natural resource, however, adverse consequences may be associated with its use. One of the primary concerns related to the development of groundwater resources is the effect of groundwater pumping on streamflow. Groundwater and surface-water systems are connected, and groundwater discharge is often a substantial component of the total flow of a stream. Groundwater pumping reduces the amount of groundwater that flows to streams and, in some cases, can draw streamflow into the underlying groundwater system. Streamflow reductions (or depletions) caused by pumping have become an important water-resource management issue because of the negative impacts that reduced flows can have on aquatic ecosystems, the availability of surface water, and the quality and aesthetic value of streams and rivers. Scientific research over the past seven decades has made important contributions to the basic understanding of the processes and factors that affect streamflow depletion by wells. Moreover, advances in methods for simulating groundwater systems with computer models provide powerful tools for estimating the rates, locations, and timing of streamflow depletion in response to groundwater pumping and for evaluating alternative approaches for managing streamflow depletion. The primary objective of this report is to summarize these scientific insights and to describe the various field methods and modeling approaches that can be used to understand and manage streamflow depletion. A secondary objective is to highlight several misconceptions concerning streamflow depletion and to explain why these misconceptions are incorrect.

  10. Uncertainties in Forecasting Streamflow using Entropy Theory

    Science.gov (United States)

    Cui, H.; Singh, V. P.

    2017-12-01

    Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

  11. Hydrological and geophysical investigation of streamflow losses and restoration strategies in an abandoned mine lands setting

    Science.gov (United States)

    Cravotta, Charles A.; Sherrod, Laura; Galeone, Daniel G.; Lehman, Wayne G.; Ackman, Terry E.; Kramer, Alexa

    2017-01-01

    Longitudinal discharge and water-quality campaigns (seepage runs) were combined with surface-geophysical surveys, hyporheic-temperature profiling, and watershed-scale hydrological monitoring to evaluate the locations, magnitude, and impact of streamwater losses from the West Creek subbasin of the West West Branch Schuylkill River into the underground Oak Hill Mine complex that extends beneath the watershed divide. Abandoned mine drainage (AMD), containing iron and other contaminants, from the Oak Hill Boreholes to the West Branch Schuylkill River was sustained during low-flow conditions and correlated to streamflow lost through the West Creek streambed. During high-flow conditions, streamflow was transmitted throughout West Creek; however, during low-flow conditions, all streamflow from the perennial headwaters was lost within the 300-to-600-m "upper reach" where an 1889 mine map indicated steeply dipping coalbeds underlie the channel. During low-flow conditions, the channel within the "intermediate reach" 700-to-1650-m downstream gained groundwater seepage with higher pH and specific conductance than upstream; however, all streamflow 1650-to-2050-m downstream was lost to underlying mines. Electrical resistivity and electromagnetic conductivity surveys indicated conductive zones beneath the upper reach, where flow loss occurred, and through the intermediate reach, where gains and losses occurred. Temperature probes at 0.06-to-0.10-m depth within the hyporheic zone of the intermediate reach indicated potential downward fluxes as high as 2.1x10-5 m/s. Cumulative streamflow lost from West Creek during seepage runs averaged 53.4 L/s, which equates to 19.3 percent of the daily average discharge of AMD from the Oak Hill Boreholes and a downward flux of 1.70x10-5 m/s across the 2.1-km-by-1.5-m West Creek stream-channel area.

  12. Comparison of historical streamflows to 2013 Streamflows in the Williamson, Sprague, and Wood Rivers, Upper Klamath Lake Basin, Oregon

    Science.gov (United States)

    Hess, Glen W.; Stonewall, Adam J.

    2014-01-01

    In 2013, the Upper Klamath Lake Basin, Oregon, experienced a dry spring, resulting in an executive order declaring a state of drought emergency in Klamath County. The 2013 drought limited the water supply and led to a near-total cessation of surface-water diversions for irrigation above Upper Klamath Lake once regulation was implemented. These conditions presented a unique opportunity to understand the effects of water right regulation on streamflows. The effects of regulation of diversions were evaluated by comparing measured 2013 streamflow with data from hydrologically similar years. Years with spring streamflow similar to that in 2013 measured at the Sprague River gage at Chiloquin from water years 1973 to 2012 were used to define a Composite Index Year (CIY; with diversions) for comparison to measured 2013 streamflows (no diversions). The best-fit 6 years (1977, 1981, 1990, 1991, 1994, and 2001) were used to determine the CIY. Two streams account for most of the streamflow into Upper Klamath Lake: the Williamson and Wood Rivers. Most streamflow into the lake is from the Williamson River Basin, which includes the Sprague River. Because most of the diversion regulation affecting the streamflow of the Williamson River occurred in the Sprague River Basin, and because of uncertainties about historical flows in a major diversion above the Williamson River gage, streamflow data from the Sprague River were used to estimate the change in streamflow from regulation of diversions for the Williamson River Basin. Changes in streamflow outside of the Sprague River Basin were likely minor relative to total streamflow. The effect of diversion regulation was evaluated using the “Baseflow Method,” which compared 2013 baseflow to baseflow of the CIY. The Baseflow Method reduces the potential effects of summer precipitation events on the calculations. A similar method using streamflow produced similar results, however, despite at least one summer precipitation event. The

  13. Geological controls on isotopic signatures of streamflow: results from a nested catchment experiment in Luxembourg (Europe)

    Science.gov (United States)

    Pfister, Laurent; McDonnell, Jeffrey J.; Hissler, Christophe; Martinez-Carreras, Nuria; Gourdol, Laurent; Klaus, Julian; François Iffly, Jean; Barnich, François; Stewart, Mike K.

    2014-05-01

    permeable bedrock, isotopic signatures of streamflow remained stable throughout the entire flow duration curve consistent with a large storage and mixing potential. On less permeable bedrock substrate, we have observed that isotopic signatures in streamflow were much more variable, due to reduced storage volume and comparatively smaller mixing potential. Other metrics such as catchment size and flowpath length exerted a smaller secondary control on isotopic signatures of streamflow in the Alzette River sub-basins. Tague, C., Grant, G.E., 2004. A geological framework for interpreting the low-flow regimes of Cascade streams, Willamette River Basin, Oregon. Water Resources Research, 40(4), doi:10.1029/2003WR002629 Sayama, T., McDonnell, J.J., Dhakal, A., Sullivan, K., 2011. How much water can a watershed store ? Hydrological Processes 25, 3899-3908. Klaus, J., McDonnell, J.J., 2013. Hydrograph separation using stable isotopes: Review and evaluation. Journal of Hydrology 505, 47-64.

  14. Geochemical baseline studies and relations between water quality and streamflow in the upper Blackfoot Watershed, Montana: data for July 1997-December 1998

    Science.gov (United States)

    Nagorski, Sonia A.; Moore, Johnnie N.; Smith, David B.

    2001-01-01

    We used ultraclean sampling techniques to study the solute (operationally defined as water geochemistry at five sites along the Upper Blackfoot River and four sites along the Landers Fork, some in more detail and more regularly than others. We collected samples also from Hogum Creek, a tributary to the Blackfoot, from Copper Creek, a tributary to the Landers Fork, and from ground water seeps contributing to the flow along the Landers Fork. To better define the physical dynamics of the hydrologic system and to determine geochemical loads, we measured streamflow at all the sites where we took samples for water quality analysis. The Upper Blackfoot River, which drains historic mines ca. 20 Km upstream of the study area, had higher trace metal concentrations than did the Landers Fork, which drains the pristine Scapegoat Wilderness area. In both rivers, many of the major elements were inversely related to streamflow, and at some sites, several show a hysteresis effect in which the concentrations were lower on the rising limb of the hydrograph than on the falling limb. However, many of the trace elements followed far more irregular trends, especially in the Blackfoot River. Elements such as As, Cu, Fe, Mn, S, and Zn exhibited complex and variable temporal patterns, which included almost no response to streamflow differences, increased concentrations following a summer storm and at the start of snowmelt in the spring, and/or increased concentrations throughout the course of spring runoff. In summary, complex interactions between the timing and magnitude of streamflow with physical and chemical processes within the watershed appeared to greatly influence the geochemistry at the sites, and streamflow values alone were not good predictors of solute concentrations in the rivers.

  15. Adjusted Streamflow and Storage 1928-1989 : with Listings of Historical Streamflow, Summation of Storage Change and Adjusted Streamflow : Columbia River and Coastal Basins.

    Energy Technology Data Exchange (ETDEWEB)

    A.G. Crook Company

    1993-04-01

    The development of irrigation projects since the 1830's and the construction of major dams and reservoirs since the early 1900's have altered substantially the natural streamflow regimen of the Columbia River and its tributaries. As development expanded a multipurpose approach to streamflow regulation evolved to provide flood control, irrigation, hydropower generation, navigation, recreation, water quality enhancement, fish and wildlife, and instream flow maintenance. The responsible agencies use computer programs to determine the effects of various alternative system regulations. This report describes the development of the streamflow data that these computer programs use.

  16. Modeling multisite streamflow dependence with maximum entropy copula

    Science.gov (United States)

    Hao, Z.; Singh, V. P.

    2013-10-01

    Synthetic streamflows at different sites in a river basin are needed for planning, operation, and management of water resources projects. Modeling the temporal and spatial dependence structure of monthly streamflow at different sites is generally required. In this study, the maximum entropy copula method is proposed for multisite monthly streamflow simulation, in which the temporal and spatial dependence structure is imposed as constraints to derive the maximum entropy copula. The monthly streamflows at different sites are then generated by sampling from the conditional distribution. A case study for the generation of monthly streamflow at three sites in the Colorado River basin illustrates the application of the proposed method. Simulated streamflow from the maximum entropy copula is in satisfactory agreement with observed streamflow.

  17. Streamflow alteration at selected sites in Kansas

    Science.gov (United States)

    Juracek, Kyle E.; Eng, Ken

    2017-06-26

    An understanding of streamflow alteration in response to various disturbances is necessary for the effective management of stream habitat for a variety of species in Kansas. Streamflow alteration can have negative ecological effects. Using a modeling approach, streamflow alteration was assessed for 129 selected U.S. Geological Survey streamgages in the State for which requisite streamflow and basin-characteristic information was available. The assessment involved a comparison of the observed condition from 1980 to 2015 with the predicted expected (least-disturbed) condition for 29 streamflow metrics. The metrics represent various characteristics of streamflow including average flow (annual, monthly) and low and high flow (frequency, duration, magnitude).Streamflow alteration in Kansas was indicated locally, regionally, and statewide. Given the absence of a pronounced trend in annual precipitation in Kansas, a precipitation-related explanation for streamflow alteration was not supported. Thus, the likely explanation for streamflow alteration was human activity. Locally, a flashier flow regime (typified by shorter lag times and more frequent and higher peak discharges) was indicated for three streamgages with urbanized basins that had higher percentages of impervious surfaces than other basins in the State. The combination of localized reservoir effects and regional groundwater pumping from the High Plains aquifer likely was responsible, in part, for diminished conditions indicated for multiple streamflow metrics in western and central Kansas. Statewide, the implementation of agricultural land-management practices to reduce runoff may have been responsible, in part, for a diminished duration and magnitude of high flows. In central and eastern Kansas, implemented agricultural land-management practices may have been partly responsible for an inflated magnitude of low flows at several sites.

  18. Skilful seasonal forecasts of streamflow over Europe?

    Science.gov (United States)

    Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian

    2018-04-01

    This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate

  19. SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

    Science.gov (United States)

    Kiang, Julie E.; Flynn, Kate; Zhai, Tong; Hummel, Paul; Granato, Gregory

    2018-03-07

    This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

  20. Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in Montana StreamStats

    Science.gov (United States)

    McCarthy, Peter M.

    2016-04-05

    Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March–June, July–October, and November–February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.

  1. Um estudo de downscaling dinâmico de precipitação intrasazonal acoplado a modelo chuva-vazão na bacia hidrográfica alto-médio São Francisco A study of intraseasonal precipitation dynamic downscaling coupled to rain-streamflow model at the alto-médio São Francisco hydrographic basin

    Directory of Open Access Journals (Sweden)

    José Pedro Rebés Lima

    2009-09-01

    Full Text Available Este estudo mostra a aplicação de modelagem hidroclimática dinâmica (hydroclimate downscaling de precipitação acoplada a um modelo hidrológico chuva-vazão, para as Bacias hidrográficas denominadas Cachoeira Manteiga e Porto da Extrema, localizadas na Bacia do Alto-Médio São Francisco no Estado de Minas Gerais. Ênfase foi dada à simulação na escala intrasazonal (mensal. Os resultados sugerem que a simulação de precipitação pode ser usada como variável de entrada em modelos de estimativa de vazão para períodos na escala de um mês, dando subsídio a um melhor aproveitamento dos recursos hídricos na bacia hidrográfica estudada. Estes ainda sugerem que a simulação de precipitação, quando corrigida pela técnica Probability Density Function (PDFs, é mais eficiente na estimativa de precipitação simulada quando comparada com a precipitação observada na bacia, resultando em uma melhor simulação de vazão afluente na bacia.This study shows the use of rainfall dynamic hydroclimate downscaling coupled to the rain-streamflow hydrological model for the hydrographic basins named Cachoeira Manteiga and Porto da Extrema, localized at Alto-Médio São Francisco Basin in Minas Gerais State. The emphasis was to simulate the intraseasonal scale (monthly. The results suggest that the rainfall simulation can be used as input data to streamflow estimation models for periods of monthly scale, allowing a more rational usage of the surface water resources in the hydrographic basin studied. It is also suggested that the rainfall data simulation, corrected by the Probability Density Function (PDF technique, is more efficient to estimate rainfall comparing to observed rainfall in the basin thus resulting in a better simulation of the basin flow outlet.

  2. Spatial and Temporal Streamflow Trends in Northern Taiwan

    Directory of Open Access Journals (Sweden)

    Chen-Feng Yeh

    2015-02-01

    Full Text Available Streamflow is an important factor in the study of water resource management, floods, and droughts. Dramatic climate change has created extreme rainfall distributions, making the study of streamflow trends and variability even more crucial. In this study, the long-term streamflow data and trends recorded at gauging stations in Northern Taiwan are analyzed using the Mann-Kendall test. The data used for trend analysis are the average annual streamflow, the average seasonal streamflow, and the high and low flows. The slope trend is calculated using the Theil-Sen estimator. Finally, change point analysis is conducted using the Mann-Whitney-Pettit test and the cumulative deviation test to gain further information about the change points and to understand the changes in streamflow before and after the change points. The average annual streamflow of the 12 gauging stations in the study area is analyzed using the Mann-Kendall test. The results show that of the 12 gauging stations, only the Ximen Bridge Station in the Lanyang River basin show a significant downward streamflow trend. Results of the monthly and seasonal average streamflow analysis show that in the spring, 72.2% of the gauging stations showed upward streamflow trends, most of which were located in the Tamsui River and the Touqian River basins. The high and low flow data analysis shows that the Ximen Bridge Station was the only gauging station to feature a significant downward streamflow trend for both high and low flows. This distribution pattern provides valuable information for regional hydrological studies and water management.

  3. 75 FR 20809 - Hydrographic Services Review Panel

    Science.gov (United States)

    2010-04-21

    ... hydrographic data and hydrographic services, marine transportation, port administration, vessel pilotage....'' NOAA encourages individuals with expertise in navigation data, products and services; coastal.... NOS collects and compiles hydrographic, tidal and current, geodetic, and a variety of other data in...

  4. Low Streamflow Forcasting using Minimum Relative Entropy

    Science.gov (United States)

    Cui, H.; Singh, V. P.

    2013-12-01

    Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.

  5. The Hydrograph Analyst, an Arcview GIS Extension That Integrates Point, Spatial, and Temporal Data Provides A Graphical User Interface for Hydrograph Analysis

    International Nuclear Information System (INIS)

    Jones, M.L.; O'Brien, G.M.; Jones, M.L.

    2000-01-01

    The Hydrograph Analyst (HA) is an ArcView GIS 3.2 extension developed by the authors to analyze hydrographs from a network of ground-water wells and springs in a regional ground-water flow model. ArcView GIS integrates geographic, hydrologic, and descriptive information and provides the base functionality needed for hydrograph analysis. The HA extends ArcView's base functionality by automating data integration procedures and by adding capabilities to visualize and analyze hydrologic data. Data integration procedures were automated by adding functionality to the View document's Document Graphical User Interface (DocGUI). A menu allows the user to query a relational database and select sites which are displayed as a point theme in a View document. An ''Identify One to Many'' tool is provided within the View DocGUI to retrieve all hydrologic information for a selected site and display it in a simple and concise tabular format. For example, the display could contain various records from many tables storing data for one site. Another HA menu allows the user to generate a hydrograph for sites selected from the point theme. Hydrographs generated by the HA are added as hydrograph documents and accessed by the user with the Hydrograph DocGUI, which contains tools and buttons for hydrograph analysis. The Hydrograph DocGUI has a ''Select By Polygon'' tool used for isolating particular points on the hydrograph inside a user-drawn polygon or the user could isolate the same points by constructing a logical expression with the ArcView GIS ''Query Builder'' dialog that is also accessible in the Hydrograph DocGUI. Other buttons can be selected to alter the query applied to the active hydrograph. The selected points on the active hydrograph can be attributed (or flagged) individually or as a group using the ''Flag'' tool found on the Hydrograph DocGUI. The ''Flag'' tool activates a dialog box that prompts the user to select an attribute and ''methods'' or ''conditions'' that qualify

  6. Developing Design Storm Hydrographs for Small Tropical ...

    African Journals Online (AJOL)

    Hydrographs are vital tools in the design and construction of water-control structures in urban and rural systems. The purpose of this study was to explore the development of design storm hydrographs for the small tropical catchment with limited data. In this study, Clark's Unit Hydrograph method was used to develop ...

  7. Streamflow disaggregation: a nonlinear deterministic approach

    Directory of Open Access Journals (Sweden)

    B. Sivakumar

    2004-01-01

    Full Text Available This study introduces a nonlinear deterministic approach for streamflow disaggregation. According to this approach, the streamflow transformation process from one scale to another is treated as a nonlinear deterministic process, rather than a stochastic process as generally assumed. The approach follows two important steps: (1 reconstruction of the scalar (streamflow series in a multi-dimensional phase-space for representing the transformation dynamics; and (2 use of a local approximation (nearest neighbor method for disaggregation. The approach is employed for streamflow disaggregation in the Mississippi River basin, USA. Data of successively doubled resolutions between daily and 16 days (i.e. daily, 2-day, 4-day, 8-day, and 16-day are studied, and disaggregations are attempted only between successive resolutions (i.e. 2-day to daily, 4-day to 2-day, 8-day to 4-day, and 16-day to 8-day. Comparisons between the disaggregated values and the actual values reveal excellent agreements for all the cases studied, indicating the suitability of the approach for streamflow disaggregation. A further insight into the results reveals that the best results are, in general, achieved for low embedding dimensions (2 or 3 and small number of neighbors (less than 50, suggesting possible presence of nonlinear determinism in the underlying transformation process. A decrease in accuracy with increasing disaggregation scale is also observed, a possible implication of the existence of a scaling regime in streamflow.

  8. Spatial Correlation Of Streamflows: An Analytical Approach

    Science.gov (United States)

    Betterle, A.; Schirmer, M.; Botter, G.

    2016-12-01

    The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the

  9. Has streamflow changed in the Nordic countries?

    Energy Technology Data Exchange (ETDEWEB)

    Hisdal, Hege; Holmqvist, Erik; Jonsdottir, Jona Finndis; Jonsson, Pall; Kuusisto, Esko; Lindstroem, Goeran; Roald, Lars A.

    2010-01-15

    Climate change studies traditionally include elaboration of possible scenarios for the future and attempts to detect a climate change signal in historical data. This study focuses on the latter. A pan-Nordic dataset of more than 160 streamflow records was analysed to detect spatial and temporal changes in streamflow. The Mann-Kendall trend test was applied to study changes in annual and seasonal streamflow as well as floods and droughts for three periods: 1961-2000, 1941-2002 and 1920-2002. The period analysed and the selection of stations influenced the regional patterns found, but the overall picture was that trends towards increased streamflow were dominating for annual values and the winter and spring seasons. Trends in summer flow highly depended on the period analysed whereas no trend was found for the autumn season. A signal towards earlier snowmelt floods was clear and a tendency towards more severe summer droughts was found in southern Norway. A qualitative comparison of the findings to available streamflow scenarios for the region showed that the strongest trends found are coherent with changes expected in the scenario period, for example increased winter discharge and earlier snowmelt floods. However, there are also expected changes that are not reflected in the trends, such as the expected increase in autumn discharge in Norway. It can be concluded that the observed temperature increase has clearly affected the streamflow in the Nordic countries. These changes correspond well with the estimated consequences of a projected temperature increase. The effect of the observed and projected precipitation increase on streamflow is less clear.(Author)

  10. Climate and Land Use Changes on Streamflow and Subsurface Recharge in the Fluvià Basin, Spain

    Directory of Open Access Journals (Sweden)

    Lucila Candela

    2016-05-01

    Full Text Available Climate change impact on water resources (streamflow and deep natural recharge based on the downscaled outputs from the ECHAM5 general circulation model (GCM has been investigated in the Mediterranean basin (Fluvià, Spain for the A2, B1 greenhouse scenarios and 2000–2024/2025–2050 time slices. The HEC-HMS 3.4 rainfall-runoff numerical model was the basic tool used to generate streamflow for the historical period, and deep natural recharge was calculated from Visual-BALAN 2.0, a water-soil-plant distributed model. The hydrologic and recharge models were employed to generate future climate change hydrographs and the deep recharge amount. Furthermore, the selected future climate scenarios, subject to possible changes in the land use/land cover forecast, were integrated into the models, and water resource impacts were assessed. The multiple combinations of climate model, time slices, greenhouse scenarios, land use/land cover scenarios and hydrological estimation methods resulted in six scenarios. The obtained results estimate an increase in temperature (1.5 °C, a decline in precipitation (17% and a maximum decrease of 49.5% and 16.8% in runoff and groundwater recharge, respectively, for 2050 (A2 compared to the historical values. Planned land cover scenarios, implying small changes of agricultural and forested land, show no major contribution to future water resource changes. According to the results, the most sensitive parameters conditioning future water resources are changes in temperature and precipitation.

  11. Disentangling the response of streamflow to forest management and climate

    Science.gov (United States)

    Dymond, S.; Miniat, C.; Bladon, K. D.; Keppeler, E.; Caldwell, P. V.

    2016-12-01

    Paired watershed studies have showcased the relationships between forests, management, and streamflow. However, classical analyses of paired-watershed studies have done little to disentangle the effects of management from overarching climatic signals, potentially masking the interaction between management and climate. Such approaches may confound our understanding of how forest management impacts streamflow. Here we use a 50-year record of streamflow and climate data from the Caspar Creek Experimental Watersheds (CCEW), California, USA to separate the effects of forest management and climate on streamflow. CCEW has two treatment watersheds that have been harvested in the past 50 years. We used a nonlinear mixed model to combine the pre-treatment relationship between streamflow and climate and the post-treatment relationship via an interaction between climate and management into one equation. Our results show that precipitation and potential evapotranspiration alone can account for >95% of the variability in pre-treatment streamflow. Including management scenarios into the model explained most of the variability in streamflow (R2 > 0.98). While forest harvesting altered streamflow in both of our modeled watersheds, removing 66% of the vegetation via selection logging using a tractor yarding system over the entire watershed had a more substantial impact on streamflow than clearcutting small portions of a watershed using cable-yarding. These results suggest that forest harvesting may result in differing impacts on streamflow and highlights the need to incorporate climate into streamflow analyses of paired-watershed studies.

  12. Estimating ice-affected streamflow by extended Kalman filtering

    Science.gov (United States)

    Holtschlag, D.J.; Grewal, M.S.

    1998-01-01

    An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.

  13. Mississippi River streamflow measurement techniques at St. Louis, Missouri

    Science.gov (United States)

    Wastson, Chester C.; Holmes, Robert R.; Biedenham, David S.

    2013-01-01

    Streamflow measurement techniques of the Mississippi River at St. Louis have changed through time (1866–present). In addition to different methods used for discrete streamflow measurements, the density and range of discrete measurements used to define the rating curve (stage versus streamflow) have also changed. Several authors have utilized published water surface elevation (stage) and streamflow data to assess changes in the rating curve, which may be attributed to be caused by flood control and/or navigation structures. The purpose of this paper is to provide a thorough review of the available flow measurement data and techniques and to assess how a strict awareness of the limitations of the data may affect previous analyses. It is concluded that the pre-1930s discrete streamflow measurement data are not of sufficient accuracy to be compared with modern streamflow values in establishing long-term trends of river behavior.

  14. Temporal variations in near surface soil moisture at two contrasting sites in the Wye catchment and their control on storm streamflow generation

    Science.gov (United States)

    Roberts, G.; Crane, S. B.

    Near surface soil moisture measurements were recorded at hourly intervals at two contrasting sites within the Cyff sub-catchment using a prototype capacitance probe system. In a mire area within a valley bottom, over the twelve month recording period, very little change in moisture content occurred. At the other site, a well drained area on a steeply sloping hillside, major variations occurred with significant soil moisture deficits being generated during a particularly dry summer. Soil moisture on the slope responded rapidly to rainfall inputs during wet periods, with little response during particularly dry periods. A number of rainfall events was analysed to determine whether changes in soil moisture could be used to characterise storm hydrographs for the Cyff and the Gwy, two sub-catchments being composed of differing percentages of mire area and steep slopes. It was found that percentage runoff for the Cyff was correlated with antecedent soil moisture on the slope, though the agreements for peak flow and lag time were poorer. For the Gwy, poor agreements were obtained for all three hydrograph characteristics. A simple formulation, based on storm rainfall and antecedent soil moisture deficits in the slope and mire areas, gave good agreement with storm streamflow volumes.

  15. Temporal variations in near surface soil moisture at two contrasting sites in the Wye catchment and their control on storm streamflow generation

    Directory of Open Access Journals (Sweden)

    G. Roberts

    1997-01-01

    Full Text Available Near surface soil moisture measurements were recorded at hourly intervals at two contrasting sites within the Cyff sub-catchment using a prototype capacitance probe system. In a mire area within a valley bottom, over the twelve month recording period, very little change in moisture content occurred. At the other site, a well drained area on a steeply sloping hillside, major variations occurred with significant soil moisture deficits being generated during a particularly dry summer. Soil moisture on the slope responded rapidly to rainfall inputs during wet periods, with little response during particularly dry periods. A number of rainfall events was analysed to determine whether changes in soil moisture could be used to characterise storm hydrographs for the Cyff and the Gwy, two sub-catchments being composed of differing percentages of mire area and steep slopes. It was found that percentage runoff for the Cyff was correlated with antecedent soil moisture on the slope, though the agreements for peak flow and lag time were poorer. For the Gwy, poor agreements were obtained for all three hydrograph characteristics. A simple formulation, based on storm rainfall and antecedent soil moisture deficits in the slope and mire areas, gave good agreement with storm streamflow volumes.

  16. Mathematical modeling of synthetic unit hydrograph case study: Citarum watershed

    Science.gov (United States)

    Islahuddin, Muhammad; Sukrainingtyas, Adiska L. A.; Kusuma, M. Syahril B.; Soewono, Edy

    2015-09-01

    Deriving unit hydrograph is very important in analyzing watershed's hydrologic response of a rainfall event. In most cases, hourly measures of stream flow data needed in deriving unit hydrograph are not always available. Hence, one needs to develop methods for deriving unit hydrograph for ungagged watershed. Methods that have evolved are based on theoretical or empirical formulas relating hydrograph peak discharge and timing to watershed characteristics. These are usually referred to Synthetic Unit Hydrograph. In this paper, a gamma probability density function and its variant are used as mathematical approximations of a unit hydrograph for Citarum Watershed. The model is adjusted with real field condition by translation and scaling. Optimal parameters are determined by using Particle Swarm Optimization method with weighted objective function. With these models, a synthetic unit hydrograph can be developed and hydrologic parameters can be well predicted.

  17. RUNOFF HYDROGRAPHS USING SNYDER AND SCS SYNTHETIC UNIT HYDROGRAPH METHODS: A CASE STUDY OF SELECTED RIVERS IN SOUTH WEST NIGERIA

    Directory of Open Access Journals (Sweden)

    Wahab Adebayo Salami

    2017-01-01

    Full Text Available This paper presents the development of runoff hydrographs for selected rivers in Ogun-Osun river catchment, south west, Nigeria using Snyder and Soil Conservation Service (SCS methods of synthetic unit hydrograph to determine the ordinates. The Soil Conservation Service (SCS curve Number method was used to estimate the excess rainfall from storm of different return periods. The peak runoff hydrographs were determined by convoluting the unit hydrographs ordinates with the excess rainfall and the value of peak flows obtained by both Snyder and SCS methods observed to vary from one river watershed to the other. The peak runoff hydrograph flows obtained based on the unit hydrograph ordinate determined with Snyder method for 20-yr, 50-yr, 100-yr, 200-yr and 500-yr, return period varied from 112.63m3/s and 13364.30m3/s, while those based on the SCS method varied from 304.43m3/s and 6466.84m3/s for the eight watersheds. However, the percentage difference shows that for values of peak flows obtained with Snyder and SCS methods varies from 13.14% to 63.30%. However, SCS method is recommended to estimate the ordinate required for the development of peak runoff hydrograph in the river watersheds because it utilized additional morphometric parameters such as watershed slope and the curve number (CN which is a function of the properties of the soil and vegetation cover of the watershed.

  18. Human influences on streamflow drought characteristics in England and Wales

    Science.gov (United States)

    Tijdeman, Erik; Hannaford, Jamie; Stahl, Kerstin

    2018-02-01

    Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata (Factors Affecting Runoff) of the UK National River Flow Archive (NRFA). A screening approach was applied on the streamflow records to identify human-influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in (1) the relationship between streamflow drought duration and the base flow index, BFI (specifically, BFIHOST, the BFI predicted from the hydrological properties of soils), (2) the correlation between streamflow and precipitation and (3) the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e. an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of their records was found for some of the

  19. Human influences on streamflow drought characteristics in England and Wales

    Directory of Open Access Journals (Sweden)

    E. Tijdeman

    2018-02-01

    Full Text Available Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata (Factors Affecting Runoff of the UK National River Flow Archive (NRFA. A screening approach was applied on the streamflow records to identify human-influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in (1 the relationship between streamflow drought duration and the base flow index, BFI (specifically, BFIHOST, the BFI predicted from the hydrological properties of soils, (2 the correlation between streamflow and precipitation and (3 the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e. an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of their records was found for

  20. Streamflow characteristics at hydrologic bench-mark stations

    Science.gov (United States)

    Lawrence, C.L.

    1987-01-01

    The Hydrologic Bench-Mark Network was established in the 1960's. Its objectives were to document the hydrologic characteristics of representative undeveloped watersheds nationwide and to provide a comparative base for studying the effects of man on the hydrologic environment. The network, which consists of 57 streamflow gaging stations and one lake-stage station in 39 States, is planned for permanent operation. This interim report describes streamflow characteristics at each bench-mark site and identifies time trends in annual streamflow that have occurred during the data-collection period. The streamflow characteristics presented for each streamflow station are (1) flood and low-flow frequencies, (2) flow duration, (3) annual mean flow, and (4) the serial correlation coefficient for annual mean discharge. In addition, Kendall's tau is computed as an indicator of time trend in annual discharges. The period of record for most stations was 13 to 17 years, although several stations had longer periods of record. The longest period was 65 years for Merced River near Yosemite, Calif. Records of flow at 6 of 57 streamflow sites in the network showed a statistically significant change in annual mean discharge over the period of record, based on computations of Kendall's tau. The values of Kendall's tau ranged from -0.533 to 0.648. An examination of climatological records showed that changes in precipitation were most likely the cause for the change in annual mean discharge.

  1. Long-range forecasting of intermittent streamflow

    Science.gov (United States)

    van Ogtrop, F. F.; Vervoort, R. W.; Heller, G. Z.; Stasinopoulos, D. M.; Rigby, R. A.

    2011-11-01

    Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth) of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.

  2. Long-range forecasting of intermittent streamflow

    Directory of Open Access Journals (Sweden)

    F. F. van Ogtrop

    2011-11-01

    Full Text Available Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.

  3. Methods for estimating drought streamflow probabilities for Virginia streams

    Science.gov (United States)

    Austin, Samuel H.

    2014-01-01

    Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.

  4. Streamflow conditions along Soldier Creek, Northeast Kansas

    Science.gov (United States)

    Juracek, Kyle E.

    2017-11-14

    The availability of adequate water to meet the present (2017) and future needs of humans, fish, and wildlife is a fundamental issue for the Prairie Band Potawatomi Nation in northeast Kansas. Because Soldier Creek flows through the Prairie Band Potawatomi Nation Reservation, it is an important tribal resource. An understanding of historical Soldier Creek streamflow conditions is required for the effective management of tribal water resources, including drought contingency planning. Historical data for six selected U.S. Geological Survey (USGS) streamgages along Soldier Creek were used in an assessment of streamflow characteristics and trends by Juracek (2017). Streamflow data for the period of record at each streamgage were used to compute annual mean streamflow, annual mean base flow, mean monthly flow, annual peak flow, and annual minimum flow. Results of the assessment are summarized in this fact sheet.

  5. Streamflow Gaging Stations

    Data.gov (United States)

    Department of Homeland Security — This map layer shows selected streamflow gaging stations of the United States, Puerto Rico, and the U.S. Virgin Islands, in 2013. Gaging stations, or gages, measure...

  6. Hydrologic Conditions that Influence Streamflow Losses in a Karst Region of the Upper Peace River, Polk County, Florida

    Science.gov (United States)

    Metz, P.A.; Lewelling, B.R.

    2009-01-01

    feet per second, or about 32 million gallons per day, on June 28, 2002. Streamflow losses varied throughout the year, and were related to seasonal fluctuations in groundwater levels. When groundwater levels were at their lowest level at the end of the dry season (May and June), there was an increased potential for streamflow losses. During this study, the largest streamflow losses occurred at the beginning of the summer rainy season when discharge in the river increased and large volumes of water were needed to replenish unfilled cavities and void spaces in the underlying aquifers. The underlying geology along the upper Peace River and floodplain is highly karstified, and aids in the movement and amount of streamflow that is lost to the groundwater system in this region. Numerous karst features and fractured carbonates and cavernous zones observed in geologic cores and geophysical logs indicate an active, well-connected, groundwater flow system. Aquifer and dye tests conducted along the upper Peace River indicate the presence of cavernous and highly transmissive layers within the floodplain area that can store and transport large volumes of water in underground cavities. A discharge measurement made during this study indicates that the cavernous system associated with Dover Sink can accept over 10 million gallons per day (16 cubic feet per second) of streamflow before the localized aquifer storage volume is replenished and the level of the sink is stabilized.

  7. 15 CFR 996.20 - Submission of a hydrographic product for certification.

    Science.gov (United States)

    2010-01-01

    ... QUALITY ASSURANCE AND CERTIFICATION REQUIREMENTS FOR NOAA HYDROGRAPHIC PRODUCTS AND SERVICES QUALITY ASSURANCE AND CERTIFICATION REQUIREMENTS FOR NOAA HYDROGRAPHIC PRODUCTS AND SERVICES Certification of a Hydrographic Product and Decertification. § 996.20 Submission of a hydrographic product for certification. (a...

  8. Characteristics and changes of streamflow on the Tibetan Plateau: A review

    Directory of Open Access Journals (Sweden)

    Lan Cuo

    2014-11-01

    New hydrological insights for the region: Streamflow follows the monthly patterns of precipitation and temperature in that all peak in May–September. Streamflow changes are affected by climate change and human activities depending on the basins. Streamflow is precipitation dominated in the northern, eastern and southeastern basins. In the central and western basin either melt water or groundwater, or both contributes significantly to streamflow. Human activities have altered streamflow in the lower reaches of the eastern, northern and western basins. Long-term trends in streamflow vary with basins. Outstanding research issues include: (1 What are the linkages between streamflow and climate systems? (2 What are the basin-wide hydrological processes? And (3 What are the cryospheric change impacts on hydrological processes and water balance?

  9. Effect of monthly areal rainfall uncertainty on streamflow simulation

    Science.gov (United States)

    Ndiritu, J. G.; Mkhize, N.

    2017-08-01

    Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

  10. Seasonal Patterns of Gastrointestinal Illness and Streamflow along the Ohio River

    Directory of Open Access Journals (Sweden)

    Elena N. Naumova

    2012-05-01

    Full Text Available Waterborne gastrointestinal (GI illnesses demonstrate seasonal increases associated with water quality and meteorological characteristics. However, few studies have been conducted on the association of hydrological parameters, such as streamflow, and seasonality of GI illnesses. Streamflow is correlated with biological contamination and can be used as proxy for drinking water contamination. We compare seasonal patterns of GI illnesses in the elderly (65 years and older along the Ohio River for a 14-year period (1991–2004 to seasonal patterns of streamflow. Focusing on six counties in close proximity to the river, we compiled weekly time series of hospitalizations for GI illnesses and streamflow data. Seasonal patterns were explored using Poisson annual harmonic regression with and without adjustment for streamflow. GI illnesses demonstrated significant seasonal patterns with peak timing preceding peak timing of streamflow for all six counties. Seasonal patterns of illness remain consistent after adjusting for streamflow. This study found that the time of peak GI illness precedes the peak of streamflow, suggesting either an indirect relationship or a more direct path whereby pathogens enter water supplies prior to the peak in streamflow. Such findings call for interdisciplinary research to better understand associations among streamflow, pathogen loading, and rates of gastrointestinal illnesses.

  11. Drivers influencing streamflow changes in the Upper Turia basin, Spain.

    Science.gov (United States)

    Salmoral, Gloria; Willaarts, Bárbara A; Troch, Peter A; Garrido, Alberto

    2015-01-15

    Many rivers across the world have experienced a significant streamflow reduction over the last decades. Drivers of the observed streamflow changes are multiple, including climate change (CC), land use and land cover changes (LULCC), water transfers and river impoundment. Many of these drivers inter-act simultaneously, making it difficult to discern the impact of each driver individually. In this study we isolate the effects of LULCC on the observed streamflow reduction in the Upper Turia basin (east Spain) during the period 1973-2008. Regression models of annual streamflow are fitted with climatic variables and also additional time variant drivers like LULCC. The ecohydrological model SWAT is used to study the magnitude and sign of streamflow change when LULCC occurs. Our results show that LULCC does play a significant role on the water balance, but it is not the main driver underpinning the observed reduction on Turia's streamflow. Increasing mean temperature is the main factor supporting increasing evapotranspiration and streamflow reduction. In fact, LULCC and CC have had an offsetting effect on the streamflow generation during the study period. While streamflow has been negatively affected by increasing temperature, ongoing LULCC have positively compensated with reduced evapotranspiration rates, thanks to mainly shrubland clearing and forest degradation processes. These findings are valuable for the management of the Turia river basin, as well as a useful approach for the determination of the weight of LULCC on the hydrological response in other regions. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Optimal hydrograph separation using a recursive digital filter constrained by chemical mass balance, with application to selected Chesapeake Bay watersheds

    Science.gov (United States)

    Raffensperger, Jeff P.; Baker, Anna C.; Blomquist, Joel D.; Hopple, Jessica A.

    2017-06-26

    Quantitative estimates of base flow are necessary to address questions concerning the vulnerability and response of the Nation’s water supply to natural and human-induced change in environmental conditions. An objective of the U.S. Geological Survey National Water-Quality Assessment Project is to determine how hydrologic systems are affected by watershed characteristics, including land use, land cover, water use, climate, and natural characteristics (geology, soil type, and topography). An important component of any hydrologic system is base flow, generally described as the part of streamflow that is sustained between precipitation events, fed to stream channels by delayed (usually subsurface) pathways, and more specifically as the volumetric discharge of water, estimated at a measurement site or gage at the watershed scale, which represents groundwater that discharges directly or indirectly to stream reaches and is then routed to the measurement point.Hydrograph separation using a recursive digital filter was applied to 225 sites in the Chesapeake Bay watershed. The recursive digital filter was chosen for the following reasons: it is based in part on the assumption that groundwater acts as a linear reservoir, and so has a physical basis; it has only two adjustable parameters (alpha, obtained directly from recession analysis, and beta, the maximum value of the base-flow index that can be modeled by the filter), which can be determined objectively and with the same physical basis of groundwater reservoir linearity, or that can be optimized by applying a chemical-mass-balance constraint. Base-flow estimates from the recursive digital filter were compared with those from five other hydrograph-separation methods with respect to two metrics: the long-term average fraction of streamflow that is base flow, or base-flow index, and the fraction of days where streamflow is entirely base flow. There was generally good correlation between the methods, with some biased

  13. The Global Streamflow Indices and Metadata Archive (GSIM) - Part 1: The production of a daily streamflow archive and metadata

    Science.gov (United States)

    Do, Hong Xuan; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth

    2018-04-01

    This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM), a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections). It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477" target="_blank">https://doi.pangaea.de/10.1594/PANGAEA.887477): (1) a GSIM catalogue collating basic metadata associated with each time series, (2) catchment boundaries for the contributing area of each gauge, and (3) catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.

  14. Development of storm hydrographs for three rivers within drainage ...

    African Journals Online (AJOL)

    The design storm hydrographs corresponding to.the excess rainfall values were determined based on the unit hydrograph ordinates established through convolution. The design storm hydrograph obtain~d for Moro River catchment based on 5-yr, 20~yr~ 50-yr, 100-yr and 200-yr return period ranged between 245.29m3/s ...

  15. Identification of Flood Reactivity Regions via the Functional Clustering of Hydrographs

    Science.gov (United States)

    Brunner, Manuela I.; Viviroli, Daniel; Furrer, Reinhard; Seibert, Jan; Favre, Anne-Catherine

    2018-03-01

    Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.

  16. The Global Streamflow Indices and Metadata Archive (GSIM – Part 1: The production of a daily streamflow archive and metadata

    Directory of Open Access Journals (Sweden)

    H. X. Do

    2018-04-01

    Full Text Available This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM, a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections. It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477: (1 a GSIM catalogue collating basic metadata associated with each time series, (2 catchment boundaries for the contributing area of each gauge, and (3 catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.

  17. Influence of landscape mosaic on streamflow of a peri-urban catchment under Mediterranean climate

    Science.gov (United States)

    Ferreira, Carla; Walsh, Rory; Ferreira, António

    2017-04-01

    Peri-urban areas tend to be characterized by patchy landscape mosaics of different land-uses. Although the impact of land-use changes on catchment hydrology have been widely investigated, the impact of mixed land-use patterns on the streamflow of peri-urban areas is still poorly understood. This study aims to (i) explore and quantify streamflow delivery from sub-catchments characterized by distinct landscape mosaics; (ii) assess the impact of different urbanization styles on hydrograph properties; and (iii) explore the influence of urbanization type on flow connectivity and stream discharge. The study was carried out in Ribeira dos Covões, a small (6.2km2) peri-urban catchment in central Portugal. The climate is Mediterranean, with a mean annual rainfall of 892mm. Catchment geology comprises sandstone (56%), limestone (41%) and alluvial deposits (3%). Soils developed on sandstone are generally deep (>3m) Fluvisols and Podsols, whereas on limestone the Leptic Cambisols are typically shallow (blocks and of high population density (9900 inhabitants km-2). The study uses hydrological data recorded over three hydrological years, starting in November 2010, in a monitoring network comprising eight streamflow gauging stations (instrumented with water level recorders) and five rainfall gauges. The gauging stations provide information on the discharge response to rainstorms of the catchment outlet and upstream sub-catchments of different size, urban pattern (in terms of percentage urban land-use and impervious area, distance to the stream network, and storm water management), and lithology (either sandstone or limestone). Annual storm runoff coefficients were lowest (13.7%) in catchments dominated by forest (>80%) and greatest (17.3-17.6%) in the most urbanized sub-catchments (49-53% urban). Impervious area seems to control streamflow particularly during dry periods. Winter runoff (streamflow per unit area) was 2-4 times higher than summer runoff in highly urbanized areas

  18. Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses

    Science.gov (United States)

    Kronholm, Scott C.; Capel, Paul D.

    2016-01-01

    Mixing models are a commonly used method for hydrograph separation, but can be hindered by the subjective choice of the end-member tracer concentrations. This work tests a new variant of mixing model that uses high-frequency measures of two tracers and streamflow to separate total streamflow into water from slowflow and fastflow sources. The ratio between the concentrations of the two tracers is used to create a time-variable estimate of the concentration of each tracer in the fastflow end-member. Multiple synthetic data sets, and data from two hydrologically diverse streams, are used to test the performance and limitations of the new model (two-tracer ratio-based mixing model: TRaMM). When applied to the synthetic streams under many different scenarios, the TRaMM produces results that were reasonable approximations of the actual values of fastflow discharge (±0.1% of maximum fastflow) and fastflow tracer concentrations (±9.5% and ±16% of maximum fastflow nitrate concentration and specific conductance, respectively). With real stream data, the TRaMM produces high-frequency estimates of slowflow and fastflow discharge that align with expectations for each stream based on their respective hydrologic settings. The use of two tracers with the TRaMM provides an innovative and objective approach for estimating high-frequency fastflow concentrations and contributions of fastflow water to the stream. This provides useful information for tracking chemical movement to streams and allows for better selection and implementation of water quality management strategies.

  19. 76 FR 32957 - Hydrographic Services Review Panel

    Science.gov (United States)

    2011-06-07

    .... SUMMARY: This notice responds to the Hydrographic Service Improvements Act Amendments of 2002, Public Law...), to solicit nominations for membership on the Hydrographic Services Review Panel (HSRP). The HSRP, a...; fisheries management; coastal and marine spatial planning; geodesy; water levels; and other science-related...

  20. 77 FR 76001 - Hydrographic Services Review Panel

    Science.gov (United States)

    2012-12-26

    ... disciplines and fields relating to hydrographic data and hydrographic services, marine transportation, port... represented on the Panel and encourages individuals with expertise in navigation data, products and services... variety of other data in order to fulfill this responsibility. The HSRP provides advice on current and...

  1. Macroinvertebrate community change associated with the severity of streamflow alteration

    Science.gov (United States)

    Carlisle, Daren M.; Eng, Kenny; Nelson, S.M.

    2014-01-01

    Natural streamflows play a critical role in stream ecosystems, yet quantitative relations between streamflow alteration and stream health have been elusive. One reason for this difficulty is that neither streamflow alteration nor ecological responses are measured relative to their natural expectations. We assessed macroinvertebrate community condition in 25 mountain streams representing a large gradient of streamflow alteration, which we quantified as the departure of observed flows from natural expectations. Observed flows were obtained from US Geological Survey streamgaging stations and discharge records from dams and diversion structures. During low-flow conditions in September, samples of macroinvertebrate communities were collected at each site, in addition to measures of physical habitat, water chemistry and organic matter. In general, streamflows were artificially high during summer and artificially low throughout the rest of the year. Biological condition, as measured by richness of sensitive taxa (Ephemeroptera, Plecoptera and Trichoptera) and taxonomic completeness (O/E), was strongly and negatively related to the severity of depleted flows in winter. Analyses of macroinvertebrate traits suggest that taxa losses may have been caused by thermal modification associated with streamflow alteration. Our study yielded quantitative relations between the severity of streamflow alteration and the degree of biological impairment and suggests that water management that reduces streamflows during winter months is likely to have negative effects on downstream benthic communities in Utah mountain streams. 

  2. Application of the geological streamflow and Muskingum Cunge ...

    African Journals Online (AJOL)

    ... of the geological streamflow and Muskingum Cunge models in the Yala River Basin, Kenya. ... can be represented by the application of hydrologic and hydraulic models. ... verification and streamflow routing based on a split record analysis.

  3. Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages

    Science.gov (United States)

    Granato, Gregory E.; Ries, Kernell G.; Steeves, Peter A.

    2017-10-16

    Streamflow statistics are needed by decision makers for many planning, management, and design activities. The U.S. Geological Survey (USGS) StreamStats Web application provides convenient access to streamflow statistics for many streamgages by accessing the underlying StreamStatsDB database. In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in StreamStatsDB for use with StreamStats and other applications. Two previously published USGS computer programs that were designed to help calculate streamflow statistics were updated to better support StreamStats as part of this effort. These programs are named “GNWISQ” (Get National Water Information System Streamflow (Q) files), updated to version 1.1.1, and “QSTATS” (Streamflow (Q) Statistics), updated to version 1.1.2.Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and about 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages. All the statistics are available in a USGS ScienceBase data release.

  4. Streamflow impacts of biofuel policy-driven landscape change.

    Directory of Open Access Journals (Sweden)

    Sami Khanal

    Full Text Available Likely changes in precipitation (P and potential evapotranspiration (PET resulting from policy-driven expansion of bioenergy crops in the United States are shown to create significant changes in streamflow volumes and increase water stress in the High Plains. Regional climate simulations for current and biofuel cropping system scenarios are evaluated using the same atmospheric forcing data over the period 1979-2004 using the Weather Research Forecast (WRF model coupled to the NOAH land surface model. PET is projected to increase under the biofuel crop production scenario. The magnitude of the mean annual increase in PET is larger than the inter-annual variability of change in PET, indicating that PET increase is a forced response to the biofuel cropping system land use. Across the conterminous U.S., the change in mean streamflow volume under the biofuel scenario is estimated to range from negative 56% to positive 20% relative to a business-as-usual baseline scenario. In Kansas and Oklahoma, annual streamflow volume is reduced by an average of 20%, and this reduction in streamflow volume is due primarily to increased PET. Predicted increase in mean annual P under the biofuel crop production scenario is lower than its inter-annual variability, indicating that additional simulations would be necessary to determine conclusively whether predicted change in P is a response to biofuel crop production. Although estimated changes in streamflow volume include the influence of P change, sensitivity results show that PET change is the significantly dominant factor causing streamflow change. Higher PET and lower streamflow due to biofuel feedstock production are likely to increase water stress in the High Plains. When pursuing sustainable biofuels policy, decision-makers should consider the impacts of feedstock production on water scarcity.

  5. Sensitivity of streamflow to climate change in California

    Science.gov (United States)

    Grantham, T.; Carlisle, D.; Wolock, D.; McCabe, G. J.; Wieczorek, M.; Howard, J.

    2015-12-01

    Trends of decreasing snowpack and increasing risk of drought are looming challenges for California water resource management. Increasing vulnerability of the state's natural water supplies threatens California's social-economic vitality and the health of its freshwater ecosystems. Despite growing awareness of potential climate change impacts, robust management adaptation has been hindered by substantial uncertainty in future climate predictions for the region. Down-scaled global climate model (GCM) projections uniformly suggest future warming of the region, but projections are highly variable with respect to the direction and magnitude of change in regional precipitation. Here we examine the sensitivity of California surface water supplies to climate variation independently of GCMs. We use a statistical approach to construct predictive models of monthly streamflow based on historical climate and river basin features. We then propagate an ensemble of synthetic climate simulations through the models to assess potential streamflow responses to changes in temperature and precipitation in different months and regions of the state. We also consider the range of streamflow change predicted by bias-corrected downscaled GCMs. Our results indicate that the streamflow in the xeric and coastal mountain regions of California is more sensitive to changes in precipitation than temperature, whereas streamflow in the interior mountain region responds strongly to changes in both temperature and precipitation. Mean climate projections for 2025-2075 from GCM ensembles are highly variable, indicating streamflow changes of -50% to +150% relative to baseline (1980-2010) for most months and regions. By quantifying the sensitivity of streamflow to climate change, rather than attempting to predict future hydrologic conditions based on uncertain GCM projections, these results should be more informative to water managers seeking to assess, and potentially reduce, the vulnerability of surface

  6. UNDERGROUND

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1993-11-15

    Full text: Cossetted deep underground, sheltered from cosmic ray noise, has always been a favourite haunt of neutrino physicists. Already in the 1930s, significant limits were obtained by taking a geiger counter down in Holborn 'tube' station, one of the deepest in London's underground system. Since then, neutrino physicists have popped up in many unlikely places - gold mines, salt mines, and road tunnels deep under mountain chains. Two such locations - the 1MB (Irvine/ Michigan/Brookhaven) detector 600 metres below ground in an Ohio salt mine, and the Kamiokande apparatus 1000m underground 300 km west of Tokyo - picked up neutrinos on 23 February 1987 from the famous 1987A supernova. Purpose-built underground laboratories have made life easier, notably the Italian Gran Sasso Laboratory near Rome, 1.4 kilometres below the surface, and the Russian Baksan Neutrino Observatory under Mount Andyrchi in the Caucasus range. Gran Sasso houses ICARUS (April, page 15), Gallex, Borexino, Macro and the LVD Large Volume Detector, while Baksan is the home of the SAGE gallium-based solar neutrino experiment. Elsewhere, important ongoing underground neutrino experiments include Soudan II in the US (April, page 16), the Canadian Sudbury Neutrino Observatory with its heavy water target (January 1990, page 23), and Superkamiokande in Japan (May 1991, page 8)

  7. Long-range forecasting of intermittent streamflow

    OpenAIRE

    F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby

    2011-01-01

    Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine th...

  8. Long-range forecasting of intermittent streamflow

    OpenAIRE

    F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby

    2011-01-01

    Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a probabilistic statistical model to forecast streamflow 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probabil...

  9. Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes

    Directory of Open Access Journals (Sweden)

    W. Wang

    2005-01-01

    Full Text Available Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average models for seasonal streamflow series. However, with McLeod-Li test and Engle's Lagrange Multiplier test, clear evidences are found for the existence of autoregressive conditional heteroskedasticity (i.e. the ARCH (AutoRegressive Conditional Heteroskedasticity effect, a nonlinear phenomenon of the variance behaviour, in the residual series from linear models fitted to daily and monthly streamflow processes of the upper Yellow River, China. It is shown that the major cause of the ARCH effect is the seasonal variation in variance of the residual series. However, while the seasonal variation in variance can fully explain the ARCH effect for monthly streamflow, it is only a partial explanation for daily flow. It is also shown that while the periodic autoregressive moving average model is adequate in modelling monthly flows, no model is adequate in modelling daily streamflow processes because none of the conventional time series models takes the seasonal variation in variance, as well as the ARCH effect in the residuals, into account. Therefore, an ARMA-GARCH (Generalized AutoRegressive Conditional Heteroskedasticity error model is proposed to capture the ARCH effect present in daily streamflow series, as well as to preserve seasonal variation in variance in the residuals. The ARMA-GARCH error model combines an ARMA model for modelling the mean behaviour and a GARCH model for modelling the variance behaviour of the residuals from the ARMA model. Since the GARCH model is not followed widely in statistical hydrology, the work can be a useful addition in terms of statistical modelling of daily streamflow processes for the hydrological community.

  10. UNDERGROUND

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    Full text: Cossetted deep underground, sheltered from cosmic ray noise, has always been a favourite haunt of neutrino physicists. Already in the 1930s, significant limits were obtained by taking a geiger counter down in Holborn 'tube' station, one of the deepest in London's underground system. Since then, neutrino physicists have popped up in many unlikely places - gold mines, salt mines, and road tunnels deep under mountain chains. Two such locations - the 1MB (Irvine/ Michigan/Brookhaven) detector 600 metres below ground in an Ohio salt mine, and the Kamiokande apparatus 1000m underground 300 km west of Tokyo - picked up neutrinos on 23 February 1987 from the famous 1987A supernova. Purpose-built underground laboratories have made life easier, notably the Italian Gran Sasso Laboratory near Rome, 1.4 kilometres below the surface, and the Russian Baksan Neutrino Observatory under Mount Andyrchi in the Caucasus range. Gran Sasso houses ICARUS (April, page 15), Gallex, Borexino, Macro and the LVD Large Volume Detector, while Baksan is the home of the SAGE gallium-based solar neutrino experiment. Elsewhere, important ongoing underground neutrino experiments include Soudan II in the US (April, page 16), the Canadian Sudbury Neutrino Observatory with its heavy water target (January 1990, page 23), and Superkamiokande in Japan (May 1991, page 8)

  11. Bayesian Models for Streamflow and River Network Reconstruction using Tree Rings

    Science.gov (United States)

    Ravindranath, A.; Devineni, N.

    2016-12-01

    Water systems face non-stationary, dynamically shifting risks due to shifting societal conditions and systematic long-term variations in climate manifesting as quasi-periodic behavior on multi-decadal time scales. Water systems are thus vulnerable to long periods of wet or dry hydroclimatic conditions. Streamflow is a major component of water systems and a primary means by which water is transported to serve ecosystems' and human needs. Thus, our concern is in understanding streamflow variability. Climate variability and impacts on water resources are crucial factors affecting streamflow, and multi-scale variability increases risk to water sustainability and systems. Dam operations are necessary for collecting water brought by streamflow while maintaining downstream ecological health. Rules governing dam operations are based on streamflow records that are woefully short compared to periods of systematic variation present in the climatic factors driving streamflow variability and non-stationarity. We use hierarchical Bayesian regression methods in order to reconstruct paleo-streamflow records for dams within a basin using paleoclimate proxies (e.g. tree rings) to guide the reconstructions. The riverine flow network for the entire basin is subsequently modeled hierarchically using feeder stream and tributary flows. This is a starting point in analyzing streamflow variability and risks to water systems, and developing a scientifically-informed dynamic risk management framework for formulating dam operations and water policies to best hedge such risks. We will apply this work to the Missouri and Delaware River Basins (DRB). Preliminary results of streamflow reconstructions for eight dams in the upper DRB using standard Gaussian regression with regional tree ring chronologies give streamflow records that now span two to two and a half centuries, and modestly smoothed versions of these reconstructed flows indicate physically-justifiable trends in the time series.

  12. Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2013-10-01

    As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation) and evapotranspiration (normalised by radiation) on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

  13. Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

    Directory of Open Access Journals (Sweden)

    R. Orth

    2013-10-01

    Full Text Available As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation and evapotranspiration (normalised by radiation on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

  14. Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns

    Science.gov (United States)

    Chen, Chia-Jeng; Lee, Tsung-Yu

    2017-04-01

    Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping

  15. Streamflow of 2016—Water year summary

    Science.gov (United States)

    Jian, Xiaodong; Wolock, David M.; Lins, Harry F.; Brady, Steven J.

    2017-09-26

    The maps and graphs in this summary describe national streamflow conditions for water year 2016 (October 1, 2015, to September 30, 2016) in the context of streamflow ranks relative to the 87-year period of 1930–2016, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey’s (USGS) National Streamflow Network. The period of 1930–2016 was used because the number of streamgages before 1930 was too small to provide representative data for computing statistics for most regions of the country.In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified period was uniformly distributed on it. Runoff quantifies the magnitude of water flowing through the Nation’s rivers and streams in measurement units that can be compared from one area to another.In all the graphics, a rank of 1 indicates the highest flow of all years analyzed and 87 indicates the lowest flow of all years. Rankings of streamflow are grouped into much below normal, below normal, normal, above normal, and much above normal based on percentiles of flow (less than 10 percent, 10–24 percent, 25–75 percent, 76–90 percent, and greater than 90 percent, respectively). Some of the data used to produce the maps and graphs are provisional and subject to change.

  16. Substantial proportion of global streamflow less than three months old

    Science.gov (United States)

    Jasechko, Scott; Kirchner, James W.; Welker, Jeffrey M.; McDonnell, Jeffrey J.

    2016-02-01

    Biogeochemical cycles, contaminant transport and chemical weathering are regulated by the speed at which precipitation travels through landscapes and reaches streams. Streamflow is a mixture of young and old precipitation, but the global proportions of these young and old components are not known. Here we analyse seasonal cycles of oxygen isotope ratios in rain, snow and streamflow compiled from 254 watersheds around the world, and calculate the fraction of streamflow that is derived from precipitation that fell within the past two or three months. This young streamflow accounts for about a third of global river discharge, and comprises at least 5% of discharge in about 90% of the catchments we investigated. We conclude that, although typical catchments have mean transit times of years or even decades, they nonetheless can rapidly transmit substantial fractions of soluble contaminant inputs to streams. Young streamflow is less prevalent in steeper landscapes, which suggests they are characterized by deeper vertical infiltration. Because young streamflow is derived from less than 0.1% of global groundwater storage, we conclude that this thin veneer of aquifer storage will have a disproportionate influence on stream water quality.

  17. Underground storage tanks

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    Environmental contamination from leaking underground storage tanks poses a significant threat to human health and the environment. An estimated five to six million underground storage tanks containing hazardous substances or petroleum products are in use in the US. Originally placed underground as a fire prevention measure, these tanks have substantially reduced the damages from stored flammable liquids. However, an estimated 400,000 underground tanks are thought to be leaking now, and many more will begin to leak in the near future. Products released from these leaking tanks can threaten groundwater supplies, damage sewer lines and buried cables, poison crops, and lead to fires and explosions. As required by the Hazardous and Solid Waste Amendments (HSWA), the EPA has been developing a comprehensive regulatory program for underground storage tanks. The EPA proposed three sets of regulations pertaining to underground tanks. The first addressed technical requirements for petroleum and hazardous substance tanks, including new tank performance standards, release detection, release reporting and investigation, corrective action, and tank closure. The second proposed regulation addresses financial responsibility requirements for underground petroleum tanks. The third addressed standards for approval of state tank programs

  18. Underground pipeline corrosion

    CERN Document Server

    Orazem, Mark

    2014-01-01

    Underground pipelines transporting liquid petroleum products and natural gas are critical components of civil infrastructure, making corrosion prevention an essential part of asset-protection strategy. Underground Pipeline Corrosion provides a basic understanding of the problems associated with corrosion detection and mitigation, and of the state of the art in corrosion prevention. The topics covered in part one include: basic principles for corrosion in underground pipelines, AC-induced corrosion of underground pipelines, significance of corrosion in onshore oil and gas pipelines, n

  19. Prediction of Missing Streamflow Data using Principle of Information Entropy

    Directory of Open Access Journals (Sweden)

    Santosa, B.

    2014-01-01

    Full Text Available Incomplete (missing of streamflow data often occurs. This can be caused by a not continous data recording or poor storage. In this study, missing consecutive streamflow data are predicted using the principle of information entropy. Predictions are performed ​​using the complete monthly streamflow information from the nearby river. Data on average monthly streamflow used as a simulation sample are taken from observation stations Katulampa, Batubeulah, and Genteng, which are the Ciliwung Cisadane river areas upstream. The simulated prediction of missing streamflow data in 2002 and 2003 at Katulampa Station are based on information from Genteng Station, and Batubeulah Station. The mean absolute error (MAE average obtained was 0,20 and 0,21 in 2002 and the MAE average in 2003 was 0,12 and 0,16. Based on the value of the error and pattern of filled gaps, this method has the potential to be developed further.

  20. NOS Hydrographic Surveys Collection

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. Diverse multi-decadal changes in streamflow within a rapidly urbanizing region

    Science.gov (United States)

    Diem, Jeremy E.; Hill, T. Chee; Milligan, Richard A.

    2018-01-01

    The impact of urbanization on streamflow depends on a variety of factors (e.g., climate, initial land cover, inter-basin transfers, water withdrawals, wastewater effluent, etc.). The purpose of this study is to examine trends in streamflow from 1986 to 2015 in a range of watersheds within the rapidly urbanizing Atlanta, GA metropolitan area. This study compares eight watersheds over three decades, while minimizing the influence of inter-annual precipitation variability. Population and land-cover data were used to analyze changes over approximately twenty years within the watersheds. Precipitation totals for the watersheds were estimated using precipitation totals at nearby weather stations. Multiple streamflow variables, such as annual streamflow, frequencies of high-flow days (HFDs), flashiness, and precipitation-adjusted streamflow, for the eight streams were calculated using daily streamflow data. Variables were tested for significant trends from 1986 to 2015 and significant differences between 1986-2000 and 2001-2015. Flashiness increased for all streams without municipal water withdrawals, and the four watersheds with the largest increase in developed land had significant increases in flashiness. Significant positive trends in precipitation-adjusted mean annual streamflow and HFDs occurred for the two watersheds (Big Creek and Suwanee Creek) that experienced the largest increases in development, and these were the only watersheds that went from majority forest land in 1986 to majority developed land in 2015. With a disproportionate increase in HFD occurrence during summer, Big Creek and Suwannee Creek also had a reduction in intra-annual variability of HFD occurrence. Watersheds that were already substantially developed at the beginning of the period and did not have wastewater discharge had declining streamflow. The most urbanized watershed (Peachtree Creek) had a significant decrease in streamflow, and a possible cause of the decrease was increasing

  2. Interaction between stream temperature, streamflow, and groundwater exchanges in alpine streams

    Science.gov (United States)

    Constantz, James E.

    1998-01-01

    Four alpine streams were monitored to continuously collect stream temperature and streamflow for periods ranging from a week to a year. In a small stream in the Colorado Rockies, diurnal variations in both stream temperature and streamflow were significantly greater in losing reaches than in gaining reaches, with minimum streamflow losses occurring early in the day and maximum losses occurring early in the evening. Using measured stream temperature changes, diurnal streambed infiltration rates were predicted to increase as much as 35% during the day (based on a heat and water transport groundwater model), while the measured increase in streamflow loss was 40%. For two large streams in the Sierra Nevada Mountains, annual stream temperature variations ranged from 0° to 25°C. In summer months, diurnal stream temperature variations were 30–40% of annual stream temperature variations, owing to reduced streamflows and increased atmospheric heating. Previous reports document that one Sierra stream site generally gains groundwater during low flows, while the second Sierra stream site may lose water during low flows. For August the diurnal streamflow variation was 11% at the gaining stream site and 30% at the losing stream site. On the basis of measured diurnal stream temperature variations, streambed infiltration rates were predicted to vary diurnally as much as 20% at the losing stream site. Analysis of results suggests that evapotranspiration losses determined diurnal streamflow variations in the gaining reaches, while in the losing reaches, evapotranspiration losses were compounded by diurnal variations in streambed infiltration. Diurnal variations in stream temperature were reduced in the gaining reaches as a result of discharging groundwater of relatively constant temperature. For the Sierra sites, comparison of results with those from a small tributary demonstrated that stream temperature patterns were useful in delineating discharges of bank storage following

  3. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    Directory of Open Access Journals (Sweden)

    F. Fundel

    2013-01-01

    Full Text Available Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month.

    The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive

  4. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    Science.gov (United States)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2013-01-01

    Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month. The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive action based on the forecast.

  5. Synthetic socioeconomic based domestic wastewater hydrographs for small arid communities

    KAUST Repository

    Elnakar, H.

    2012-06-04

    A model was developed to predict synthetic socioeconomic based domestic wastewater hydrographs for the small arid communities. The model predicts the flow hydrograph for random weekdays and weekends based on the specific socioeconomic characteristics of the community. The main socioeconomic characteristics are the composition of the community, the different user behaviours in using water appliances, and the unit discharges of such appliances. Use patterns of water appliances are assumed to vary for the various members of the community and the type of day. Each community is composed of several social categories such as the employee, working woman, stay home woman, stay home child, students etc. The use patterns account for the stochastic nature of use in terms of number of uses, duration of the use and times of use in the day. Randomly generated hydrographs are generated for weekdays and weekends along with synthetic hydrographs of non-exceedance. The model was verified for a small residential compound in Sharm El Shiekh - Egypt using 11 days of flow measurements performed in summer. The synthetic hydrographs based on assumed water use patterns of the various members of the community compared reasonably with the measured hydrographs. Synthetic hydrographs can be derived for a community under consideration to reflect its socioeconomic conditions and thus can be used to generate probability based peaking factors to be used in the design of sewerage systems pumping facilities, and treatment plants. © 201 WIT Press.

  6. Synthetic socioeconomic based domestic wastewater hydrographs for small arid communities

    KAUST Repository

    Elnakar, H.; Imam, E.; Nassar, K.

    2012-01-01

    A model was developed to predict synthetic socioeconomic based domestic wastewater hydrographs for the small arid communities. The model predicts the flow hydrograph for random weekdays and weekends based on the specific socioeconomic characteristics of the community. The main socioeconomic characteristics are the composition of the community, the different user behaviours in using water appliances, and the unit discharges of such appliances. Use patterns of water appliances are assumed to vary for the various members of the community and the type of day. Each community is composed of several social categories such as the employee, working woman, stay home woman, stay home child, students etc. The use patterns account for the stochastic nature of use in terms of number of uses, duration of the use and times of use in the day. Randomly generated hydrographs are generated for weekdays and weekends along with synthetic hydrographs of non-exceedance. The model was verified for a small residential compound in Sharm El Shiekh - Egypt using 11 days of flow measurements performed in summer. The synthetic hydrographs based on assumed water use patterns of the various members of the community compared reasonably with the measured hydrographs. Synthetic hydrographs can be derived for a community under consideration to reflect its socioeconomic conditions and thus can be used to generate probability based peaking factors to be used in the design of sewerage systems pumping facilities, and treatment plants. © 201 WIT Press.

  7. The effects of changing land cover on streamflow simulation in Puerto Rico

    Science.gov (United States)

    Van Beusekom, Ashley; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad

    2014-01-01

    This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

  8. Alteration of streamflow magnitudes and potential ecological consequences: A multiregional assessment

    Science.gov (United States)

    Carlisle, Daren M.; Wolock, David M.; Meador, Michael R.

    2011-01-01

    Human impacts on watershed hydrology are widespread in the US, but the prevalence and severity of stream-flow alteration and its potential ecological consequences have not been quantified on a national scale. We assessed streamflow alteration at 2888 streamflow monitoring sites throughout the conterminous US. The magnitudes of mean annual (1980–2007) minimum and maximum streamflows were found to have been altered in 86% of assessed streams. The occurrence, type, and severity of streamflow alteration differed markedly between arid and wet climates. Biological assessments conducted on a subset of these streams showed that, relative to eight chemical and physical covariates, diminished flow magnitudes were the primary predictors of biological integrity for fish and macroinvertebrate communities. In addition, the likelihood of biological impairment doubled with increasing severity of diminished streamflows. Among streams with diminished flow magnitudes, increasingly common fish and macroinvertebrate taxa possessed traits characteristic of lake or pond habitats, including a preference for fine-grained substrates and slow-moving currents, as well as the ability to temporarily leave the aquatic environment.

  9. extrap: Software to assist the selection of extrapolation methods for moving-boat ADCP streamflow measurements

    Science.gov (United States)

    Mueller, David S.

    2013-04-01

    Selection of the appropriate extrapolation methods for computing the discharge in the unmeasured top and bottom parts of a moving-boat acoustic Doppler current profiler (ADCP) streamflow measurement is critical to the total discharge computation. The software tool, extrap, combines normalized velocity profiles from the entire cross section and multiple transects to determine a mean profile for the measurement. The use of an exponent derived from normalized data from the entire cross section is shown to be valid for application of the power velocity distribution law in the computation of the unmeasured discharge in a cross section. Selected statistics are combined with empirically derived criteria to automatically select the appropriate extrapolation methods. A graphical user interface (GUI) provides the user tools to visually evaluate the automatically selected extrapolation methods and manually change them, as necessary. The sensitivity of the total discharge to available extrapolation methods is presented in the GUI. Use of extrap by field hydrographers has demonstrated that extrap is a more accurate and efficient method of determining the appropriate extrapolation methods compared with tools currently (2012) provided in the ADCP manufacturers' software.

  10. Integrated Hydrographical Basin Management. Study Case - Crasna River Basin

    Science.gov (United States)

    Visescu, Mircea; Beilicci, Erika; Beilicci, Robert

    2017-10-01

    Hydrographical basins are important from hydrological, economic and ecological points of view. They receive and channel the runoff from rainfall and snowmelt which, when adequate managed, can provide fresh water necessary for water supply, irrigation, food industry, animal husbandry, hydrotechnical arrangements and recreation. Hydrographical basin planning and management follows the efficient use of available water resources in order to satisfy environmental, economic and social necessities and constraints. This can be facilitated by a decision support system that links hydrological, meteorological, engineering, water quality, agriculture, environmental, and other information in an integrated framework. In the last few decades different modelling tools for resolving problems regarding water quantity and quality were developed, respectively water resources management. Watershed models have been developed to the understanding of water cycle and pollution dynamics, and used to evaluate the impacts of hydrotechnical arrangements and land use management options on water quantity, quality, mitigation measures and possible global changes. Models have been used for planning monitoring network and to develop plans for intervention in case of hydrological disasters: floods, flash floods, drought and pollution. MIKE HYDRO Basin is a multi-purpose, map-centric decision support tool for integrated hydrographical basin analysis, planning and management. MIKE HYDRO Basin is designed for analyzing water sharing issues at international, national and local hydrographical basin level. MIKE HYDRO Basin uses a simplified mathematical representation of the hydrographical basin including the configuration of river and reservoir systems, catchment hydrology and existing and potential water user schemes with their various demands including a rigorous irrigation scheme module. This paper analyzes the importance and principles of integrated hydrographical basin management and develop a case

  11. Effect of Hydrograph Characteristics on Vertical Grain Sorting in Gravel Bed Rivers

    Science.gov (United States)

    Hassan, M. A.; Parker, G.; Egozi, R.

    2005-12-01

    This study focuses on the formation of armour layers over a range of hydrologic conditions that includes two limiting cases; a relatively flat hydrograph that represents conditions produced by continuous snowmelt and a sharply peaked hydrograph that represents conditions associated with flash floods. To achieve our objective we analyzed field evidence, conducted flume experiments and performed numerical simulations. Sediment supply appears to be a first-order control on bed surface armouring, while the shape of the hydrograph plays a secondary role. All constant hydrograph experiments developed a well-armored structured surface while short asymmetrical hydrographs did not show substantial vertical sorting. All symmetrical hydrographs show some degree of sorting, and the sorting tended to become more pronounced with longer duration. Using the numerical framework of Parker, modified Powell, et al. and Wilcock and Crowe, we were able to achieve similar results.

  12. The Canfranc Underground Laboratory

    International Nuclear Information System (INIS)

    Amare, J.; Beltran, B.; Carmona, J.M.; Cebrian, S.; Garcia, E.; Irastorza, I.G.; Gomez, H.; Luzon, G.; Martinez, M.; Morales, J.; Ortiz de Solorzano, A.; Pobes, C.; Puimedon, J.; Rodriguez, A.; Ruz, J.; Sarsa, M.L.; Torres, L.; Villar, J.A.

    2005-01-01

    This paper describes the forthcoming enlargement of the Canfranc Underground Laboratory (LSC) which will allow to host new international Astroparticle Physics experiments and therefore to broaden the European underground research area. The new Canfranc Underground Laboratory will operate in coordination (through the ILIAS Project) with the Gran Sasso (Italy), Modane (France) and Boulby (UK) underground laboratories

  13. Reconstructing pre-instrumental streamflow in Eastern Australia using a water balance approach

    Science.gov (United States)

    Tozer, C. R.; Kiem, A. S.; Vance, T. R.; Roberts, J. L.; Curran, M. A. J.; Moy, A. D.

    2018-03-01

    Streamflow reconstructions based on paleoclimate proxies provide much longer records than the short instrumental period records on which water resource management plans are currently based. In Australia there is a lack of in-situ high resolution paleoclimate proxy records, but remote proxies with teleconnections to Australian climate have utility in producing streamflow reconstructions. Here we investigate, via a case study for a catchment in eastern Australia, the novel use of an Antarctic ice-core based rainfall reconstruction within a Budyko-framework to reconstruct ∼1000 years of annual streamflow. The resulting streamflow reconstruction captures interannual to decadal variability in the instrumental streamflow, validating both the use of the ice core rainfall proxy record and the Budyko-framework method. In the preinstrumental era the streamflow reconstruction shows longer wet and dry epochs and periods of streamflow variability that are higher than observed in the instrumental era. Importantly, for both the instrumental record and preinstrumental reconstructions, the wet (dry) epochs in the rainfall record are shorter (longer) in the streamflow record and this non-linearity must be considered when inferring hydroclimatic risk or historical water availability directly from rainfall proxy records alone. These insights provide a better understanding of present infrastructure vulnerability in the context of past climate variability for eastern Australia. The streamflow reconstruction presented here also provides a better understanding of the range of hydroclimatic variability possible, and therefore represents a more realistic baseline on which to quantify the potential impacts of anthropogenic climate change on water security.

  14. Design study of underground facility of the Underground Research Laboratory

    International Nuclear Information System (INIS)

    Hibiya, Keisuke; Akiyoshi, Kenji; Ishizuka, Mineo; Anezaki, Susumu

    1998-03-01

    Geoscientific research program to study deep geological environment has been performed by Power Reactor and Nuclear Fuel Development Corporation (PNC). This research is supported by 'Long-Term Program for Research, Development and Utilization of Nuclear Energy'. An Underground Research Laboratory is planned to be constructed at Shoma-sama Hora in the research area belonging to PNC. A wide range of geoscientific research and development activities which have been previously studied at the Tono Area is planned in the laboratory. The Underground Research Laboratory is consisted of Surface Laboratory and Underground Research Facility located from the surface down to depth between several hundreds and 1,000 meters. Based on the results of design study in last year, the design study performed in this year is to investigate the followings in advance of studies for basic design and practical design: concept, design procedure, design flow and total layout. As a study for the concept of the underground facility, items required for the facility are investigated and factors to design the primary form of the underground facility are extracted. Continuously, design methods for the vault and the underground facility are summarized. Furthermore, design procedures of the extracted factors are summarized and total layout is studied considering the results to be obtained from the laboratory. (author)

  15. Preliminary assessment of streamflow characteristics for selected streams at Fort Gordon, Georgia, 1999-2000

    Science.gov (United States)

    Stamey, Timothy C.

    2001-01-01

    In 1999, the U.S. Geological Survey, in cooperation with the U.S. Army Signal Center and Fort Gordon, began collection of periodic streamflow data at four streams on the military base to assess and estimate streamflow characteristics of those streams for potential water-supply sources. Simple and reliable methods of determining streamflow characteristics of selected streams on the military base are needed for the initial implementation of the Fort Gordon Integrated Natural Resources Management Plan. Long-term streamflow data from the Butler Creek streamflow gaging station were used along with several concurrent discharge measurements made at three selected partial-record streamflow stations on Fort Gordon to determine selected low-flow streamflow characteristics. Streamflow data were collected and analyzed using standard U.S. Geological Survey methods and computer application programs to verify the use of simple drainage area to discharge ratios, which were used to estimate the low-flow characteristics for the selected streams. Low-flow data computed based on daily mean streamflow include: mean discharges for consecutive 1-, 3-, 7-, 14-, and 30-day period and low-flow estimates of 7Q10, 30Q2, 60Q2, and 90Q2 recurrence intervals. Flow-duration data also were determined for the 10-, 30-, 50-, 70-, and 90-percent exceedence flows. Preliminary analyses of the streamflow indicate that the flow duration and selected low-flow statistics for the selected streams averages from about 0.15 to 2.27 cubic feet per square mile. The long-term gaged streamflow data indicate that the streamflow conditions for the period analyzed were in the 50- to 90-percent flow range, or in which streamflow would be exceeded about 50 to 90 percent of the time.

  16. Contribution of human and climate change impacts to changes in streamflow of Canada.

    Science.gov (United States)

    Tan, Xuezhi; Gan, Thian Yew

    2015-12-04

    Climate change exerts great influence on streamflow by changing precipitation, temperature, snowpack and potential evapotranspiration (PET), while human activities in a watershed can directly alter the runoff production and indirectly through affecting climatic variables. However, to separate contribution of anthropogenic and natural drivers to observed changes in streamflow is non-trivial. Here we estimated the direct influence of human activities and climate change effect to changes of the mean annual streamflow (MAS) of 96 Canadian watersheds based on the elasticity of streamflow in relation to precipitation, PET and human impacts such as land use and cover change. Elasticities of streamflow for each watershed are analytically derived using the Budyko Framework. We found that climate change generally caused an increase in MAS, while human impacts generally a decrease in MAS and such impact tends to become more severe with time, even though there are exceptions. Higher proportions of human contribution, compared to that of climate change contribution, resulted in generally decreased streamflow of Canada observed in recent decades. Furthermore, if without contributions from retreating glaciers to streamflow, human impact would have resulted in a more severe decrease in Canadian streamflow.

  17. Performance Analysis of Low-Cost Single-Frequency GPS Receivers in Hydrographic Surveying

    Science.gov (United States)

    Elsobeiey, M.

    2017-10-01

    The International Hydrographic Organization (IHO) has issued standards that provide the minimum requirements for different types of hydrographic surveys execution to collect data to be used to compile navigational charts. Such standards are usually updated from time to time to reflect new survey techniques and practices and must be achieved to assure both surface navigation safety and marine environment protection. Hydrographic surveys can be classified to four orders namely, special order, order 1a, order 1b, and order 2. The order of hydrographic surveys to use should be determined in accordance with the importance to the safety of navigation in the surveyed area. Typically, geodetic-grade dual-frequency GPS receivers are utilized for position determination during data collection in hydrographic surveys. However, with the evolution of high-sensitivity low-cost single-frequency receivers, it is very important to evaluate the performance of such receivers. This paper investigates the performance of low-cost single-frequency GPS receivers in hydrographic surveying applications. The main objective is to examine whether low-cost single-frequency receivers fulfil the IHO standards for hydrographic surveys. It is shown that the low-cost single-frequency receivers meet the IHO horizontal accuracy for all hydrographic surveys orders at any depth. However, the single-frequency receivers meet only order 2 requirements for vertical accuracy at depth more than or equal 100 m.

  18. Variance analysis of forecasted streamflow maxima in a wet temperate climate

    Science.gov (United States)

    Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

    2018-05-01

    Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

  19. Design flood hydrographs from the relationship between flood peak and volume

    Directory of Open Access Journals (Sweden)

    L. Mediero

    2010-12-01

    Full Text Available Hydrological frequency analyses are usually focused on flood peaks. Flood volumes and durations have not been studied as extensively, although there are many practical situations, such as when designing a dam, in which the full hydrograph is of interest. A flood hydrograph may be described by a multivariate function of the peak, volume and duration. Most standard bivariate and trivariate functions do not produce univariate three-parameter functions as marginal distributions, however, three-parameter functions are required to fit highly skewed data, such as flood peak and flood volume series. In this paper, the relationship between flood peak and hydrograph volume is analysed to overcome this problem. A Monte Carlo experiment was conducted to generate an ensemble of hydrographs that maintain the statistical properties of marginal distributions of the peaks, volumes and durations. This ensemble can be applied to determine the Design Flood Hydrograph (DFH for a reservoir, which is not a unique hydrograph, but rather a curve in the peak-volume space. All hydrographs on that curve have the same return period, which can be understood as the inverse of the probability to exceed a certain water level in the reservoir in any given year. The procedure can also be applied to design the length of the spillway crest in terms of the risk of exceeding a given water level in the reservoir.

  20. Spatial patterns of March and September streamflow trends in Pacific Northwest Streams, 1958-2008

    Science.gov (United States)

    Chang, Heejun; Jung, Il-Won; Steele, Madeline; Gannett, Marshall

    2012-01-01

    Summer streamflow is a vital water resource for municipal and domestic water supplies, irrigation, salmonid habitat, recreation, and water-related ecosystem services in the Pacific Northwest (PNW) in the United States. This study detects significant negative trends in September absolute streamflow in a majority of 68 stream-gauging stations located on unregulated streams in the PNW from 1958 to 2008. The proportion of March streamflow to annual streamflow increases in most stations over 1,000 m elevation, with a baseflow index of less than 50, while absolute March streamflow does not increase in most stations. The declining trends of September absolute streamflow are strongly associated with seven-day low flow, January–March maximum temperature trends, and the size of the basin (19–7,260 km2), while the increasing trends of the fraction of March streamflow are associated with elevation, April 1 snow water equivalent, March precipitation, center timing of streamflow, and October–December minimum temperature trends. Compared with ordinary least squares (OLS) estimated regression models, spatial error regression and geographically weighted regression (GWR) models effectively remove spatial autocorrelation in residuals. The GWR model results show spatial gradients of local R 2 values with consistently higher local R 2 values in the northern Cascades. This finding illustrates that different hydrologic landscape factors, such as geology and seasonal distribution of precipitation, also influence streamflow trends in the PNW. In addition, our spatial analysis model results show that considering various geographic factors help clarify the dynamics of streamflow trends over a large geographical area, supporting a spatial analysis approach over aspatial OLS-estimated regression models for predicting streamflow trends. Results indicate that transitional rain–snow surface water-dominated basins are likely to have reduced summer streamflow under warming scenarios

  1. Application of ANN and fuzzy logic algorithms for streamflow ...

    Indian Academy of Sciences (India)

    The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years ...

  2. F00190: NOS Hydrographic Survey , Hydrographic and Wire Drag Investigations, Connecticut, 1963-05-13

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. Climate model assessment of changes in winter-spring streamflow timing over North America

    Science.gov (United States)

    Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.

    2018-01-01

    Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.

  4. Relative contributions of transient and steady state infiltration during ephemeral streamflow

    Science.gov (United States)

    Blasch, Kyle W.; Ferré, Ty P.A.; Hoffmann, John P.; Fleming, John B.

    2006-01-01

    Simulations of infiltration during three ephemeral streamflow events in a coarse‐grained alluvial channel overlying a less permeable basin‐fill layer were conducted to determine the relative contribution of transient infiltration at the onset of streamflow to cumulative infiltration for the event. Water content, temperature, and piezometric measurements from 2.5‐m vertical profiles within the alluvial sediments were used to constrain a variably saturated water flow and heat transport model. Simulated and measured transient infiltration rates at the onset of streamflow were about two to three orders of magnitude greater than steady state infiltration rates. The duration of simulated transient infiltration ranged from 1.8 to 20 hours, compared with steady state flow periods of 231 to 307 hours. Cumulative infiltration during the transient period represented 10 to 26% of the total cumulative infiltration, with an average contribution of approximately 18%. Cumulative infiltration error for the simulated streamflow events ranged from 9 to 25%. Cumulative infiltration error for typical streamflow events of about 8 hours in duration in is about 90%. This analysis indicates that when estimating total cumulative infiltration in coarse‐grained ephemeral stream channels, consideration of the transient infiltration at the onset of streamflow will improve predictions of the total volume of infiltration that may become groundwater recharge.

  5. Changing characteristics of streamflow in the Midwest and its relation to oceanic-atmospheric oscillations

    Science.gov (United States)

    Thakur, B.; Pathak, P.; Kalra, A.; Ahmad, S.

    2016-12-01

    The identification of primary drivers of streamflow may prove beneficial in forecasting streamflow in the Midwestern U.S. In the past researches, streamflow in the region have been strongly correlated with El Niño-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO). The present study takes in to account the pre-defined Pacific and Atlantic Ocean regions (e.g., ENSO, PDO, AMO) along with new regions with an intent to identify new significantly correlated regions. This study assesses the interrelationship between sea surface temperatures (SST) anomalies in the Pacific and Atlantic Ocean and seasonal streamflow in the Midwestern U.S. Average Pacific and Atlantic Ocean SST anomalies, were calculated for 2 different 3 month series: September-November and December-February so as to create a lead time varying from 3 to 9 months. Streamflow were averaged for three seasons: spring (April-June), spring-summer (April-August) and summer (June-August). The correlation between streamflow and SST is analyzed using singular value decomposition for a period of 1960-2013. The result of the study showed several regions-other than the known Pacific and Atlantic Ocean regions- that were significantly correlated with streamflow stations. Higher correlation between the climate indices and streamflow were observed as the lead time decreased. The identification of the associations between SST and streamflow and significant SST regions in the Pacific and Atlantic Ocean may enhance the skill of streamflow predictability and water management in the region.

  6. Environment Of Underground Water And Pollution

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jeong Sang

    1998-02-15

    This book deals with environment of underground water and pollution, which introduces the role of underground water in hydrology, definition of related study of under water, the history of hydro-geology, basic conception of underground water such as origin of water, and hydrogeologic characteristic of aquifers, movement of underground water, hydrography of underground water and aquifer test analysis, change of an underground water level, and water balance analysis and development of underground water.

  7. Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains

    Science.gov (United States)

    Shen, Yan-Jun; Shen, Yanjun; Fink, Manfred; Kralisch, Sven; Chen, Yaning; Brenning, Alexander

    2018-02-01

    Streamflow and snowmelt runoff timing of mountain rivers are susceptible to climate change. Trends and variability in streamflow and snowmelt runoff timing in four mountain basins in the southern Tianshan were analyzed in this study. Streamflow trends were detected by Mann-Kendall tests and changes in snowmelt runoff timing were analyzed based on the winter/spring snowmelt runoff center time (WSCT). Pearson's correlation coefficient was further calculated to analyze the relationships between climate variables, streamflow and WSCT. Annual streamflow increased significantly in past decades in the southern Tianshan, especially in spring and winter months. However, the relations between streamflow and temperature/precipitation depend on the different streamflow generation processes. Annual precipitation plays a vital role in controlling recharge in the Toxkon basin, while the Kaidu and Huangshuigou basins are governed by both precipitation and temperature. Seasonally, temperature has a strong effect on streamflow in autumn and winter, while summer streamflow appears more sensitive to changes in precipitation. However, temperature is the dominant factor for streamflow in the glacierized Kunmalik basin at annual and seasonal scales. An uptrend in streamflow begins in the 1990s at both annual and seasonal scales, which is generally consistent with temperature and precipitation fluctuations. Average WSCT dates in the Kaidu and Huangshuigou basins are earlier than in the Toxkon and Kunmalik basins, and shifted towards earlier dates since the mid-1980s in all the basins. It is plausible that WSCT dates are more sensitive to warmer temperature in spring period compared to precipitation, except for the Huangshuigou basin. Taken together, these findings are useful for applications in flood risk regulation, future hydropower projects and integrated water resources management.

  8. The role of groundwater in streamflow in a headwater catchment with sub-humid climate

    Science.gov (United States)

    Liu, Yaping; Tian, Fuqiang; Hu, Hongchang; Tie, Qiang

    2015-04-01

    Recent studies have suggested that bedrock groundwater can exert considerable influence on streamflow in headwater catchments under humid climate. However, study of the role of bedrock groundwater is still challenged due to limited direct observation data. In this study, by utilizing observed hydrometric and hydrochemical data, we aimed at characterize the bedrock groundwater's response to rainfall at hillslope and catchment scales in a small headwater catchment with sub-humid climate. We selected Xitaizi catchment with area of 6.7 km in the earth-rock mountain region, which located in the north of Beijing, China, as study area. The catchment bedrock is mainly consist of fractured granite. Four weather stations were installed to observe the weather condition and soil volumetric water content (VWC) at depth of 10-60 cm with 10-minute interval. Five wells with depth of 10 m were drilled in two slopes to monitor the bedrock water table by pneumatic water gauge. At slope 1, the soil VWC at depth of 10-80 cm were also observed by soil moisture sensors, and surface/subsurface hillslope runoff at three different layers (0-20cm, 20-80cm, 80-300cm) was observed by three recording buckets. Field works were conducted from July 2013 to November 2014. During the period, precipitation, river, spring and groundwater were sampled nearly monthly. Water temperature, electrical conductivity (EC) and pH were measured in site with portable instruments. In addition, the precipitation, river and groundwater were also sampled intensively during two storm events. All the samples were subjected to stable isotope analysis, the samples taken monthly during the period from July 2013 to July 2014 were subjected to hydrochemistry analysis. Our results show that: (1) the bedrock groundwater is the dominant component of streamflow in the headwater catchment with sub-humid climate; (2) stream is recharged by groundwater sourcing from different mountains with different hydrochemistry characteristics

  9. Past and future changes of streamflow in Poyang Lake Basin, Southeastern China

    Directory of Open Access Journals (Sweden)

    S. L. Sun

    2012-07-01

    Full Text Available To understand the causes of the past water cycle variations and the influence of climate variability on the streamflow, lake storage, and flood potential, we analyze the changes in streamflow and the underlying drivers in four typical watersheds (Gaosha, Meigang, Saitang, and Xiashan within the Poyang Lake Basin, based on the meteorological observations at 79 weather stations, and datasets of streamflow and river level at four hydrological stations for the period of 1961-2000. The contribution of different climate factors to the change in streamflow in each watershed is estimated quantitatively using the water balance equations. Results show that in each watershed, the annual streamflow exhibits an increasing trend from 1961–2000. The increases in streamflow by 4.80 m3 s−1 yr−1 and 1.29 m3 s−1 yr−1 at Meigang and Gaosha, respectively, are statistically significant at the 5% level. The increase in precipitation is the biggest contributor to the streamflow increment in Meigang (3.79 m3 s−1 yr−1, Gaosha (1.12 m3 s−1 yr−1, and Xiashan (1.34 m3 s−1 yr−1, while the decrease in evapotranspiration is the major factor controlling the streamflow increment in Saitang (0.19 m3 s−1 yr−1. In addition, radiation and wind contribute more than actual vapor pressure and mean temperature to the changes in evapotranspiration and streamflow for the four watersheds.

    For revealing the possible change of streamflow due to the future climate change, we also investigate the projected precipitation and evapotranspiration from of the Coupled Model Intercomparison Project phase 3 (CMIP3 under three greenhouse gases emission scenarios (SRESA1B, SRESA2 and SRESB1 for the period of 2061–2100. When the future changes in the soil water storage

  10. A watershed modeling approach to streamflow reconstruction from tree-ring records

    International Nuclear Information System (INIS)

    Saito, Laurel; Biondi, Franco; Salas, Jose D; Panorska, Anna K; Kozubowski, Tomasz J

    2008-01-01

    Insight into long-term changes of streamflow is critical for addressing implications of global warming for sustainable water management. To date, dendrohydrologists have employed sophisticated regression techniques to extend runoff records, but this empirical approach cannot directly test the influence of watershed factors that alter streamflow independently of climate. We designed a mechanistic watershed model to calculate streamflows at annual timescales using as few inputs as possible. The model was calibrated for upper reaches of the Walker River, which straddles the boundary between the Sierra Nevada of California and the Great Basin of Nevada. Even though the model incorporated simplified relationships between precipitation and other components of the hydrologic cycle, it predicted water year streamflows with correlations of 0.87 when appropriate precipitation values were used

  11. IOD and ENSO impacts on the extreme stream-flows of Citarum river in Indonesia

    Energy Technology Data Exchange (ETDEWEB)

    Sahu, Netrananda; Yamashiki, Yosuke; Takara, Kaoru [Kyoto University, Disaster Prevention Research Institute, Innovative Disaster Prevention Technology and Policy Research Laboratory, Gokasho, Uji City, Kyoto (Japan); Behera, Swadhin K. [JAMSTEC, Research Institute for Global Change, Yokohama, Kanagawa (Japan); JAMSTEC, Application Laboratory, Yokohama (Japan); Yamagata, Toshio [University of Tokyo, School of Science, Bunkyo-ku, Tokyo (Japan); JAMSTEC, Application Laboratory, Yokohama (Japan)

    2012-10-15

    Extreme stream-flow events of Citarum River are derived from the daily stream-flows at the Nanjung gauge station. Those events are identified based on their persistently extreme flows for 6 or more days during boreal fall when the seasonal mean stream-flow starts peaking-up from the lowest seasonal flows of June-August. Most of the extreme events of high-streamflows were related to La Nina conditions of tropical Pacific. A few of them were also associated with the negative phases of IOD and the newly identified El Nino Modoki. Unlike the cases of extreme high streamflows, extreme low streamflow events are seen to be associated with the positive IODs. Nevertheless, it was also found that the low-stream-flow events related to positive IOD events were also associated with El Nino events except for one independent event of 1977. Because the occurrence season coincides the peak season of IOD, not only the picked extreme events are seen to fall under the IOD seasons but also there exists a statistically significant correlation of 0.51 between the seasonal IOD index and the seasonal streamflows. There also exists a significant lag correlation when IOD of June-August season leads the streamflows of September-November. A significant but lower correlation coefficient (0.39) is also found between the seasonal streamflow and El Nino for September-November season only. (orig.)

  12. H01271: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H03775: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H04095: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H03977: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. L01175: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. L00415: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H06410: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H01584: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. D00012: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H01633: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H01782: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. D00018: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H02711: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H02501: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H04578: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H06357: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H03641: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H02012: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H02465: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H04003: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H04738: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H04513: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H00232: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H00380: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H01186: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H06627: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H04165: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H04004: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H00412: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H02259: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H02679: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H03182: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H04575: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H04562: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. L01365: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H02455: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H01769: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H02918: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H03567: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. L00912: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. L00549: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. L01953: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. L00841: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. L02207: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. L00117: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. L01655: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. L00459: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. L01616: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. L00074: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. L00196: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. L00564: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. L01745: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. L02183: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. L01818: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. L01575: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. L01715: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. L02211: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. L00175: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. L01137: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. L00317: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H01893: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H04566: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H00450: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H00655: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H02707: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H09482: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H02575: NOS Hydrographic Survey

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    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H02462: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H01628: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H03978: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. L02164: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H04296: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. L00252: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H02152: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H01824: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. L02087: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H02038: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. L01055: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H00903: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H02032: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H01668: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H00678: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H01980: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H01950: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H02112: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H04565: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H02195: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H02194: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H02533: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H02528: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H02991: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H02989: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H02994: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H02059: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H03392: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H03929: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. D00024: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H02184: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H02471: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H00748: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H00698: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H00497: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H03123: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H02872: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H02252: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H01705: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. F00018: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. L00259: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H04022: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H03987: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H00263: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H03687: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H01717: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H02141: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00364: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H00195: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H00149: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H00328: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H02225: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H06289: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H00889: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H04368: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H04851: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H04030: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H03381: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H00435: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H03928: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H00862: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H02770: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H02769: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. D00011: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H00407: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H03797: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H04687: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00509: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H04823: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H00305: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H02573: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H04663: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H01837: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H01809: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H03407: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H03259: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. D00086: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H00246: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H13072: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H01341: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H02494: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H02992: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H00861: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H07558: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H02762: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H07497: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H05038: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00674: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H12885: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. W00144: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. W00139: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H00394: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H02830: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H01594: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H02019: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. W00133: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H07491: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. D00060: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. W00134: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H00556: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H00803: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H03999: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H00730: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H04821: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H04048: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H03726: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. L00330: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00982: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H00211: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H01724: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. L00340: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H07308: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H05019: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. L02326: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H02754: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H00339: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H01935: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H03023: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H02911: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H06480: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H00214: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H02009: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H01897: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H00737: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. L01227: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. L00572: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H03562: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H02603: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H03408: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H03383: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H00236: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H00554: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H02278: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H00615: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H03783: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H00939: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H00147: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H02224: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H01745: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H02592: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H04806: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H01000: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H04803: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H04804: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H00390: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H00785: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H00786: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00481: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. L00469: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H00891: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H00951: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H02336: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H00648: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H00186: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H02348: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H03782: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H02084: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H04329: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H00162: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H02309: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H02622: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H04837: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H00843: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. L00138: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H02574: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H03201: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H02487: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. L00315: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. L00089: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H00177: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. L01304: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H04857: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H01635: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H00271: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H00270: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H00875: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H02739: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H07677: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H04137: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. F00026: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H03689: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H00368: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H04826: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H00868: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. L02094: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H02799: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H03671: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H06168: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H04482: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. L00536: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H00219: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. L00389: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. L00941: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H03709: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H12971: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H02120: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H00910: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H01978: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H00697: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H00870: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H07759: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. L01716: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. L00585: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H00197: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H02466: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. L00971: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H00611: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H03008: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H07524: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H00703: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H03066: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H02988: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. L01021: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. L00136: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H00670: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H00596: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H03460: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. L00253: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. L01208: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H01435: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. W00132: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. L00440: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. W00196: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. L00320: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H00892: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H05987: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H01703: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00625: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H02006: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H04595: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H03915: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. NOAA's Hydrographic Surveys and Reports

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data to support the compilation of nautical charts and...

  11. H00926: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H03522: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H01561: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H01552: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H04766: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H00277: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H04468: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H04323: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H00306: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H00894: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. H04322: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H04313: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H00399: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H00470: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H02917: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00355: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. F00006: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H00457: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. D00017: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H06749: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H00685: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H03583: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H04306: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H00642: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. H04437: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. H04610: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. H01701: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H00769: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H05002: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. L01273: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. L00139: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. H02984: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. L00171: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H03433: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H02923: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H01576: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H01617: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H03991: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H01898: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. H02771: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H00161: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H01674: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H03656: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. D00043: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. D00047: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. D00037: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. D00045: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. D00050: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. D00046: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. D00049: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  1. D00041: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  2. D00040: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  3. H02544: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  4. H01715: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  5. H03250: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  6. H00415: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  7. H00416: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  8. H00423: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  9. H01679: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  10. L00226: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  11. H02623: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  12. H00548: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  13. H07209: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  14. H02621: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  15. L00381: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  16. D00222: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  17. L00384: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  18. H00291: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  19. H02327: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...

  20. H01829: NOS Hydrographic Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe...