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At least 91 records · Page 5Linked to original sources
USGS2014

Water-quality variability and constituent transport and processes in streams of Johnson County, Kansas, using continuous monitoring and regression models, 2003-11

The population of Johnson County, Kansas increased by about 24 percent between 2000 and 2012, making it one of the most rapidly developing areas of Kansas. The U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began a comprehensive study of Johnson County streams in 2002 to evaluate and monitor changes in stream quality. The purpose of this report is to describe water-quality variability and constituent transport for streams representing the five largest watersheds in Johnson County, Kansas during 2003 through 2011. The watersheds ranged in urban development from 98.3 percent urban (Indian Creek) to 16.7 percent urban (Kill Creek). Water-quality conditions are quantified among the watersheds of similar size (50.1 square miles to 65.7 square miles) using continuous, in-stream measurements, and using regression models developed from continuous and discrete data. These data are used to quantify variability in concentrations and loads during changing streamflow and seasonal conditions, describe differences among sites, and assess water quality relative to water-quality standards and stream management goals. Water quality varied relative to streamflow conditions, urbanization in the upstream watershed, and contributions from wastewater treatment facilities and storm runoff. Generally, as percent impervious surface (a measure of urbanization) increased, streamflow yield increased. Water temperature of Indian Creek, the most urban site which is also downstream from wastewater facility discharges, was higher than the other sites about 50 percent of the time, particularly during winter months. Dissolved oxygen concentrations were less than the Kansas Department of Health and Environment minimum criterion of 5 milligrams per liter about 15 percent of the time at the Indian Creek site. Dissolved oxygen concentrations were less than the criterion about 10 percent of the time at the rural Blue River and Kill Creek sites, and less than 5 percent of the time at the other sites. Low dissolved oxygen at all sites generally coincided with lowest streamflow and warmer water temperatures. Hourly dissolved oxygen concentrations less than 5 milligrams per liter were measured at all sites every year, indicating that even under normal climate conditions in non-urban watersheds such as Kill Creek, dissolved oxygen concentrations may not meet State aquatic-life criterion. Specific conductance was nearly always highest in Indian and Mill Creeks, which were the most urban streams with the largest upstream discharges from wastewater treatment facilities. The largest chloride concentrations and variability were recorded at urban sites and during winter. Each winter during the study period, chloride concentrations in the most urban site, Indian Creek, exceeded the U.S. Environmental Protection Agency-recommended criterion of 230 milligrams per liter for at least 10 consecutive days. The U.S. Environmental Protection Agency-recommended ecoregion criterion for turbidity was exceeded 30 (Indian Creek) to 50 (Blue River) percent of the time. The highest average annual streamflow-weighted suspendedsediment concentration during the study period was in Mill Creek, which has undergone rapid development that likely contributed to higher sediment concentrations. One of the largest suspended-sediment load events in Indian Creek was recorded in early May 2007 when about 25 percent of the total annual sediment load was transported during a period of about 2.25 days. A simultaneous load event was recorded in Kill Creek, when about 75 percent of the total annual sediment load was transported. Sediment yields generally increased as percent impervious surface increased. Computed hourly total nitrogen and total phosphorus concentrations and yields and streamflow-weighted concentrations generally were largest in Indian and Mill Creeks. Annual percent contribution of total nitrogen in the Blue River from wastewater treatment facility discharges ranged from 19 percent in 2010 to 60 percent in 2006. Annual percent contribution of total nitrogen in Indian Creek from wastewater treatment facility discharges ranged from 35 percent in 2010 to 93 percent in 2006. The largest percent nutrient contributions from wastewater discharges coincided with the smallest annual precipitation and streamflow volume, resulting in less contribution originating from runoff. Fecal indicator bacteria Escherichia coli density at the urban Indian Creek site was usually the largest of the five monitoring sites, with an annual median density that consistently exceeded the State primary contact criterion value but was less than the secondary contact criterion. Less than 1 percent of the total annual bacteria load in the Blue River and Indian Creek originated from wastewater discharges, except during 2006 when about 6 percent of the Indian Creek load originated from wastewater. Continuous water-quality monitoring provides a foundation for comprehensive evaluation and understanding of variability and loading characteristics in streams in Johnson County. Because several directly measured parameters are strongly correlated with particular constituents of interest, regression models provide a valuable tool for evaluating variability and loading on the basis of computed continuous data. Continuous data are particularly useful for characterizing nonpoint-source contributions from stormwater runoff. Transmission of continuous data in real-time makes it possible to rapidly detect and respond to potential environmental concerns. As monitoring technologies continue to improve, so does the ability to monitor additional constituents of interest, with smaller measurement error, and at lower operational cost. Continuous water-quality data including model information and computed concentrations and loads during the study period are available at http://nrtwq.usgs.gov/ks/ .

Kansas↗
USGS2020

Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas

The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, assessed statistical relations between hydraulic properties of streams at approximate bankfull conditions for different ecological regions (ecoregions) in Texas. Data from more than 103,000 records of measured discharge and ancillary hydraulic properties were assembled from summaries of discharge measurements for 424 U.S. Geological Survey streamgages in Texas. The data were subsequently subsetted at each streamgage for a streamgage-specific discharge interval centered on the estimated median annual peak discharge (0.5 annual exceedance probability) obtained from previously published regional regression equations in Texas in conjunction with the streamgage-specific sample median annual peak discharge for the period of record for each streamgage. Discharge measurements at gaged locations representing bankfull conditions (approximated from a discharge interval centered on the estimated median annual peak discharge at a given site) and associated watershed properties were subjected to rigorous statistical analysis. For most discharge measurements (where discharge is symbolically represented as Q ), the following hydraulic properties are available: cross-section area ( A ), water-surface top width ( B ), and reported mean velocity ( V ). Statewide summary statistics were computed by using these four hydraulic properties ( Q , A , B , and V ) and the following five watershed properties: (1) watershed area (contributing drainage area), (2) a multiple of main-channel slope (1,000 times main-channel slope), (3) mean annual precipitation, (4) drainage density, and (5) sinuosity ratio. From the initial set of 424 streamgages, summary statistics were computed for 372 selected streamgages in Texas and constitute the subsetted measurements dataset described in this report. Eight of the 10 ecoregions in Texas are represented in the statewide summary statistics. The resulting statistical relations, expressed as regression equations, can be used to estimate cross-section area, water-surface top width, discharge, and mean velocity of streams in different Texas ecoregions, at approximate bankfull conditions. In the regression equations, watershed properties were the independent variables for applicable watersheds, and predictions from the equations might be useful for estimating the four hydraulic properties at ungaged or unmonitored locations from selected characteristics measured at both the ungaged locations and gaged locations. Four regression equations to estimate the four hydraulic properties were identified as the preferred equations from this study. The four preferred equations use watershed area, mean annual precipitation, and aggregated ecoregion (treated as a categorical variable) to estimate the hydraulic properties, and justification is provided for this preference. For the four equations, the proportions of variance explained by the regression equations as measured by Nash-Sutcliffe efficiency are about 71 percent for cross-section area, 36 percent for top width, 76 percent for discharge, and 25 percent for mean velocity. Residual standard error (RSEs) of the regression equations are 0.252 log10 square feet for cross-section area, 0.319 log10 feet for top width, 0.247 log10 cubic feet per second for discharge, and 0.190 log10 feet per second for mean velocity, and the corresponding standard deviations of response are 0.465 log10 square feet, 0.397 log10 feet, 0.507 log10 cubic feet per second, and 0.220 log10 feet per second, respectively. The residual standard errors are less than the standard deviations as anticipated but show that the uncertainty reduction (percent change) for cross-section area is about −46 percent, about −20 percent for top width, about −51 percent for discharge, and about −14 percent for mean velocity.

Texas↗
USGS2013

Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China

Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.

Dongjiang↗
USGS2024

Estimating biogeochemical rates using a computationally efficient Lagrangian approach

Nutrient concentrations in many estuaries have increased over the past century due to increases in wastewater discharge and increased agricultural intensity, contributing to multiple environmental problems. Numerous biogeochemical and physical processes in estuaries influence nutrient concentrations during transport, resulting in complex spatial and temporal variability and challenges identifying predominant processes and their rates. Mechanistic models which require these rates to quantify biogeochemical processes become complex and difficult to calibrate as the number of processes and parameters grows, owing to the high dimensionality of the parameter space and the computational cost of simultaneously modeling the transport and transformations of constituents. We developed a modeling approach that decouples transport from transformations, enabling fast, data-driven exploration of the parameter space. The approach extracted information including water age, cumulative exposure to specific habitats, and mean water depth exposure from a hydrodynamic model. Using this information, a biogeochemical model was implemented to predict ammonium and nitrate concentrations in a Lagrangian frame. The model performed each simulation in milliseconds on a laptop computer, allowing the fitting of rate parameters for key transformations by optimization. The optimization used fixed station nitrate observations and the model was then validated against high-resolution mapping observations of ammonium and nitrate. The results suggest that the observed spatial and temporal variation can be largely represented with five transformation processes and their associated rates. Dissolved inorganic nitrogen (DIN) losses occurred only in shallow vegetated areas in the model, highlighting that biogeochemical processes in these areas should be included in DIN models.

California↗
USGS2003

Flood-frequency prediction methods for unregulated streams of Tennessee, 2000

Up-to-date flood-frequency prediction methods for unregulated, ungaged rivers and streams of Tennessee have been developed. Prediction methods include the regional-regression method and the newer region-of-influence method. The prediction methods were developed using stream-gage records from unregulated streams draining basins having from 1 percent to about 30 percent total impervious area. These methods, however, should not be used in heavily developed or storm-sewered basins with impervious areas greater than 10 percent. The methods can be used to estimate 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence-interval floods of most unregulated rural streams in Tennessee. A computer application was developed that automates the calculation of flood frequency for unregulated, ungaged rivers and streams of Tennessee. Regional-regression equations were derived by using both single-variable and multivariable regional-regression analysis. Contributing drainage area is the explanatory variable used in the single-variable equations. Contributing drainage area, main-channel slope, and a climate factor are the explanatory variables used in the multivariable equations. Deleted-residual standard error for the single-variable equations ranged from 32 to 65 percent. Deleted-residual standard error for the multivariable equations ranged from 31 to 63 percent. These equations are included in the computer application to allow easy comparison of results produced by the different methods. The region-of-influence method calculates multivariable regression equations for each ungaged site and recurrence interval using basin characteristics from 60 similar sites selected from the study area. Explanatory variables that may be used in regression equations computed by the region-of-influence method include contributing drainage area, main-channel slope, a climate factor, and a physiographic-region factor. Deleted-residual standard error for the region-of-influence method tended to be only slightly smaller than those for the regional-regression method and ranged from 27 to 62 percent.

Tennessee↗
USGS2010

Implementation of the Next Generation Attenuation (NGA) ground-motion prediction equations in Fortran and R

This report presents two methods for implementing the earthquake ground-motion prediction equations released in 2008 as part of the Next Generation Attenuation of Ground Motions (NGA-West, or NGA) project coordinated by the Pacific Earthquake Engineering Research Center (PEER). These models were developed for predicting ground-motion parameters for shallow crustal earthquakes in active tectonic regions (such as California). Of the five ground-motion prediction equations (GMPEs) developed during the NGA project, four models are implemented: the GMPEs of Abrahamson and Silva (2008), Boore and Atkinson (2008), Campbell and Bozorgnia (2008), and Chiou and Youngs (2008a); these models are abbreviated as AS08, BA08, CB08, and CY08, respectively. Since site response is widely recognized as an important influence of ground motions, engineering applications typically require that such effects be modeled. The model of Idriss (2008) is not implemented in our programs because it does not explicitly include site response, whereas the other four models include site response and use the same variable to describe the site condition (VS30). We do not intend to discourage the use of the Idriss (2008) model, but we have chosen to implement the other four NGA models in our programs for those users who require ground-motion estimates for various site conditions. We have implemented the NGA models by using two separate programming languages: Fortran and R (R Development Core Team, 2010). Fortran, a compiled programming language, has been used in the scientific community for decades. R is an object-oriented language and environment for statistical computing that is gaining popularity in the statistical and scientific community. Derived from the S language and environment developed at Bell Laboratories, R is an open-source language that is freely available at http://www.r-project.org/ (last accessed 11 January 2011). In R, the functions for computing the NGA equations can be loaded as an add-on user-contributed code, which is referred to as a ?package? in R. The details of the nga package (Kaklamanos and Thompson, 2010) are presented in this report. In addition, differences between the R and Fortran implementations will be discussed later in this report. The NGA models have established a new baseline for seismic hazard assessments, and they have been incorporated into the most recent national seismic hazard maps published by the U.S. Geological Survey (Petersen and others, 2008). However, many of the new models are significantly more complicated than previous GMPEs and, therefore, require a substantial investment of time to implement and validate. We hope that the scientific and engineering communities find our implementations to be useful in research and practice. Our implementations may be considered as an alternate to the Microsoft Excel spreadsheet implementation available on the PEER NGA project Web site (http://peer.berkeley.edu/ngawest/, last accessed 11 January 2011). The implementations in Fortran and R are more appropriate for performing batch calculations than the implementation in Microsoft Excel. Spreadsheets and Fortran code for some of the individual models also are available on the PEER NGA project Web site; our programs implement the four GMPEs simultaneously. Our programs give the same results as the programs on the PEER NGA Web site, but we offer some additional flexibility of input, additional methods of estimating unknown input parameters, and additional options for output. Although these programs have been used by the U.S. Geological Survey (USGS), Tufts University, and others, no warranty, expressed or implied, is made by Tufts or the USGS as to the accuracy or functioning of the programs and related material, nor shall the fact of distribution constitute any such warranty, and no responsibility is assumed by Tufts or the USGS in connection therewith.

Open-File Report↗
USGS1975

Chemical analyses of ground water for saline-water resources studies in Texas Coastal Plain stored in National Water Data Storage and Retrieval System

Chemical analyses of 4,269 water samples from wells in 66 counties in Texas have been processed into the National Water Data Storage and Retrieval System by the Gulf Coast Hydrogeology Project of the U. S. Geological Survey. More than 65,000 chemical analyses of saline waters produced by oil test and production wells have been contributed to the project by major oil companies. The computerized tabulation and the computer-drawn map of the locations of sampling sites are the initial release of oil company, State, and Federal data in Texas Coastal Plain from the data bank.

Open-File Report↗
USGS2007

Estimated water use and availability in the Pawtuxet and Quinebaug River basins, Rhode Island, 1995-99

Water availability became a concern in Rhode Island during a drought in 1999, and an investigation was needed to assess demands on the hydrologic system from withdrawals during periods of little to no precipitation. The low water levels during the drought prompted the U.S. Geological Survey and the Rhode Island Water Resources Board to begin a series of studies on water use and availability in each drainage area in Rhode Island for 1995–99. The study area for this report, which includes the Pawtuxet River Basin in central Rhode Island (231.6 square miles) and the Quinebaug River Basin in western Rhode Island (60.97 square miles), was delineated as the surface-water drainage areas of these basins. During the study period from 1995 through 1999, two major water suppliers withdrew an average of 71.86 million gallons per day (Mgal/d) from the Pawtuxet River Basin; of this amount, about 35.98 Mgal/d of potable water were exported to other basins in Rhode Island. The estimated water withdrawals from minor water suppliers were 0.026 Mgal/d in the Pawtuxet River Basin and 0.003 Mgal/d in the Quinebaug River Basin. Total self-supply withdrawals were 2.173 Mgal/d in the Pawtuxet River Basin and 0.360 Mgal/d in the Quinebaug River Basin, which has no public water supply. Total water use averaged 18.07 Mgal/d in the Pawtuxet River Basin and 0.363 Mgal/d in the Quinebaug River Basin. Total return flow in the Pawtuxet River Basin was 30.64 Mgal/d, which included about 12.28 Mgal/d that were imported from other basins in Rhode Island. Total return flow was 0.283 Mgal/d in the Quinebaug River Basin. During times of little to no recharge in the form of precipitation, the surface- and ground-water flows are from storage primarily in the stratified sand and gravel deposits; water also flows through the till deposits, but at a slower rate. The ground water discharging to the streams during times of little to no recharge from precipitation is referred to as base flow. The PART program, a computerized hydrograph-separation application, was used to analyze the data collected at two selected index stream-gaging stations to determine water availability on the basis of the 75th, 50th, and 25th percentiles of the total base flow; the base flow for the 7-day, 10-year low-flow scenario; and the base flow for the Aquatic Base Flow scenario for both stations. The index stream-gaging stations used in the analysis were the Branch River at Forestdale, Rhode Island (period of record 1957–1999) and the Nooseneck River at Nooseneck, Rhode Island (period of record 1964–1980). A regression equation was used to estimate unknown base-flow contributions from sand and gravel deposits at the two stations. The base-flow contributions from sand and gravel deposits and till deposits at the index stations were computed for June, July, August, and September within the periods of record, and divided by the area of each type of surficial deposit at each index station. These months were selected because they define a period when there is usually an increased demand for water and little to no precipitation. The base flows at the stream-gaging station Branch River at Forestdale, Rhode Island were lowest in August at the 75th, 50th, and 25th percentiles (29.67, 21.48, and 13.30 Mgal/d, respectively). The base flows at the stream-gaging station Nooseneck River at Nooseneck, Rhode Island were lowest in September at the 75th percentile (3.551 Mgal/d) and lowest in August at the 50th and 25th percentiles (2.554 and 1.811 Mgal/d). The base flows per unit area for the index stations were multiplied by the areas of sand and gravel and till in the studyarea subbasins to determine the amount of available water for each scenario. The water availability in the Pawtuxet River Basin at the 50th percentile ranged from 126.5 Mgal/d in August to 204.7 Mgal/d in June, and the total gross water availability for the 7-day, 10-year low-flow scenario at the 50th percentile ranged from 112.2 Mgal/d in August to 190.4 Mgal/d in June. The Scituate Reservoir safe yield was 83 Mgal/d in all scenarios. Water availability in the Quinebaug River Basin ranged from 13.94 Mgal/d in August to 30.53 Mgal/d in June at the 50th percentile. The total gross water availability for the 7-day, 10-year low-flow scenario at the 50th percentile ranged from 14.26 Mgal/d in August to 42.69 Mgal/d in June. Because water withdrawals and use are greater during the summer than other times of the year, water availability in June, July, August, and September was compared to water withdrawals in the basin and subbasins. The ratios of water withdrawn to water available were calculated for the 75th, 50th, and 25th percentiles for the subbasins; the closer the ratio is to 1, the closer the withdrawals are to the estimated water available, and the less net water is available. Withdrawals in July were higher than in the other summer months in both basins. In the Pawtuxet River Basin, the ratios were close to 1 in July for the estimated gross yield (from sand and gravel and from till and from the Scituate Reservoir safe yield), 7-day, 10-year low-flow scenario, and Aquatic Base Flow scenario at the 75th percentile and in August for all three scenarios at the 50th and 25th percentiles. In the Quinebaug River Basin, the ratios were close to 1 in August for the estimated gross yield; 7-day, 10-year low-flow scenario; and Aquatic Base Flow scenario. A long-term water budget was calculated for 1941 through 1999 to identify and assess the basin and subbasin inflow and outflows for the Pawtuxet and Quinebaug River Basins. The water withdrawals and return flows used in the budget were from 1995 through 1999. Inflow was assumed to be equal to outflow; total inflows and outflows were 574.9 Mgal/d in the Pawtuxet River Basin and 148.4 Mgal/d in the Quinebaug River Basin. Precipitation and return flow were 95 and 5 percent of the estimated inflows to the Pawtuxet River Basin, respectively. Precipitation was 100 percent of the estimated inflow to the Quinebaug River Basin; return flow was less than 1 percent of the inflow. Evapotranspiration, streamflow, and water withdrawals were 46, 41, and 13 percent, respectively, of the estimated outflows in the Pawtuxet River Basin. Evapotranspiration and streamflow were 49 and 51 percent, respectively, of the estimated outflows in the Quinebaug River Basin. Water withdrawals were less than 1 percent of outflows in the Quinebaug River Basin.

Rhode Island↗
USGS2010

Application of AFINCH as a tool for evaluating the effects of streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the southeast Lake Michigan hydrologic subregion

Bootstrapping techniques employing random subsampling were used with the AFINCH (Analysis of Flows In Networks of CHannels) model to gain insights into the effects of variation in streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the 0405 (Southeast Lake Michigan) hydrologic subregion. AFINCH uses stepwise-regression techniques to estimate monthly water yields from catchments based on geospatial-climate and land-cover data in combination with available streamflow and water-use data. Calculations are performed on a hydrologic-subregion scale for each catchment and stream reach contained in a National Hydrography Dataset Plus (NHDPlus) subregion. Water yields from contributing catchments are multiplied by catchment areas and resulting flow values are accumulated to compute streamflows in stream reaches which are referred to as flow lines. AFINCH imposes constraints on water yields to ensure that observed streamflows are conserved at gaged locations. Data from the 0405 hydrologic subregion (referred to as Southeast Lake Michigan) were used for the analyses. Daily streamflow data were measured in the subregion for 1 or more years at a total of 75 streamflow-gaging stations during the analysis period which spanned water years 1971–2003. The number of streamflow gages in operation each year during the analysis period ranged from 42 to 56 and averaged 47. Six sets (one set for each censoring level), each composed of 30 random subsets of the 75 streamflow gages, were created by censoring (removing) approximately 10, 20, 30, 40, 50, and 75 percent of the streamflow gages (the actual percentage of operating streamflow gages censored for each set varied from year to year, and within the year from subset to subset, but averaged approximately the indicated percentages). Streamflow estimates for six flow lines each were aggregated by censoring level, and results were analyzed to assess (a) how the size and composition of the streamflow-gaging network affected the average apparent errors and variability of the estimated flows and (b) whether results for certain months were more variable than for others. The six flow lines were categorized into one of three types depending upon their network topology and position relative to operating streamflow-gaging stations. Statistical analysis of the model results indicates that (1) less precise (that is, more variable) estimates resulted from smaller streamflow-gaging networks as compared to larger streamflow-gaging networks, (2) precision of AFINCH flow estimates at an ungaged flow line is improved by operation of one or more streamflow gages upstream and (or) downstream in the enclosing basin, (3) no consistent seasonal trend in estimate variability was evident, and (4) flow lines from ungaged basins appeared to exhibit the smallest absolute apparent percent errors (APEs) and smallest changes in average APE as a function of increasing censoring level. The counterintuitive results described in item (4) above likely reflect both the nature of the base-streamflow estimate from which the errors were computed and insensitivity in the average model-derived estimates to changes in the streamflow-gaging-network size and composition. Another analysis demonstrated that errors for flow lines in ungaged basins have the potential to be much larger than indicated by their APEs if measured relative to their true (but unknown) flows. “Missing gage” analyses, based on examination of censoring subset results where the streamflow gage of interest was omitted from the calibration data set, were done to better understand the true error characteristics for ungaged flow lines as a function of network size. Results examined for 2 water years indicated that the probability of computing a monthly streamflow estimate within 10 percent of the true value with AFINCH decreased from greater than 0.9 at about a 10-percent network-censoring level to less than 0.6 as the censoring level approached 75 percent. In addition, estimates for typically dry months tended to be characterized by larger percent errors than typically wetter months.

Indiana, Michigan↗
USGS2012

Sediment transport to and from small impoundments in northeast Kansas, March 2009 through September 2011

The U.S. Geological Survey, in cooperation with the Kansas Water Office, investigated sediment transport to and from three small impoundments (average surface area of 0.1 to 0.8 square miles) in northeast Kansas during March 2009 through September 2011. Streamgages and continuous turbidity sensors were operated upstream and downstream from Atchison County, Banner Creek, and Centralia Lakes to study the effect of varied watershed characteristics and agricultural practices on sediment transport in small watersheds in northeast Kansas. Atchison County Lake is located in a predominantly agricultural basin of row crops, with wide riparian buffers along streams, a substantial amount of tile drainage, and numerous small impoundments (less than 0.05 square miles; hereafter referred to as “ponds”). Banner Creek Lake is a predominantly grassland basin with numerous small ponds located in the watershed, and wide riparian buffers along streams. Centralia Lake is a predominantly agricultural basin of row crops with few ponds, few riparian buffers along streams, and minimal tile drainage. Upstream from Atchison County, Banner Creek, and Centralia Lakes 24, 38, and 32 percent, respectively, of the total load was transported during less than 0.1 percent (approximately 0.9 days) of the time. Despite less streamflow in 2011, larger sediment loads during that year indicate that not all storm events transport the same amount of sediment; larger, extreme storms during the spring may transport much larger sediment loads in small Kansas watersheds. Annual sediment yields were 360, 400, and 970 tons per square mile per year at Atchison County, Banner, and Centralia Lake watersheds, respectively, which were less than estimated yields for this area of Kansas (between 2,000 and 5,000 tons per square mile per year). Although Centralia and Atchison County Lakes had similar percentages of agricultural land use, mean annual sediment yields upstream from Centralia Lake were about 2.7 times those at Atchison County or Banner Creek Lakes. These data indicate larger yields of sediment from watersheds with row crops and those with fewer small ponds, and smaller yields in watersheds which are primarily grassland, or agricultural with substantial tile drainage and riparian buffers along streams. These results also indicated that a cultivated watershed can produce yields similar to those observed under the assumed reference (or natural) condition. Selected small ponds were studied in the Atchison County Lake watershed to characterize the role of small ponds in sediment trapping. Studied ponds trapped about 8 percent of the sediment upstream from the sediment-sampling site. When these results were extrapolated to the other ponds in the watershed, differences in the extent of these ponds was not the primary factor affecting differences in yields among the three watersheds. However, the selected small ponds were both 45 years old at the time of this study, and have reduced capacity because of being filled in with sediments. Additionally, trapping efficiency of these small ponds decreased over five observed storms, indicating that processes that suspended or resuspended sediments in these shallow ponds, such as wind and waves, affected their trapping efficiencies. While small ponds trapped sediments in small storms, they could be a source of sediment in larger or more closely spaced storm events. Channel slope was similar at all three watersheds, 0.40, 0.46, and 0.31 percent at Atchison County, Banner Creek, and Centralia Lake watersheds, respectively. Other factors, such as increased bank and stream erosion, differences in tile drainage, extent of grassland, or riparian buffers, could be the predominant factors affecting sediment yields from these basins. These results show that reference-like sediment yields may be observed in heavily agricultural watersheds through a combination of field-scale management activities and stream channel protection. When computing loads using published erosion rates obtained by single-point survey methodology, streambank contributions from the main stem of Banner Creek are three times more than the sediment load observed by this study at the sediment sampling site at Banner Creek, 2.6 times more than the sediment load observed by this study at the sediment sampling site at Clear Creek (upstream from Atchison County Lake), and are 22 percent of the load observed by this study at the sediment sampling site at Black Vermillion River above Centralia Lake. Comparisons of study sites to similarly sized urban and urbanizing watersheds in Johnson County, Kansas indicated that sediment yields from the Centralia Lake watershed were similar to those in construction-affected watersheds, while much smaller sediment yields in the Atchison County and Banner Creek watersheds were comparable to stable, heavily urbanized watersheds. Comparisons of study sites to larger watersheds upstream from Tuttle Creek Lake indicate the Black Vermillion River watershed continues to have high sediment yields despite 98 percent of sediment from the Centralia watershed (a headwater of the Black Vermillion River) being trapped in Centralia Lake. Estimated trapping efficiencies for the larger watershed lakes indicated that Banner Creek and Centralia Lakes trapped 98 percent of incoming sediment, whereas Atchison County Lake trapped 72 percent of incoming sediment during the 3-year study period.

Kansas↗
USGS2020

Hydrology of Haskell Lake and investigation of a groundwater contamination plume, Lac du Flambeau Reservation, Wisconsin

Haskell Lake is a shallow, 89-acre drainage lake in the headwaters of the Squirrel River, on the Lac du Flambeau Reservation in northern Wisconsin. The lake has long been valued by the Lac du Flambeau Band of Lake Superior Chippewa Indians (LDF Tribe) for abundant wild rice and game fish. In recent decades, however, wild rice has mostly disappeared from the lake and the fishery has declined. A petroleum contamination plume discovered in the 1990s in the shallow aquifer upgradient from the northern end of the lake poses a threat to the ecological health of the lake and the aquifer, which is the sole drinking water source for nearby residents and businesses. Understanding of the lake’s hydrology is important to the LDF Tribe as they seek to restore wild rice and maintain the ecological health of the Haskell Lake/Tower Creek watershed. An improved understanding of lithology in the area of the contamination plume, documentation of a contamination pathway from groundwater in the plume source area to Haskell Lake, and an understanding of the plume extent beneath the lake are needed to advance remediation efforts. Evaluation of the fraction of groundwater discharge that is contaminated relative to the overall lake water budget is desired as a first step towards determining the extent of ecological effects from the plume. A cooperative study between the U.S. Geological Survey and the LDF Tribe was initiated to quantify the lake water budget and the sources of water to the lake, to provide a rough estimate of the maximum quantity of groundwater discharge to the lake that may be contaminated, and to improve the conceptual understanding of the plume extent and subsurface materials in the area of contamination. The results of this study can help inform natural resource management of the Haskell Lake/Tower Creek watershed, including planned wild rice restoration and cleanup of the contaminant plume. During 2016–17, field data on lake and groundwater levels, gradients, fluxes, and subsurface lithology were collected using a variety of techniques that ranged from basic measurement of water levels and streamflows to distributed temperature sensing, vertical temperature profiling, and several shallow geophysical methods. The data were used to inform a MODFLOW–NWT model that simulated the contributing groundwatershed, including the water budget for Haskell Lake and Tower Creek using the Lake, Streamflow-Routing, and Unsaturated Zone-Flow Packages. Particle tracking with the MODFLOW solution (using MODPATH 6) was used to improve understanding of the downgradient extent of the contamination plume, estimate groundwater flux through the plume area, and delineate the groundwater contributing area (groundwatershed) for the lake/creek system. Linear uncertainty estimates for model results were computed during model parameter estimation using the software package PEST++. Results indicate groundwater discharge along the perimeter of Haskell Lake, with groundwater accounting for about 22 (± 11.5) percent of the lake water budget. Field data and particle tracking results indicate discharge of the entire contamination plume to Haskell Lake. Although the exact locations where contaminated groundwater enters the lake are unknown, the downgradient extent of the plume beneath Haskell Lake is likely limited to within about 700 feet from the shore. Groundwater flux through the plume accounts for at most about 1.4 percent of total groundwater discharge to Haskell Lake, or about 0.3 percent of the lake water budget. Most groundwater discharging to Haskell Lake and Tower Creek originates as terrestrial recharge. A lesser amount originates in or passes through neighboring lakes, including Buckskin, Crawling Stone, Broken Bow, Tippecanoe, and Jerms Lakes, as well as several unnamed kettles. The average age of simulated groundwater discharge to the lake is about 20 years.

Wisconsin↗
USGS2004

Acidity and alkalinity in mine drainage: Theoretical considerations

Acidity, net acidity, and net alkalinity are widely used parameters for the characterization of mine drainage, but these terms are not well defined and are often misunderstood. Incorrect interpretation of acidity, alkalinity, and derivative terms can lead to inadequate treatment design or poor regulatory decisions. We briefly explain derivations of theoretical expressions of three types of alkalinities (caustic, phenolphthalein, and total) and acidities (mineral, CO 2 , and total). Theoretically defined total alkalinity is closely analogous to measured alkalinity and presents few practical interpretation problems. Theoretically defined “CO 2- acidity” is closely related to most standard titration methods used for mine drainage with an endpoint pH of 8.3, but it presents numerous interpretation problems, and it is unfortunately named because CO 2 is intentionally driven off during titration of mine-drainage samples. Using the proton condition/massaction approach and employing graphs for visualization, we explore the concept of principal components and how to assign acidity contributions to solution species, including aqueous complexes, commonly found in mine drainage. We define a comprehensive theoretical definition of acidity in mine drainage on the basis of aqueous speciation at the sample pH and the capacity of these species to undergo hydrolysis to pH 8.3. This definition indicates the computed acidity in milligrams per liter (mg L -1 ) as CaCO 3 (based on pH and analytical concentrations of dissolved Fe III , Fe II , Mn, and Al in mg L -1 ): Acidity computed = 50. (10 (3-pH) + 3.C FeIII /55.8 + 2.C FeII /55.8 + 2.C Mn /54.9 + 3.C Al /27.0) underestimates contributions from HSO 4 - and H + , but overestimates the acidity due to Fe 3+ . These errors tend to approximately cancel each other. We demonstrate that “net alkalinity” is a valid mathematical construction based on theoretical definitions of alkalinity and acidity. We demonstrate that, for most mine-drainage solutions, a useful net alkalinity value can be derived from: 1) alkalinity and acidity values based on aqueous speciation, 2) measured alkalinity - computed acidity, or 3) taking the negative of the value obtained in a standard method “hot peroxide” acidity titration, provided that labs report negative values . We recommend the third approach; i.e., Net alkalinity = - Hot Acidity.

Conference Paper↗
USGS2017

Characterization of sediment transport upstream and downstream from Lake Emory on the Little Tennessee River near Franklin, North Carolina, 2014–15

Federal, State, and local agencies and organizations have expressed concerns regarding the detrimental effects of excessive sediment transport on aquatic resources and endangered species populations in the upper Little Tennessee River and some of its tributaries. In addition, the storage volume of Lake Emory, which is necessary for flood control and power generation, has been depleted by sediment deposition. To help address these concerns, a 2-year study was conducted in the upper Little Tennessee River Basin to characterize the ambient suspended-sediment concentrations and suspended-sediment loads upstream and downstream from Lake Emory in Franklin, North Carolina. The study was conducted by the U.S. Geological Survey in cooperation with Duke Energy. Suspended-sediment samples were collected periodically, and time series of stage and turbidity data were measured from December 2013 to January 2016 upstream and downstream from Lake Emory. The stage data were used to compute time-series streamflow. Suspended-sediment samples, along with time-series streamflow and turbidity data, were used to develop regression models that were used to estimate time-series suspended-sediment concentrations for the 2014 and 2015 calendar years. These concentrations, along with streamflow data, were used to compute suspended-sediment loads. Selected suspended-sediment samples were collected for analysis of particle-size distribution, with emphasis on high-flow events. Bed-load samples were also collected upstream from Lake Emory. The estimated annual suspended-sediment loads (yields) for the upstream site for the 2014 and 2015 calendar years were 27,000 short tons (92 short tons per square mile) and 63,300 short tons (215 short tons per square mile), respectively. The annual suspended-sediment loads (yields) for the downstream site for 2014 and 2015 were 24,200 short tons (75 short tons per square mile) and 94,300 short tons (292 short tons per square mile), respectively. Overall, the suspended-sediment load at the downstream site was about 28,300 short tons greater than the upstream site over the study period. As expected, high-flow events (the top 5 percent of daily mean flows) accounted for the majority of the sediment load; 80 percent at the upstream site and 90 percent at the downstream site. A similar relation between turbidity (the top 5 percent of daily mean turbidity) and high loads was also noted. In general, when instantaneous streamflows at the upstream site exceeded 5,000 cubic feet per second, increased daily loads were computed at the downstream site. During low to moderate flows, estimated suspended-sediment loads were lower at the downstream site when compared to the upstream site, which suggests that sediment deposition may be occurring in the intervening reach during those conditions. During the high-flow events, the estimated suspended-sediment loads were higher at the downstream site; however, it is impossible to say with certainty whether the increase in loading was due to scouring of lake sediment, contributions from the additional source area, model error, or a combination of one or more of these factors. The computed loads for a one-week period (December 24–31, 2015), during which the two largest high-flow events of the study period occurred, were approximately 52 percent of the 2015 annual sediment load (36 percent of 2-year load) at the upstream site and approximately 72 percent of the 2015 annual sediment load (57 percent of 2-year load) at the downstream site. Six bedload samples were collected during three events; two high-flow events and one base-flow event. The contribution of bedload to the total sediment load was determined to be insignificant for sampled flows. In general, streamflows for long-term streamgages in the study area were below normal for the majority of the study period; however, flows during the last 3 months of the study period were above normal, including the extreme events during the last week of the study period.

North Carolina↗
USGS2016

Identifying and preserving high-water mark data

High-water marks provide valuable data for understanding recent and historical flood events. The proper collection and recording of high-water mark data from perishable and preserved evidence informs flood assessments, research, and water resource management. Given the high cost of flooding in developed areas, experienced hydrographers, using the best available techniques, can contribute high-quality data toward efforts such as public education of flood risk, flood inundation mapping, flood frequency computations, indirect streamflow measurement, and hazard assessments. This manual presents guidance for skilled high-water mark identification, including marks left behind in natural and man-made environments by tranquil and rapid flowing water. This manual also presents pitfalls and challenges associated with various types of flood evidence that help hydrographers identify the best high-water marks and assess the uncertainty associated with a given mark. Proficient high-water mark data collection contributes to better understanding of the flooding process and reduces risk through greater ability to estimate flood probability. The U.S. Geological Survey, operating the Nation’s premier water data collection network, encourages readers of this manual to familiarize themselves with the art and science of high-water mark collection. The U.S. Geological survey maintains a national database at http://water.usgs.gov/floods/FEV/ that includes high-water mark information for many flood events, and local U.S. Geological Survey Water Science Centers can provide information to interested readers about participation in data collection and flood documentation efforts as volunteers or observers.

Techniques and Methods↗
USGS2004

Estimates of flow duration, mean flow, and peak-discharge frequency values for Kansas stream locations

Streamflow statistics of flow duration and peak-discharge frequency were estimated for 4,771 individual locations on streams listed on the 1999 Kansas Surface Water Register. These statistics included the flow-duration values of 90, 75, 50, 25, and 10 percent, as well as the mean flow value. Peak-discharge frequency values were estimated for the 2-, 5-, 10-, 25-, 50-, and 100-year floods. Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating flow-duration values of 90, 75, 50, 25, and 10 percent and the mean flow for uncontrolled flow stream locations. The contributing-drainage areas of 149 U.S. Geological Survey streamflow-gaging stations in Kansas and parts of surrounding States that had flow uncontrolled by Federal reservoirs and used in the regression analyses ranged from 2.06 to 12,004 square miles. Logarithmic transformations of climatic and basin data were performed to yield the best linear relation for developing equations to compute flow durations and mean flow. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were contributing-drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. The analyses yielded a model standard error of prediction range of 0.43 logarithmic units for the 90-percent duration analysis to 0.15 logarithmic units for the 10-percent duration analysis. The model standard error of prediction was 0.14 logarithmic units for the mean flow. Regression equations used to estimate peak-discharge frequency values were obtained from a previous report, and estimates for the 2-, 5-, 10-, 25-, 50-, and 100-year floods were determined for this report. The regression equations and an interpolation procedure were used to compute flow durations, mean flow, and estimates of peak-discharge frequency for locations along uncontrolled flow streams on the 1999 Kansas Surface Water Register. Flow durations, mean flow, and peak-discharge frequency values determined at available gaging stations were used to interpolate the regression-estimated flows for the stream locations where available. Streamflow statistics for locations that had uncontrolled flow were interpolated using data from gaging stations weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled reaches of Kansas streams, the streamflow statistics were interpolated between gaging stations using only gaged data weighted by drainage area.

Kansas↗
USGS2011

Improvement in precipitation-runoff model simulations by recalibration with basin-specific data, and subsequent model applications, Onondaga Lake Basin, Onondaga County, New York

Water-resource managers in Onondaga County, New York, are faced with the challenge of improving the water quality of Onondaga Lake, which has the distinction of being one of the most contaminated lakes in the United States. To assist in this endeavor, during 2003-07 the U.S. Geological Survey (USGS), in cooperation with the Onondaga Lake Partnership, developed a precipitation-runoff model of the 285-square-mile Onondaga Lake Basin with the computer program Hydrological Simulation Program-Fortran (HSPF). The model was intended to provide a tool whereby the processes responsible for the generation of loads of sediment and nutrients that are transported to Onondaga Lake could be better understood. This objective was only partly attained because data for calibration of the model were available from monitoring sites only at or near the mouths of the major tributaries to Onondaga Lake; no calibration data from headwater subbasins, where the loads originated, were available. To address this limitation and thereby decrease the uncertainty in the simulated results that were associated with headwater processes, the USGS conducted a 3-year (2005-08) basinwide study to assess the quality of surface water in the Onondaga Lake Basin. The study quantified the relative contributions of nonpoint sources associated with the major land uses and land covers in the basin and also monitored known sources and presumed sinks of sediment and nutrient loads, which previously had not been evaluated. The use of the newly acquired data to recalibrate the HSPF model resulted in improvements in the simulation of processes in the headwater subbasins, including suspended-sediment, orthophosphate, and phosphorus generation and transport. Simulation of streamflows in small subbasins was improved by adjusting model parameter values to match base flows, storm peaks, and storm recessions more precisely than had been done with the original model. Simulated recessional and low flows were either increased or decreased as appropriate for a given stream, and simulated peak flows generally were lowered in the revised model. The use of suspended-sediment concentrations rather than concentrations of the surrogate constituent, total suspended solids, resulted in increases in the simulated low-flow sediment concentrations and, in most cases, decreases in the simulated peak-flow sediment concentrations. Simulated orthophosphate concentrations in base flows generally increased but decreased for peak flows in selected headwater subbasins in the revised model. Compared with the original model, phosphorus concentrations simulated by the revised model were comparable in forested subbasins, generally decreased in developed and wetland-dominated subbasins, and increased in agricultural subbasins. A final revision to the model was made by the addition of the simulation of chloride (salt) concentrations in the Onondaga Creek Basin to help water-resource managers better understand the relative contributions of salt from multiple sources in this particular tributary. The calibrated revised model was used to (1) compute loading rates for the various land types that were simulated in the model, (2) conduct a watershed-management analysis that estimated the portion of the total load that was likely to be transported to Onondaga Lake from each of the modeled subbasins, (3) compute and assess chloride loads to Onondaga Lake from the Onondaga Creek Basin, and (4) simulate precolonization (forested) conditions in the basin to estimate the probable minimum phosphorus loads to the lake.

Onondaga, New York↗
USGS2013

2D IR spectra of cyanide in water investigated by molecular dynamics simulations

Using classical molecular dynamics simulations, the 2D infrared (IR) spectroscopy of CN − solvated in D 2 O is investigated. Depending on the force field parametrizations, most of which are based on multipolar interactions for the CN − molecule, the frequency-frequency correlation function and observables computed from it differ. Most notably, models based on multipoles for CN − and TIP3P for water yield quantitatively correct results when compared with experiments. Furthermore, the recent finding that T 1 times are sensitive to the van der Waals ranges on the CN − is confirmed in the present study. For the linear IR spectrum, the best model reproduces the full widths at half maximum almost quantitatively (13.0 cm −1 vs. 14.9 cm −1 ) if the rotational contribution to the linewidth is included. Without the rotational contribution, the lines are too narrow by about a factor of two, which agrees with Raman and IR experiments. The computed and experimental tilt angles (or nodal slopes) α as a function of the 2D IR waiting time compare favorably with the measured ones and the frequency fluctuation correlation function is invariably found to contain three time scales: a sub-ps, 1 ps, and one on the 10-ps time scale. These time scales are discussed in terms of the structural dynamics of the surrounding solvent and it is found that the longest time scale (≈10 ps) most likely corresponds to solvent exchange between the first and second solvation shell, in agreement with interpretations from nuclear magnetic resonance measurements.

Journal of Chemical Physics↗
USGS1980

Effective and bankfull discharges of streams in the Yampa River basin, Colorado and Wyoming

The effective discharge is defined as the increment of discharge that transports the largest fraction of the annual sediment load over a period of years. Increments of the average annual total sediment load transported by various discharges were calculated by the flow-duration, sediment-transport-curve method for 15 gaging stations in the Yampa River basin of Colorado and Wyoming. A total sediment-transport curve was constructed for each gaging station by adding measured instantaneous suspended-sediment discharges to bedload-sediment discharges computed by the Meyer-Peter and Mueller relation. The streamflow durations were compiled from the respective gaging-station records. The quantity of sediment transported by discharges having various frequencies may be computed by combining these two relations. The 15 gaging stations had diverse hydraulic and sediment characteristics. Contributing drainage area ranged from 51.8 to 9,960 km 2 , and mean-annual discharge ranged from 0.040 to 43.9 m 3 /s. The median diameter of bed material ranged from 0.4 to 86 mm. Mean-annual sediment load from the drainage basins studied ranged from 500 to 1.3·10 6 metric tons per year. The effective discharges at the 15 gaging stations were equaled or exceeded on the average of between 1.5 days per year (0.4% of the time) and 11 days per year (3.0% of the time). The recurrence interval of the effective discharges ranged from 1.18 to 3.26 yr. on the annual flood series. To compare the effective discharge with the bankfull discharge, cross-sections were surveyed in a self-formed reach of the channel in the vicinity of each gaging station. The bankfull discharge was defined as the discharge which filled the channel to the level of the floodplain. At all gaging stations, the effective discharge and the bankfull discharge were nearly equal. Thus, the stream channels appear to be adjusted to their effective discharge.

Colorado, Wyoming↗