Geology topics

David L. Lorenz

Publications and source records attributed to David L. Lorenz.

At least 19 recordsLinked to original sources

USGS2018

A surrogate regression approach for computing continuous loads for the tributary nutrient and sediment monitoring program on the Great Lakes

Water quality (WQ) in many Great Lake tributaries has been degraded (increased nutrient and sediment concentrations) due to changes in their watersheds, resulting in downstream eutrophication. As part of the Great Lakes Water Quality Agreement, specific goals were established for loading of specific constituents (e.g., phosphorus). In 2010, the Great Lakes Restoration Initiative was launched to identify problem areas, accelerate restoration efforts, and track their progress. In 2011, the U.S. Geological Survey established a monitoring program on 30 tributaries to the lakes, representing ~ 46% of the U.S. draining area and the spectrum of land uses. Discrete measurements of nutrients and suspended sediment, and continuous measurements of flow and WQ surrogates (turbidity, temperature, specific conductance, pH, and dissolved oxygen) are being collected in these tributaries to document their WQ and estimate continuous (5-min) loading. To estimate loadings, two regression models were developed for each constituent for each site: one using continuous flow and a seasonality factor; and one using flow, seasonality, and continuous surrogates. Variables included in the final models for each constituent were chosen from the explanatory variables that worked “best” for all sites. In computing loads, when continuous surrogate data were unavailable for short periods, loads were computed using the flow and seasonality models. Prediction intervals for all loads were calculated using results from both models. These results provide a better understanding of short-term variability and long-term changes in loading affecting the environmental health of the Great Lakes than traditional regression techniques that employ only flow and seasonality parameters.

Great Lake↗

USGS2017

Streamflow distribution maps for the Cannon River drainage basin, southeast Minnesota, and the St. Louis River drainage basin, northeast Minnesota

Streamflow distribution maps for the Cannon River and St. Louis River drainage basins were developed by the U.S. Geological Survey, in cooperation with the Legislative-Citizen Commission on Minnesota Resources, to illustrate relative and cumulative streamflow distributions. The Cannon River was selected to provide baseline data to assess the effects of potential surficial sand mining, and the St. Louis River was selected to determine the effects of ongoing Mesabi Iron Range mining. Each drainage basin (Cannon, St. Louis) was subdivided into nested drainage basins: the Cannon River was subdivided into 152 nested drainage basins, and the St. Louis River was subdivided into 353 nested drainage basins. For each smaller drainage basin, the estimated volumes of groundwater discharge (as base flow) and surface runoff flowing into all surface-water features were displayed under the following conditions: (1) extreme low-flow conditions, comparable to an exceedance-probability quantile of 0.95; (2) low-flow conditions, comparable to an exceedance-probability quantile of 0.90; (3) a median condition, comparable to an exceedance-probability quantile of 0.50; and (4) a high-flow condition, comparable to an exceedance-probability quantile of 0.02. Streamflow distribution maps were developed using flow-duration curve exceedance-probability quantiles in conjunction with Soil-Water-Balance model outputs; both the flow-duration curve and Soil-Water-Balance models were built upon previously published U.S. Geological Survey reports. The selected streamflow distribution maps provide a proactive water management tool for State cooperators by illustrating flow rates during a range of hydraulic conditions. Furthermore, after the nested drainage basins are highlighted in terms of surface-water flows, the streamflows can be evaluated in the context of meeting specific ecological flows under different flow regimes and potentially assist with decisions regarding groundwater and surface-water appropriations. Presented streamflow distribution maps are foundational work intended to support the development of additional streamflow distribution maps that include statistical constraints on the selected flow conditions.

Minnesota↗

USGS2017

Groundwater discharge to the Mississippi River and groundwater balances for the Interstate 94 Corridor surficial aquifer, Clearwater to Elk River, Minnesota, 2012–14

The Interstate 94 Corridor has been identified as 1 of 16 Minnesota groundwater areas of concern because of its limited available groundwater resources. The U.S. Geological Survey, in cooperation with the Minnesota Department of Natural Resources, completed six seasonal and annual groundwater balances for parts of the Interstate 94 Corridor surficial aquifer to better understand its long-term (next several decades) sustainability. A high-precision Mississippi River groundwater discharge measurement of 5.23 cubic feet per second per mile was completed at low-flow conditions to better inform these groundwater balances. The recharge calculation methods RISE program and Soil-Water-Balance model were used to inform the groundwater balances. For the RISE-derived recharge estimates, the range was from 3.30 to 11.91 inches per year; for the SWB-derived recharge estimates, the range was from 5.23 to 17.06 inches per year. Calculated groundwater discharges ranged from 1.45 to 5.06 cubic feet per second per mile, a ratio of 27.7 to 96.4 percent of the measured groundwater discharge. Ratios of groundwater pumping to total recharge ranged from 8.6 to 97.2 percent, with the longer-term groundwater balances ranging from 12.9 to 19 percent. Overall, this study focused on the surficial aquifer system and its interactions with the Mississippi River. During the study period (October 1, 2012, through November 30, 2014), six synoptic measurements, along with continuous groundwater hydrographs, rainfall records, and a compilation of the pertinent irrigation data, establishes the framework for future groundwater modeling efforts.

Minnesota↗

USGS2017

Determining the sources of fine-grained sediment using the Sediment Source Assessment Tool (Sed_SAT)

A sound understanding of sources contributing to instream sediment flux in a watershed is important when developing total maximum daily load (TMDL) management strategies designed to reduce suspended sediment in streams. Sediment fingerprinting and sediment budget approaches are two techniques that, when used jointly, can qualify and quantify the major sources of sediment in a given watershed. The sediment fingerprinting approach uses trace element concentrations from samples in known potential source areas to determine a clear signature of each potential source. A mixing model is then used to determine the relative source contribution to the target suspended sediment samples. The computational steps required to apportion sediment for each target sample are quite involved and time intensive, a problem the Sediment Source Assessment Tool (Sed_SAT) addresses. Sed_SAT is a user-friendly statistical model that guides the user through the necessary steps in order to quantify the relative contributions of sediment sources in a given watershed. The model is written using the statistical software R (R Core Team, 2016b) and utilizes Microsoft Access® as a user interface but requires no prior knowledge of R or Microsoft Access® to successfully run the model successfully. Sed_SAT identifies outliers, corrects for differences in size and organic content in the source samples relative to the target samples, evaluates the conservative behavior of tracers used in fingerprinting by applying a “Bracket Test,” identifies tracers with the highest discriminatory power, and provides robust error analysis through a Monte Carlo simulation following the mixing model. Quantifying sediment source contributions using the sediment fingerprinting approach provides local, State, and Federal land management agencies with important information needed to implement effective strategies to reduce sediment. Sed_SAT is designed to assist these agencies in applying the sediment fingerprinting approach to quantify sediment sources in the sediment TMDL framework.

Open-File Report↗

USGS2017

smwrGraphs—An R package for graphing hydrologic data, version 1.1.2

This report describes an R package called smwrGraphs , which consists of a collection of graphing functions for hydrologic data within R, a programming language and software environment for statistical computing. The functions in the package have been developed by the U.S. Geological Survey to create high-quality graphs for publication or presentation of hydrologic data that meet U.S. Geological Survey graphics guidelines.

Open-File Report↗

USGS2016

Application of dimensionless sediment rating curves to predict suspended-sediment concentrations, bedload, and annual sediment loads for rivers in Minnesota

Consistent and reliable sediment data are needed by Federal, State, and local government agencies responsible for monitoring water quality, planning river restoration, quantifying sediment budgets, and evaluating the effectiveness of sediment reduction strategies. Heightened concerns about excessive sediment in rivers and the challenge to reduce costs and eliminate data gaps has guided Federal and State interests in pursuing alternative methods for measuring suspended and bedload sediment. Simple and dependable data collection and estimation techniques are needed to generate hydraulic and water-quality information for areas where data are unavailable or difficult to collect. The U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency and the Minnesota Department of Natural Resources, completed a study to evaluate the use of dimensionless sediment rating curves (DSRCs) to accurately predict suspended-sediment concentrations (SSCs), bedload, and annual sediment loads for selected rivers and streams in Minnesota based on data collected during 2007 through 2013. This study included the application of DSRC models developed for a small group of streams located in the San Juan River Basin near Pagosa Springs in southwestern Colorado to rivers in Minnesota. Regionally based DSRC models for Minnesota also were developed and compared to DSRC models from Pagosa Springs, Colorado, to evaluate which model provided more accurate predictions of SSCs and bedload in Minnesota. Multiple measures of goodness-of-fit were developed to assess the effectiveness of DSRC models in predicting SSC and bedload for rivers in Minnesota. More than 600 dimensionless ratio values of SSC, bedload, and streamflow were evaluated and delineated according to Pfankuch stream stability categories of “good/fair” and “poor” to develop four Minnesota-based DSRC models. The basis for Pagosa Springs and Minnesota DSRC model effectiveness was founded on measures of goodness-of-fit that included proximity of the model(s) fitted line to the 95-percent confidence intervals of the site-specific model, Nash-Sutcliffe Efficiency values, model biases, and deviation of annual sediment loads from each model to the annual sediment loads calculated from measured data. Composite plots comparing Pagosa Springs DSRCs, Minnesota DSRCs, site-specific regression models, and measured data indicated that regionally developed DSRCs (Minnesota DSRC models) more closely approximated measured data for nearly every site. Pagosa Springs DSRC models had markedly larger exponents (slopes) when compared to the Minnesota DSRC models and the site-specific regression models, and over-represent SSC and bedload at streamflows exceeding bankfull. The Nash-Sutcliffe Efficiency values for the Minnesota DSRC model for suspended-sediment concentrations closely matched Nash-Sutcliffe Efficiency values of the site-specific regression models for 12 out of 16 sites. Nash-Sutcliffe Efficiency values associated with Minnesota DSRCs were greater than those associated with Pagosa Springs DSRCs for every site except the Whitewater River near Beaver, Minnesota site. Pagosa Springs DSRC models were less accurate than the mean of the measured data at predicting SSC values for one-half of the sites for good/fair stability sites and one-half of the sites for poor stability sites. Relative model biases were calculated and determined to be substantial (greater than 5 percent) for Pagosa Springs and Minnesota models, with Minnesota models having a lower mean model bias. For predicted annual suspended-sediment loads (SSL), the Minnesota DSRC models for good/fair and poor stream stability sites more closely approximated the annual SSLs calculated from the measured data as compared to the Pagosa Springs DSRC model. Results of data analyses indicate that DSRC models developed using data collected in Minnesota were more effective at compensating for differences in individual stream characteristics across a variety of basin sizes and flow regimes than DSRC models developed using data collected for Pagosa Springs, Colorado. Minnesota DSRC models retained a substantial portion of the unique sediment signatures for most rivers, although deviations were observed for streams with limited sediment supply and for rivers in southeastern Minnesota, which had markedly larger regression exponents. Compared to Pagosa Springs DSRC models, Minnesota DSRC models had regression slopes that more closely matched the slopes of site-specific regression models, had greater Nash-Sutcliffe Efficiency values, had lower model biases, and approximated measured annual sediment loads more closely. The results presented in this report indicate that regionally based DSRCs can be used to estimate reasonably accurate values of SSC and bedload. Practitioners are cautioned that DSRC reliability is dependent on representative measures of bankfull streamflow, SSC, and bedload. It is, therefore, important that samples of SSC and bedload, which will be used for estimating SSC and bedload at the bankfull streamflow, are collected over a range of conditions that includes the ascending and descending limbs of the event hydrograph. The use of DSRC models may have substantial limitations for certain conditions. For example, DSRC models should not be used to predict SSC and sediment loads for extreme streamflows, such as those that exceed twice the bankfull streamflow value because this constitutes conditions beyond the realm of current (2016) empirical modeling capability. Also, if relations between SSC and streamflow and between bedload and streamflow are not statistically significant, DSRC models should not be used to predict SSC or bedload, as this could result in large errors. For streams that do not violate these conditions, DSRC estimates of SSC and bedload can be used for stream restoration planning and design, and for estimating annual sediment loads for streams where little or no sediment data are available.

Minnesota↗

USGS2016

Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water; however, streamgages cannot be installed at every location where streamflow information is needed. Therefore, methods for estimating streamflow at ungaged stream locations need to be developed. This report presents a statewide study to develop methods to estimate the structure of historical daily streamflow at ungaged stream locations in Minnesota. Historical daily mean streamflow at ungaged locations in Minnesota can be estimated by transferring streamflow data at streamgages to the ungaged location using the QPPQ method. The QPPQ method uses flow-duration curves at an index streamgage, relying on the assumption that exceedance probabilities are equivalent between the index streamgage and the ungaged location, and estimates the flow at the ungaged location using the estimated flow-duration curve. Flow-duration curves at ungaged locations can be estimated using recently developed regression equations that have been incorporated into StreamStats ( http://streamstats.usgs.gov/ ), which is a U.S. Geological Survey Web-based interactive mapping tool that can be used to obtain streamflow statistics, drainage-basin characteristics, and other information for user-selected locations on streams.

Minnesota↗

USGS2015

Methods for estimating flow-duration curve and low-flow frequency statistics for ungaged locations on small streams in Minnesota

Knowledge of the magnitude and frequency of low flows in streams, which are flows in a stream during prolonged dry weather, is fundamental for water-supply planning and design; waste-load allocation; reservoir storage design; and maintenance of water quality and quantity for irrigation, recreation, and wildlife conservation. This report presents the results of a statewide study for which regional regression equations were developed for estimating 13 flow-duration curve statistics and 10 low-flow frequency statistics at ungaged stream locations in Minnesota. The 13 flow-duration curve statistics estimated by regression equations include the 0.0001, 0.001, 0.02, 0.05, 0.1, 0.25, 0.50, 0.75, 0.9, 0.95, 0.99, 0.999, and 0.9999 exceedance-probability quantiles. The low-flow frequency statistics include annual and seasonal (spring, summer, fall, winter) 7-day mean low flows, seasonal 30-day mean low flows, and summer 122-day mean low flows for a recurrence interval of 10 years. Estimates of the 13 flow-duration curve statistics and the 10 low-flow frequency statistics are provided for 196 U.S. Geological Survey continuous-record streamgages using streamflow data collected through September 30, 2012. The study area includes 196 streamgages located within Minnesota and 50 miles beyond the State’s borders in North Dakota, South Dakota, Iowa, and Wisconsin. The study area was divided into five regions that were developed in a previous study using the concept of hydrologic landscape units. Geographic information system software was used to calculate 18 characteristics investigated as potential explanatory variables in regression analyses for each streamgage drainage basin. Trend analyses indicated statistically significant trends in summer 7-day low flows that were not related to precipitation patterns for 19 streamgages. For 16 of these streamgages, the streamflow record was subset using structural change analysis to identify the most recent period of record without a significant trend. The three remaining streamgages with significant trends were excluded from the final analysis because the effective period of record without a significant trend was less than 10 years. Because several streams in this study have zero flow as their minimum reported flow, weighted left-censored regression was used to analyze the flow data in an unbiased manner, with weights based on the number of years of record. A total of 115 regression equations were developed in this study to calculate flow-duration curve and low-flow frequency statistics for ungaged locations in the study area. In addition, data from 25 pairs of streamgages were used to develop drainage-area ratio equations that can be used to estimate streamflow statistics at ungaged locations on streams that have a streamgage in another location. Streamflow statistics estimated using regional regression and drainage-area ratio equations were compared among regions. For regions A, D, and E, drainagearea ratio equations were more accurate than regional regression equations for flows, but regional regression equations were more accurate for high flows. For region F, regional regression equations were consistently more accurate than drainage-area ratio equations. For region BC, the pattern in accuracies of regional regression and drainage-area ratio equations between low flows and high flows was not consistent. Equations developed in this study apply only to stream locations where flows are not substantially affected by regulation, diversion, or urbanization. All equations presented in this study will be incorporated into StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey. StreamStats allows users to obtain streamflow statistics, basin characteristics, and other information for user-selected locations on streams through an interactive map.

Iowa, Minnesota, North Dakota, South Dakota, Wisco↗

USGS2015

smwrBase—An R package for managing hydrologic data, version 1.1.1

This report describes an R package called smwrBase, which consists of a collection of functions to import, transform, manipulate, and manage hydrologic data within the R statistical environment. Functions in the package allow users to import surface-water and groundwater data from the U.S. Geological Survey’s National Water Information System database and other sources. Additional functions are provided to transform, manipulate, and manage hydrologic data in ways necessary for analyzing the data.

Open-File Report↗

USGS2015

smwrData—An R package of example hydrologic data, version 1.1.1

A collection of 24 datasets, including streamflow, well characteristics, groundwater elevations, and discrete water-quality concentrations, is provided to produce a consistent set of example data to demonstrate typical data manipulations or statistical analysis of hydrologic data. These example data are provided in an R package called smwrData. The data in the package have been collected by the U.S. Geological Survey or published in its reports, for example Helsel and Hirsch (2002). The R package provides a convenient mechanism for distributing the data to users of R within the U.S. Geological Survey and other users in the R community.

Open-File Report↗

USGS2015

A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R 2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R 2 and a version with R 2 within one standard error of the maximum (the 1SE model). The former yielded CV training R 2 values of 0.94–1.0. Cross-validation testing R 2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R 2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R 2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R 2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

California↗

USGS2014

Trends in major-ion constituents and properties for selected sampling sites in the Tongue and Powder River watersheds, Montana and Wyoming, based on data collected during water years 1980-2010

The primary purpose of this report is to present information relating to flow-adjusted temporal trends in major-ion constituents and properties for 16 sampling sites in the Tongue and Powder River watersheds based on data collected during 1980–2010. In association with this primary purpose, the report presents background information on major-ion characteristics (including specific conductance, calcium, magnesium, potassium, sodium adsorption ratio, sodium, alkalinity, chloride, fluoride, dissolved sulfate, and dissolved solids) of the sampling sites and coal-bed methane (CBM) produced water (groundwater pumped from coal seams) in the site watersheds, trend analysis methods, streamflow conditions, and factors that affect trend results. The Tongue and Powder River watersheds overlie the Powder River structural basin (PRB) in northeastern Wyoming and southeastern Montana. Limited extraction of coal-bed methane (CBM) from the PRB began in the early 1990’s, and increased dramatically during the late 1990’s and early 2000’s. CBM-extraction activities produce discharges of water with high concentrations of dissolved solids (particularly sodium and bicarbonate ions) relative to most stream water in the Tongue and Powder River watersheds. Water-quality of CBM produced water is of concern because of potential effects of sodium on agricultural soils and potential effects of bicarbonate on aquatic biota. Two parametric trend-analysis methods were used in this study: the time-series model (TSM) and ordinary least squares regression (OLS) on time, streamflow, and season. The TSM was used to analyze trends for 11 of the 16 study sites. For five sites, data requirements of the TSM were not met and OLS was used to analyze trends. Two primary 10-year trend-analysis periods were selected. Trend-analysis period 1 (water years 1986–95; hereinafter referred to as period 1) was selected to represent variability in major-ion concentrations in the Tongue and Powder River watersheds before potential effects of CBM-extraction activities. Trend analysis period 2 (water years 2001–10; hereinafter referred to as period 2) was selected because it encompassed substantial CBM-extraction activities and therefore might indicate potential effects of CBM-extraction activities on water quality of receiving streams in the Tongue and Powder River watersheds. For sites that did not satisfy data requirements for the TSM, OLS was used to analyze trends for period 2 (if complete data were available) or a 6-year period (2005–10). Flow-rate characteristics of CBM-produced water were estimated to allow general comparisons with streamflow characteristics of the sampling sites. The information on flow-rate characteristics of CBM-produced water in relation to streamflow does not account for effects of disposal, treatment, or other remediation activities on the potential quantitative effects of CBM-produced water on receiving streams. In many places, CBM-produced water is discharged into impoundments or channels in upper reaches of tributary watersheds where water infiltrates and does not directly contribute to streamflow. For Tongue River at State line (site 4) mean annual pumping rate of CBM-produced water during water years 2001–10 (hereinafter referred to as mean CBM pumping rate) was 6 percent of the mean of annual median streamflows during water years 2001–10 (hereinafter referred to as 2001–10 median streamflow). For main-stem Tongue River sites 5, 7, and 10, mean CBM pumping rate was 8–12 percent of 2001–10 median streamflow. For main-stem Powder River sites (sites 12, 13, and 16), mean CBM pumping rates were 26, 28, and 34 percent of 2001–10 median streamflows, respectively. For main-stem Tongue River sites analyzed by using the TSM and downstream from substantial CBM-extraction activities [Tongue River at State line (site 4), Tongue River at Tongue River Dam (site 5), Tongue River at Birney Day School (site 7), and Tongue River at Miles City (site 10)], generally small significant or nonsignificant decreases in most constituents are indicated for period 1. For period 2 for these sites, the TSM trend results do not allow confident conclusions concerning detection of effects of CBM-extraction activities on stream water quality. Detection of significant trends in major-ion constituents and properties for period 2 generally was infrequent, and direction, magnitudes, and significance of fitted trends were not strongly consistent with relative differences in water quality between stream water and CBM-produced water. The TSM indicated significant or generally large magnitude increases in median values of sodium adsorption ratio (SAR), sodium, and alkalinity for period 2 for sites 5 and 7, which might indicate potential effects of CBM-extraction activities on stream water. However, other factors, including operations of Tongue River Reservoir, irrigation activities, contributions of saline groundwater, and operations of the Decker coal mine, confound confident determination of causes of detected significant trends for sites 5 and 7. For all mainstem Tongue River sites, trends for period 2 generally are within ranges of those for period 1 before substantial CBM-extraction activities. For main-stem Powder River sites analyzed by using the TSM [Powder River at Sussex (site 11), Powder River at Arvada (site 12), Powder River at Moorhead (site 13), and Powder River near Locate (site 16)], significant or generally large magnitude decreases in median values of SAR, sodium, estimated alkalinity, chloride, fluoride, specific conductance, and dissolved solids are indicated for period 1. Patterns in trend results for period 1 for main-stem Powder River sites are consistent with effects of Salt Creek oil-brine reinjection that started in 1990. Trend results for all main-stem Powder River sites downstream from substantial CBM-extraction activities (sites 12, 13, and 16) indicate evidence of potential effects of CBM-extraction activities on stream water quality, although evidence is stronger for sites 12 and 13 than for site 16. Evidence in support of potential CBM effects includes significant increases in median values of SAR, sodium, and estimated alkalinity for period 2 for sites 12, 13, and 16 that are consistent with relative differences between stream water and CBM-produced water. Significant increases in median values of these constituents for period 2 are not indicated for Powder River at Sussex (site 11) upstream from substantial CBM-extraction activities. In interpreting the trend results, it is notable that the fitted trends evaluate changes in median concentrations and also notable that changes in median concentrations that might be attributed to CBM-extraction activities probably are more strongly evident during low to median streamflow conditions than during mean to high streamflow conditions. This observation is relevant in assessing trend results in relation to specific water-quality concerns, including effects of water-quality changes on irrigators and effects on stream biota and ecology.

Montana;Wyoming↗

USGS2014

Water-quality trends for selected sampling sites in the upper Clark Fork Basin, Montana, water years 1996-2010

A large-scale trend analysis was done on specific conductance, selected trace elements (arsenic, cadmium, copper, iron, lead, manganese, and zinc), and suspended-sediment data for 22 sites in the upper Clark Fork Basin for water years 1996–2010. Trend analysis was conducted by using two parametric methods: a time-series model (TSM) and multiple linear regression on time, streamflow, and season (MLR). Trend results for 1996–2010 indicate moderate to large decreases in flow-adjusted concentrations (FACs) and loads of copper (and other metallic elements) and suspended sediment in Silver Bow Creek upstream from Warm Springs. Deposition of metallic elements and suspended sediment within Warm Springs Ponds substantially reduces the downstream transport of those constituents. However, mobilization of copper and suspended sediment from floodplain tailings and stream banks in the Clark Fork reach from Galen to Deer Lodge is a large source of metallic elements and suspended sediment, which also affects downstream transport of those constituents. Copper and suspended-sediment loads mobilized from within this reach accounted for about 40 and 20 percent, respectively, of the loads for Clark Fork at Turah Bridge (site 20); whereas, streamflow contributed from within this reach only accounted for about 8 percent of the streamflow at Turah Bridge. Minor changes in FACs and loads of copper and suspended sediment are indicated for this reach during 1996–2010. Clark Fork reaches downstream from Deer Lodge are relatively smaller sources of metallic elements than the reach from Galen to Deer Lodge. In general, small decreases in loads and FACs of copper and suspended sediment are indicated for Clark Fork sites downstream from Deer Lodge during 1996–2010. Thus, although large decreases in FACs and loads of copper and suspended sediment are indicated for Silver Bow Creek upstream from Warm Springs, those large decreases are not translated to the more downstream reaches largely because of temporal stationarity in constituent transport relations in the Clark Fork reach from Galen to Deer Lodge. Unlike metallic elements, arsenic (a metalloid element) in streams in the upper Clark Fork Basin typically is mostly in dissolved phase, has less variability in concentrations, and has weaker direct relations with suspended-sediment concentrations and streamflow. Arsenic trend results for 1996–2010 indicate generally moderate decreases in FACs and loads in Silver Bow Creek upstream from Opportunity. In general, small temporal changes in loads and FACs of arsenic are indicated for Silver Bow Creek and Clark Fork reaches downstream from Opportunity during 1996–2010. Contribution of arsenic (from Warm Springs Ponds, the Mill-Willow bypass, and groundwater sources) in the Silver Bow Creek reach from Opportunity to Warm Springs is a relatively large source of arsenic. Arsenic loads originating from within this reach accounted for about 11 percent of the load for Clark Fork at Turah Bridge; whereas, streamflow contributed from within this reach only accounted for about 2 percent of the streamflow at Turah Bridge.

Montana↗

USGS2013

Methods and results of peak-flow frequency analyses for streamgages in and bordering Minnesota, through water year 2011

Peak-flow frequency analyses were completed for 409 streamgages in and bordering Minnesota having at least 10 systematic peak flows through water year 2011. Selected annual exceedance probabilities were determined by fitting a log-Pearson type III probability distribution to the recorded annual peak flows. A detailed explanation of the methods that were used to determine the annual exceedance probabilities, the historical period, acceptable low outliers, and analysis method for each streamgage are presented. The final results of the analyses are presented.

Minnesota↗

USGS2012

Seasonal patterns in nutrients, carbon, and algal responses in wadeable streams within three geographically distinct areas of the United States, 2007-08

The U.S. Geological Survey determined seasonal variability in nutrients, carbon, and algal biomass in 22 wadeable streams over a 1-year period during 2007 or 2008 within three geographically distinct areas in the United States. The three areas are the Upper Mississippi River Basin (UMIS) in Minnesota, the Ozark Plateaus (ORZK) in southern Missouri and northern Arkansas, and the Upper Snake River Basin (USNK) in southern Idaho. Seasonal patterns in some constituent concentrations and algal responses were distinct. Nitrate concentrations were greatest during the winter in all study areas potentially because of a reduction in denitrification rates and algal uptake during the winter, along with reduced surface runoff. Decreases in nitrate concentrations during the spring and summer at most stream sites coincided with increased streamflow during the snowmelt runoff or spring storms indicating dilution. The continued decrease in nitrate concentrations during summer potentially is because of a reduction in nitrate inputs (from decreased surface runoff) or increases in biological uptake. In contrast to nitrate concentrations, ammonia concentrations varied among study areas. Ammonia concentration trends were similar at UMIS and USNK sampling sites with winter peak concentrations and rapid decreases in ammonia concentrations by spring or early summer. In contrast, ammonia concentrations at OZRK sampling sites were more variable with peak concentrations later in the year. Ammonia may accumulate in stream water in the winter under ice and snow cover at the UMIS and USNK sites because of limited algal metabolism and increased mineralization of decaying organic matter under reducing conditions within stream bottom sediments. Phosphorus concentration patterns and the type of phosphorus present changes with changing hydrologic conditions and seasons and varied among study areas. Orthophosphate concentrations tended to be greater in the summer at UMIS sites, whereas total phosphorus concentrations at most UMIS and USNK sites peaked in the spring during runoff and then decreased through the remainder of the sampling period. Total phosphorus and orthophosphate concentrations in OZRK streams peaked during summer indicating a runoff-based source of both nutrients. Orthophosphate concentrations may increase in streams in the late summer when surface runoff composes less of total streamflow, and when groundwater containing orthophosphate becomes a more dominant source in streams during lower flows. Seston chlorophyll a concentrations were greatest early in the growing season (spring), whereas the spring runoff events coincided with reductions in benthic algal chlorophyll a biomass likely because of scour of benthic algae from the channel bottom that are entrained in the water column during that period. Nitrate, ammonia, and orthophosphate concentrations also decreased during that same period, indicating dilution in the spring during runoff events. The data from this study indicate that the source of water (surface runoff or groundwater) to a stream and the intensity of major runoff events are important factors controlling instream concentrations. Biological processes appear to affect nutrient concentrations during more stable lower flow periods in later summer, fall, and winter when residence time of water in a channel is longer, which allows more time for biological uptake and transformations. Management of nutrient conditions in streams is challenging and requires an understanding of multiple factors that affect in-stream nutrient concentrations and biological uptake and growth.

Scientific Investigations Report↗

USGS2011

USGS library for S-PLUS for Windows -- Release 4.0

Release 4.0 of the U.S. Geological Survey S-PLUS library supercedes release 2.1. It comprises functions, dialogs, and datasets used in the U.S. Geological Survey for the analysis of water-resources data. This version does not contain ESTREND, which was in version 2.1. See Release 2.1 for information and access to that version. This library requires Release 8.1 or later of S-PLUS for Windows. S-PLUS is a commercial statistical and graphical analysis software package produced by TIBCO corporation(http://www.tibco.com/). The USGS library is not supported by TIBCO or its technical support staff.

Open-File Report↗

USGS2011

Assessment of nutrient enrichment by use of algal-, invertebrate-, and fish-community attributes in wadeable streams in ecoregions surrounding the Great Lakes

The algal, invertebrate, and fish taxa and community attributes that best reflect the effects of nutrients along a gradient of low to high nutrient concentrations in wadeable, primarily midwestern streams were determined as part of the U.S. Geological Suvey's National Water-Quality Assessment (NAWQA) Program. Nutrient data collected from 64 sampling sites that reflected reference, agricultural, and urban influences between 1993 and 2006 were used to represent the nutrient gradient within Nutrient Ecoregion VI (Cornbelt and Northern Great Plains), VII (Mostly Glaciated Dairy Region), and VIII (Nutrient Poor Largely Glaciated Upper Midwest and Northeast). Nutrient Ecoregions VII and VIII comprise the Glacial North diatom ecoregion (GNE) and Nutrient Ecoregion VI represents the Central and Western Plains diatom ecoregion (CWPE). The diatom-ecoregion groupings were used chiefly for data analysis. The total nitrogen (TN) and total phosphorus (TP) data from 64 sites, where at least 6 nutrient samples were collected within a year at each site, were used to classify the sites into low-, medium-, and high-nutrient categories based upon the 10th and 75th percentiles of for sites within each Nutrient Ecoregion. In general, TN and TP concentrations were 3-5 times greater in Nutrient Ecoregion VI than in Nutrient Ecoregions VII and VIII. A subgroup of 54 of these 64 sites had algal-, invertebrate-, and fish-community data that were collected within the same year as the nutrients; these sites were used to assess the effects of nutrients on the biological communities. Multidimensional scaling was used to determine whether the entire region could be assessed together or whether there were regional differences between the algal, invertebrate, and fish communities. The biological communities were significantly different between the northern sites, primarily in the GNE and the southern sites, primarily in the CWPE. In the higher nutrient concentration gradient in the streams of the CWPE, algae exhibited greater differences than invertebrates and fish between all of the nutrient categories for both TN and TP; however, in the lower nutrient gradient in the streams of the GNE, invertebrates exhibited greater differences between the nutrient categories. Certain species of algae, invertebrates, and fish were more prevalent in low- and high-nutrient categories within each of the diatom ecoregions. Breakpoint analysis was used to identify the concentration at which the relations between the response variable (biological attribute) and the stressor variable (TN and TP) change. There were significant breakpoints for nutrients (TN and TP) and multiple attributes for algae, invertebrates, and fish communities within the CWPE and GNE diatom ecoregions. In general, more significant breakpoints, with lower concentrations, were found in the GNE than the more nutrient-rich CWPE. The breakpoints from all biological communities were generally about 3-5 times higher in the south (CWPE) than the north (GNE). In the north, breakpoints with similar lower concentrations were found for TN from all biological communities (around 0.60 milligram per liter) and for TP (between 0.02 and 0.03 milligram per liter) for the algae and invertebrate communities. The findings from our study suggest that the range in breakpoints for TN and TP from the GNE can be used as oligotrophic and eutrophic boundaries derived from biological response based on this ecoregion having (1) a gradient with sufficiently low to high nutrient concentrations, (2) distinctive differences in the biological communities in the low- to high-nutrient streams, (3) similarity of breakpoints within algal, invertebrate, and fish communities, (4) significant attributes with either direct relations to nutrients or traditional changes in community structure (that is, decreases in sensitive species or increases in tolerant species), and (5) similar breakpoints in other studies in this and other regions. In nutrie

Scientific Investigations Report↗

USGS2011

Floods of September 2010 in Southern Minnesota

During September 22-24, 2010, heavy rainfall ranging from 3 inches to more than 10 inches caused severe flooding across southern Minnesota. The floods were exacerbated by wet antecedent conditions, where summer rainfall totals were as high as 20 inches, exceeding the historical average by more than 4 inches. Widespread flooding that occurred as a result of the heavy rainfall caused evacuations of hundreds of residents, and damages in excess of 64 million dollars to residences, businesses, and infrastructure. In all, 21 counties in southern Minnesota were declared Federal disaster areas. Peak-of-record streamflows were recorded at nine U.S. Geological Survey and three Minnesota Department of Natural Resources streamgages as a result of the heavy rainfall. Flood-peak gage heights, peak streamflows, and annual exceedance probabilities were tabulated for 27 U.S. Geological Survey and 5 Minnesota Department of Natural Resources streamgages and 5 ungaged sites. Flood-peak streamflows in 2010 had annual exceedance probabilities estimated to be less than 0.2 percent (recurrence interval greater than 500 years) at 7 streamgages and less than 1 percent (recurrence interval greater than 100 years) at 5 streamgages and 4 ungaged sites. High-water marks were identified and tabulated for the most severely affected communities of Faribault along the Cannon and Straight Rivers, Owatonna along the Straight River and Maple Creek, Pine Island along the North Branch and Middle Fork Zumbro River, and Zumbro Falls along the Zumbro River. The nearby communities of Hammond, Henderson, Millville, Oronoco, Pipestone, and Rapidan also received extensive flooding and damage but were not surveyed for high-water marks. Flood-peak inundation maps and water-surface profiles for the four most severely affected communities were constructed in a geographic information system by combining high-water-mark data with the highest resolution digital elevation model data available. The flood maps and profiles show the extent and height of flooding through the communities and can be used for flood response and recovery efforts by local, county, State, and Federal agencies.

Minnesota↗