Geology topics

Sara B. Levin

Publications and source records attributed to Sara B. Levin.

At least 19 recordsLinked to original sources

USGS2025

Hydroclimatic and land-use factors affecting peak streamflow in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis provides the basis for flood risk estimates used by water-resource managers in land-use planning, and it informs the design of essential infrastructure such as bridges and culverts. Federal guidelines for flood-frequency analysis do not offer guidance on addressing changing climate and land-use conditions when estimating floods. However, failing to consider climatic and land-use changes that cause abrupt or gradual changes in flood regimes can result in a poor representation of the true flood risk. In response to concerns about changing flood regimes, the U.S. Geological Survey, in cooperation with nine State agencies (Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation) began a study to examine variability and change in hydrology and climate and the effects of urbanization and tile drainage on flooding. The analyses of patterns and changes in hydrology and climate were reported in a multichapter Scientific Investigations Report, the findings of which are summarized in this U.S. Geological Survey Circular. Additional analyses documenting changes in seasonality of flooding and the effects of urbanization and tile drainage were completed and published as separate studies and are also summarized in this Circular. These studies provide extensive exploratory analysis of peak streamflow, daily streamflow, and climate data, setting the stage for advancements in flood-frequency analysis.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗

USGS2025

Nonstationary flood frequency analysis using regression in the north-central United States

Traditional flood frequency methods assume that the statistical properties of peak streamflow do not change with time and may not be appropriate for many areas in the north-central United States. This study examines a nonstationary flood frequency analysis method that uses ordinary least squares linear regression to estimate flood magnitudes at U.S. Geological Survey streamgages that exhibit trends and change points in a nine-State region including Montana, North Dakota, South Dakota, Minnesota, Illinois, Iowa, Wisconsin, Missouri, and Michigan. Additionally, an extension of this method is introduced, which enables nonstationary flood frequency based on a statistical relation with a stochastic climate predictor. Estimates of the 1-percent annual exceedance probability flood using regression equations to adjust for conditions in 2020 were computed at U.S. Geological Survey streamgages across the study area. Regression equations used either a time index or a climate variable as the explanatory variable for changes in peak streamflow. Of 153 candidate streamgages, the assumptions of time-adjusted analyses were met at 137 streamgages. Climate-adjusted flood frequency analyses were applicable at 98 streamgages based on annual precipitation, annual temperature, or annual snowfall. Time- and climate-adjusted methods produced similar estimates of the 1-percent annual exceedance probability flood magnitude at streamgages where both methods were applicable. Nonstationary estimates of the 1-percent annual exceedance probability flood were primarily greater than stationary estimates in eastern North and South Dakota, Minnesota, Iowa, Illinois, and parts of Missouri and less than stationary estimates in Montana, western North and South Dakota, and Wisconsin. The largest differences between stationary and nonstationary flood estimates were in North and South Dakota and Minnesota.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗

USGS2025

Suspended sediment and bedload transport along the Main and South Branches, Wild Rice River, northwestern Minnesota, 1979 through 2023

The geologic history and anthropogenic modifications of Minnesota’s Wild Rice River have caused major morphological adjustments, which induce erosion and excess fluvial sediment transport. The excess sediment deposits in the lower Wild Rice River, exacerbating flooding. To help mitigate these problems, the Wild Rice Watershed District has future plans to implement a river restoration on the lower Wild Rice River. The Wild Rice Watershed District collaborated with the U.S. Geological Survey to measure and analyze sediment transport along the Wild Rice River’s Main and South Branches to assess any potential changes in sediment transport among sites and time periods. Time differencing results indicated that all suspended-sediment constituents showed a significant difference between the two sampling periods at one South Branch site but not at the Main Branch site. Piecewise regression analysis better matched the suspended-sediment constituents transport process at most sites by differentiating no relation between suspended-sediment constituents at lower streamflows and a positive relation at higher streamflows at most Wild Rice River sites. Five of the sites showed elevated sediment transport with increasing streamflow. In contrast, the site farthest downstream showed a negative relation with increasing streamflow, indicating that that the lower Wild Rice River is supply limited and deposition is likely occurring upstream and (or) near the site. Overall, the uncertainty in results indicates the complexity of sediment transport in a river when using streamflow as the sole explanatory variable and suggests a need for multisite, multiyear, and multifaceted data.

Minnesota↗

USGS2024

Peak streamflow trends in Michigan and their relation to changes in climate, water years 1921–2020

This study characterizes hydroclimatic variability and change in peak streamflow and daily streamflow in Michigan from water years 1921 through 2020. Four analysis periods were examined: the 100-year period from water year 1921 through 2020, the 75-year period from water year 1946 through 2020, the 50-year period from water year 1971 through 2020, and the 30-year period from water year 1991 through 2020. Peak streamflow and climate data were available at 4, 29, 50, and 30 streamgages in the 100-, 75-, 50-, and 30-year periods, respectively. Daily streamflow was available for 4, 29, 74, and 79 streamgages in the 100-, 75-, 50-, and 30-year periods, respectively. Peak streamflow for each streamgage and analysis period was assessed for monotonic trends and change points. Trends in peak streamflow were predominantly upward, with some isolated downward trends throughout the southern half of Michigan for all four analysis periods. Trends in the Upper Peninsula were downward in 75- and 50-year analysis periods and upward or neutral in the 30-year period. Upward trends in peak flows were largely driven by increases in precipitation, which occurred at nearly every streamgage in all analysis periods, with the greatest magnitude trends in winter and spring in the 50- and 30-year periods.

Michigan↗

USGS2024

Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States. This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States. Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.

Iowa, Illinois, Michigan, Missouri, Minnesota, Mon↗

USGS2024

Peak streamflow trends in Wisconsin and their relation to changes in climate, water years 1921–2020

This study characterizes hydroclimatic variability and change in peak streamflow and daily streamflow in Wisconsin from water years 1921 through 2020. Nonstationarity in peak streamflow in Wisconsin can include monotonic trends, change points, and autocorrelation. Spatial patterns of nonstationarity in peak streamflow, daily streamflow, and monthly precipitation, temperature, and snowfall were examined using four temporal periods. Upward trends in peak streamflow and daily streamflow were detected across the State, from around 1990 to 2020 and were likely predominantly driven by concurrent increases in precipitation and temperatures during this time. Earlier decreases in peak streamflow between the 1920s to the 1980s in the southern parts of the State were likely affected by nonclimate-related factors such as urbanization, water use, and land-use changes associated with agriculture.

Wisconsin↗

USGS2023

Techniques for estimating the magnitude and frequency of peak flows on small streams in Minnesota, excluding the Rainy River Basin, based on data through water year 2019

Annual peak-flow data collected at U.S. Geological Survey streamgages in Minnesota and adjacent areas of neighboring states of Iowa and South Dakota were analyzed to develop and update regional regression equations that can be used to estimate the magnitude and frequency of peak streamflow for ungaged streams in Minnesota, excluding the Lake of the Woods-Rainy River Basin upstream from Kenora, Ontario, Canada. Hydraulic engineers use peak-flow frequency estimates to inform designs of bridges, culverts, and dams, and water managers use the estimates for regulation and planning activities. Peak-flow estimates are provided for the 66.7-, 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities (AEPs), which are equivalent to annual flood-frequency recurrence intervals of 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively. The estimates were computed by applying the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows for 298 streamgages based on annual peak-flow data collected through water year 2019. The study area is represented by six hydrologic regions delineated on the basis of a pattern of residuals of statewide regressions, using basin characteristics such as drainage area, main-channel slope, lake area, storage area, and mean annual runoff as explanatory variables. The concept and principles of hydrologic landscape units was used to validate the regions. Residual analysis of the regional regression equations was used to subsequently develop equations relating the peak flow estimates for selected AEPs using 17 characteristics tested as explanatory variables in the regression analysis. The equations developed in this study can be used to produce AEPs within the six regions and to update equations developed in earlier, similar studies in Minnesota. Furthermore, updating the equations in StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey, will allow hydraulic engineers and water managers to obtain AEPs and basin characteristics for user-selected locations on streams through an interactive map.

Minnesota↗

USGS2023

A novel suspended-sediment sampling method: Depth-Integrated Grab (DIG)

Measuring suspended sediment in fluvial systems is critical to understanding and managing water resources. Sampling suspended sediment has been the primary means of understanding fluvial suspended sediment. Specialized samplers, sampling methods, and laboratory methods developed by select U.S. Federal Agencies are more representative of river and stream conditions than commonly used grab sampling and total suspended solids (TSS) laboratory methods but are not widely used because they are expensive, time consuming, and not required as part of water quality standards in the United States. A new suspended-sediment sampling method called a depth-integrated grab (DIG) was developed by combining certain elements from both grab and depth-integrating sampling methods and suspended-sediment concentration (SSC) laboratory methods. The goal of the DIG method was to provide more accurate results than Grab-TSS while being easier and cheaper to sample than specialized samplers and methods. Approximately 50 paired comparison samples were collected at 9 sites in Minnesota from 2018 through 2019. Results showed no significant difference between the DIG and specialized sampling methods and a significant difference between both methods and the Grab-TSS method. The DIG-SSC provided an improved alternative to the Grab-TSS method, but additional research and testing is important to evaluate if this method is appropriate in different conditions than were observed in this study.

Minnesota↗

USGS2023

Estimating flood magnitude and frequency for unregulated streams in Wisconsin

Flood frequency characteristics and estimated flood discharges for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed at 299 streamgaged locations in Wisconsin. The State was divided into four flood frequency regions using a cluster analysis to produce regions which are homogeneous with respect to physical basin characteristics. Regression equations relating flood discharges to basin characteristics within each region were developed and can be used to estimate flood discharges at ungaged locations in Wisconsin. Basin characteristics included in the final regression equations include drainage area, saturated hydraulic conductivity, percent forest, percent herbaceous upland, percent open water, and the maximum 24-hour precipitation with a 10-year recurrence interval. The standard error of prediction for regression equations ranges between 40 and 71 percent, and the pseudo coefficient of determination ranges between 0.8 and 0.95. Nonmonotonic trends in the annual peak flow time series in the southwest part of the State are producing bias in some flood discharge estimates at streamgages with shorter (less than 20 years) periods of record. This bias increases the uncertainty in regression equations in this flood frequency region.

Wisconsin↗

USGS2023

Comparing empirical sediment transport modeling approaches in Michigan rivers

Excess or limited fluvial sediment transport can contribute to and exacerbate many environmental issues including nutrient loading, aquatic habitat degradation, flooding, channel navigation dredging, dam operation, and stream degradation or aggradation. However, fluvial sediment transport is difficult and expensive to comprehensively characterize because it can vary substantially both temporally and spatially. Having better estimates of fluvial sediment transport is important for understanding and solving these environmental issues when it is not possible to collect fluvial sediment samples. Different modeling approaches can be used to help estimate suspended sediment when sampling data are limited or unavailable. This study compared dimensionless sediment rating curves (DSRCs) developed in Pagosa Springs Colorado, Minnesota, and Michigan to determine if these DSRCs were suitable to make predictions of suspended sediment for Michigan rivers. Approximately 3,000 suspended sediment samples collected in or near Michigan from the mid-1960s through August 2022 were used to develop two DSRC models. The DSRCs developed in Michigan include a pooled DSRC model which uses nonlinear least squares regression, and a mixed-effects DSRC model which uses a mixed-effects modeling approach. In general, there was not a noticeable improvement in the performance of the Michigan mixed-effects DSRC model over the Michigan pooled DSRC model. The two Michigan DSRCs were evaluated against DSRCs developed for Pagosa Springs and Minnesota. The results showed DSRC models developed from Minnesota and Michigan were similar to each other. In contrast, the Pagosa Springs DSRC predicts higher suspended-sediment concentration (SSC) at low flows and increases at a higher rate due to having a greater exponent. The Pagosa Springs DSRC produces higher SSC predictions that do not approximate the observed data well at most of the Michigan sites in the study. The results suggest that the Pagosa Springs DSRC was not suitable to make predictions of suspended sediment for Michigan rivers. The similarity of the DSRC equations developed for Minnesota and Michigan compared to the Pagosa Springs DSRC equation suggest that there may be regional patterns of SSC in the upper Midwest rivers that differ from those in other areas of the country like Pagosa Springs. A regionally applicable model could be developed and strengthened by combining data from additional midwestern states. Since the Michigan DSRCs goodness-of-fit metrics were comparable to the site-specific simple linear regressions (SLRs) and outperformed them in the aggregate goodness-of-fit metrics, the Michigan DSRCs are suitable to make predictions of suspended sediment in Michigan rivers with limited data. However, the availability of the DSRCs from this study should not diminish the value of collecting physical samples and exploring alternative modeling approaches because of the uncertainty associated with using DSRCs. Approximately 3,000 suspended sediment samples collected in or near Michigan from the mid-1960s through August 2022 were used to develop two DSRC models. The DSRCs developed in Michigan include a pooled DSRC model which uses nonlinear least squares regression, and a mixed-effects DSRC model which uses a mixed-effects modeling approach. In general, there was not a noticeable improvement in the performance of the Michigan mixed-effects DSRC model over the Michigan pooled DSRC model. The two Michigan DSRCs were evaluated against DSRCs developed for Pagosa Springs and Minnesota. The results showed DSRC models developed from Minnesota and Michigan were similar to each other. In contrast, the Pagosa Springs DSRC predicts higher suspended-sediment concentration (SSC) at low flows and increases at a higher rate due to having a greater exponent. The Pagosa Springs DSRC produces higher SSC predictions that do not approximate the observed data well at most of the Michigan sites in the study. The results suggest that the Pagosa Springs DSRC was not suitable to make predictions of suspended sediment for Michigan rivers. The similarity of the DSRC equations developed for Minnesota and Michigan compared to the Pagosa Springs DSRC equation suggest that there may be regional patterns of SSC in the upper Midwest rivers that differ from those in other areas of the country like Pagosa Springs. A regionally applicable model could be developed and strengthened by combining data from additional midwestern states. Since the Michigan DSRCs goodness-of-fit metrics were comparable to the site-specific simple linear regressions (SLRs) and outperformed them in the aggregate goodness-of-fit metrics, the Michigan DSRCs are suitable to make predictions of suspended sediment in Michigan rivers with limited data. However, the availability of the DSRCs from this study should not diminish the value of collecting physical samples and exploring alternative modeling approaches because of the uncertainty associated with using DSRCs.

Michigan↗

USGS2023

Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records

Flood-frequency analysis is essential in numerous water-resource management applications, including critical structure design and flood-plain mapping. A basic assumption within Bulletin 17C [1], the standardized guidelines for conducting flood-frequency analysis, is that basins without major hydrologic alterations, such as regulation or urbanization, exhibit stationary statistical properties of the distribution of annual peak streamflow. That is, the mean, variance, and skew are constant over time and the peak-flow record is a representative sample of the population of future floods [1]. In recent decades, better understanding of long-term climatic persistence and concerns about climate and land-use change have caused the assumption of stationarity in peak-flow records to be reexamined [2, 3, 4, 5]. Under nonstationary conditions, the long-term distributional properties (mean, variance, and/or skew) of peak-flow series change one or more times, either gradually or abruptly. Nonstationarities may be attributed to one source, but are often a result of a mixture of drivers, making detection and attribution of nonstationarities challenging [6, 7, 8]. Failure to incorporate observed trends and abrupt changes into flood-frequency analysis may result in a poor representation of the true flood risk. Bulletin 17C currently offers no guidance on how to account for nonstationarities when estimating floods and acknowledges the benefit additional flood frequency studies that incorporate changing climate or basin characteristics into the analysis would provide[1].

Midwest↗

USGS2022

Quantifying relations between altered hydrology and fish community responses for streams in Minnesota

Altered hydrology is a stressor on aquatic life for several streams in Minnesota, but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota. Best subsets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic explanatory metrics (i.e., duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and six categories of biological response metrics (i.e., composition, habitat, life history, reproductive, tolerance, trophic) computed from fish community samples, as well as fish-based indices of biotic integrity (FIBI) scores and FIBI scores normalized to the an impairment threshold of the corresponding stream class (FIBI_BCG4). Three hydrologic datasets were used to examine rRelations between altered hydrology and fish community responses were examined at three different temporal scalesusing three hydrologic datasets that represented periods of record, long-term changes, and short-term changes to flow regimes in streams of Minnesota.

Minnesota↗

USGS2020

Evaluation of uncertainty intervals for daily, statistically derived streamflow estimates at ungaged basins across the continental U.S.

Streamflow estimation methods that transfer information from an index gage to an ungaged site are commonly used; however, uncertainty in daily streamflow estimates are often not adequately quantified. In this study, daily streamflow was simulated at 1,331 validation streamgages across the continental United States using four transfer-based streamflow estimation methods. Empirical 95 percent uncertainty intervals were computed for estimated daily streamflows. Uncertainty intervals were evaluated for reliability, sharpness, and overall ability to accurately quantify the uncertainty inherent in the estimated daily streamflow. Uncertainty intervals performed reliably in the Eastern U.S. and Pacific Northwest regions of the country, containing a median of 96 and 99 percent of the observed values respectively. Uncertainty intervals were less reliable in the Great Plains and arid Southwest regions, where uncertainty intervals contained a median of 83 and 94 percent of the observed streamflows respectively. Uncertainty interval performance was correlated with gage density and hydrologic similarity near the validation site, as well as the aridity and base-flow indices at the site.

Water↗

USGS2018

User guide for the Massachusetts Sustainable-Yield Estimator (MA SYE—version 2.0) computer program

This report is a user guide for the Massachusetts Sustainable-Yield Estimator (MA SYE) computer program (version 2.0). The MA SYE was developed by the U.S. Geological Survey in cooperation with the Massachusetts Department of Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Massachusetts. The MA SYE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The MA SYE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The MA SYE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.

Massachusetts↗

USGS2018

Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0

The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed previously and has been implemented with minor changes and updated water-use data in version 2.0 of the Massachusetts Sustainable-Yield Estimator. Unaltered streamflow at selected exceedance probabilities is estimated by previously published regression equations. Streamflow is interpolated between the regressed quantiles to produce a continuous flow duration curve. A daily streamflow time series is produced for the ungaged site by relating the estimated flow duration curve at the ungaged site to a flow duration curve at a gaged reference site and then transferring the dates from the reference site to the ungaged site. Minor refinements were made to the previously published methods to estimate unaltered and water-use-adjusted streamflow, including a procedure to enforce the monotonic structure of the regression-based unaltered flow quantiles, improvements to the interpolation method used for computing the estimated flow duration curve, and updates to the methods used to compute time-lagged stream alterations from groundwater pumping or discharges. Additionally, a procedure was developed to estimate prediction intervals for daily and monthly unregulated streamflow time series at an ungaged site. The Massachusetts Sustainable-Yield Estimator computes water-use-adjusted streamflow using water-use data provided by the Massachusetts Department of Environmental Protection. Available water-use data included monthly withdrawal and wastewater discharge volumes from 2010 to 2014 for surface-water and groundwater sources. Water-use-adjusted streamflow represents the potential effect of current water use on natural streamflow in the basin over the range of historical hydrologic conditions. Georeferenced water withdrawal and discharge volumes were incorporated into the Massachusetts StreamStats web application for use in version 2.0 of the Massachusetts Sustainable-Yield Estimator. To compute water-use-adjusted streamflow, mean daily withdrawals and discharges within a user-defined basin are subtracted and added to the unaltered time series, respectively. Surface-water volumes are applied directly to the equation. Time-lagged streamflow alterations from groundwater withdrawal or wastewater discharge sources are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models in Massachusetts. The Massachusetts Sustainable-Yield Estimator was updated to version 2.0 to improve software stability and usability. The version 2.0 software application was developed in Microsoft Access with a graphical user interface. All geoprocessing steps, including basin delineation and compilation of basin characteristics and water use within the basin, were completed in the Massachusetts StreamStats web application and exported for use by the Massachusetts Sustainable-Yield Estimator version 2.0.

Massachusetts↗

USGS2018

User guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE—version 1.0) computer program

This report is a user guide for the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) computer program (version 1.0). The CT SSWUE was developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics to assess sustainable water use at ungaged sites in Connecticut. The CT SSWUE provides estimates of unaltered streamflow (which is assumed to occur in the absence of any water withdrawals or wastewater discharges and with minimal human development), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The CT SSWUE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The CT SSWUE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access. The graphical user interface is designed to include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.

Open-File Report↗

USGS2018

The Connecticut Streamflow and Sustainable Water Use Estimator—A decision-support tool to estimate water availability at ungaged stream locations in Connecticut

Freshwater streams in Connecticut are subject to many competing demands, including public water supply; agricultural, commercial, and industrial water use; and ecosystem and habitat needs. In recent years, drought has further stressed Connecticut’s water resources. To sustainably allocate and manage water resources among these competing uses, Federal, State, and local water-resource managers require data and modeling tools to estimate the water availability at a variety of temporal and spatial scales for planning purposes. The Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE), developed by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection, is a decision-support tool for estimating daily unaltered streamflow and sustainable water use at ungaged sites in Connecticut. The CT SSWUE estimates unaltered daily mean streamflow and water-use-adjusted streamflow for the period from October 1, 1960, to September 30, 2015, and the monthly sustainable net withdrawal at ungaged sites in Connecticut. Unaltered streamflow is the estimated daily mean streamflow in a drainage basin in the absence of any water withdrawals or wastewater discharges and with minimal human development. Sustainable net withdrawal is the maximum net withdrawal (withdrawal minus wastewater discharges) that can be drawn from a basin without critically depleting the water available through natural streamflow patterns. Sustainable net withdrawal is defined for this study as the difference between the unaltered daily mean streamflow and a user-defined target minimum streamflow. Weighted least squares and Tobit regression techniques were used to develop equations for estimating streamflow at ungaged sites at 19 streamflow quantiles with exceedance probabilities ranging from 0.005 to 99.995 percent. Regressions were based on streamflow quantiles and basin characteristics from 36 reference streamgages in and around Connecticut. Four basin characteristics—drainage area, mean of the soil permeability, mean of the average annual precipitation, and ratio of the length of streams that overlay sand and gravel deposits to the total length of streams in the basin—are used as explanatory variables in the equations. At an ungaged site, interpolation between the streamflow quantiles estimated from the regression equations produces a continuous flow-duration curve. A time series of daily mean streamflow at an ungaged site is then estimated by assuming that for each day, the streamflow quantile occurs on the same date at both a reference streamgage and the ungaged site. In a remove-one cross validation, estimated unaltered daily mean streamflow agreed well with observed values at reference streamgages, with a few exceptions. Nash Sutcliffe efficiency ranged from −0.43 to 0.97 with a median value of 0.88. The normalized root-mean-square error ranged from 16.6 to 120.4 percent with a median value of 34.5 percent. An empirical method for estimating 95-percent prediction intervals for unaltered daily and monthly mean streamflow was developed and tested by using the cross-validation data. Prediction intervals for unaltered daily mean streamflow at the cross-validation reference streamgages performed well in most cases. Gaged streamflow values from the cross-validation data fell within the prediction intervals a median 96.6 percent of the time for daily mean time series and 93.9 percent of the time for monthly mean time series. The CT SSWUE computes water-use-adjusted streamflow using spatially referenced water-use information provided by the Connecticut Department of Energy and Environmental Protection. Available water-use information included permitted and registered water withdrawals and permitted wastewater discharges during 1998 to 2015 for the Thames River Basin and central coastal drainage basins. Water-use information was incorporated into the U.S. Geological Survey StreamStats web application for Connecticut and can be used for computing water-use-adjusted streamflow and sustainable net withdrawal at selected points of interest. Altered daily streamflow is computed by applying average daily withdrawals and wastewater discharges to the water balance equation. Average daily surface water withdrawals and wastewater discharges are applied directly to the daily water balance equation. Time-lagged alterations on streamflow from groundwater withdrawals or wastewater discharges are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models.

Connecticut↗

USGS2017

Characterizing uncertainty in daily streamflow estimates at ungauged locations for the Massachusetts sustainable yield estimator

Hydrologic characterization at ungauged locations is one of the quintessential challenges of hydrology. Beyond simulation of historical streamflows, it is similarly important to characterize the level of uncertainty in hydrologic estimates. In tandem with updates to Massachusetts Sustainable Yield Estimator, this work explores the application of global uncertainty estimates to daily streamflow simulations. Expanding on a method developed for deterministic modeling, this approach produces confidence intervals on daily streamflow developed through nonlinear spatial interpolation of daily streamflow using flow duration curves; the 95% confidence is examined. Archived cross‐validations of daily streamflows from 66 watersheds in and around Massachusetts are used to evaluate an approach to uncertainty characterization. Neighboring sites are treated as ungauged, producing relative errors that can be resampled and applied to target sites. The method, with some modification, is found to provide appropriately narrow confidence intervals that contain 95% of the observed streamflows in cross‐validation. Further characterizing uncertainty, multiday means of daily streamflow are evaluated. Working through cross‐validation in Massachusetts, two‐ to three‐month averages of daily streamflow show the best performance. These two approaches to uncertainty characterization inform how streamflow simulation produced for prediction in ungauged basins can be used for water resources management.

Massachusetts↗