Geology topics

Stacey A. Archfield

Publications and source records attributed to Stacey A. Archfield.

At least 37 records · Page 2Linked to original sources

USGS2016

Urban base flow with low impact development

A novel form of urbanization, low impact development (LID), aims to engineer systems that replicate natural hydrologic functioning, in part by infiltrating stormwater close to the impervious surfaces that generate it. We sought to statistically evaluate changes in a base flow regime because of urbanization with LID, specifically changes in base flow magnitude, seasonality, and rate of change. We used a case study watershed in Clarksburg, Maryland, in which streamflow was monitored during whole-watershed urbanization from forest and agricultural to suburban residential development using LID. The 1.11-km 2 watershed contains 73 infiltration-focused stormwater facilities, including bioretention facilities, dry wells, and dry swales. We examined annual and monthly flow during and after urbanization (2004–2014) and compared alterations to nearby forested and urban control watersheds. We show that total streamflow and base flow increased in the LID watershed during urbanization as compared with control watersheds. The LID watershed had more gradual storm recessions after urbanization and attenuated seasonality in base flow. These flow regime changes may be because of a reduction in evapotranspiration because of the overall decrease in vegetative cover with urbanization and the increase in point sources of recharge. Precipitation that may once have infiltrated soil, been stored in soil moisture to be eventually transpired in a forested landscape, may now be recharged and become base flow. The transfer of evapotranspiration to base flow is an unintended consequence to the water balance of LID.

Hydrological Processes↗

USGS2016

Regional flow duration curves: Geostatistical techniques versus multivariate regression

A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.

Advances in Water Resources↗

USGS2015

Accelerating advances in continental domain hydrologic modeling

In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

Water Resources Research↗

USGS2015

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

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

Iowa, Minnesota↗

USGS2015

A bootstrap method for estimating uncertainty of water quality trends

Estimation of the direction and magnitude of trends in surface water quality remains a problem of great scientific and practical interest. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method was recently introduced as an exploratory data analysis tool to provide flexible and robust estimates of water quality trends. This paper enhances the WRTDS method through the introduction of the WRTDS Bootstrap Test (WBT), an extension of WRTDS that quantifies the uncertainty in WRTDS-estimates of water quality trends and offers various ways to visualize and communicate these uncertainties. Monte Carlo experiments are applied to estimate the Type I error probabilities for this method. WBT is compared to other water-quality trend-testing methods appropriate for data sets of one to three decades in length with sampling frequencies of 6–24 observations per year. The software to conduct the test is in the EGRETci R-package.

Environmental Modelling and Software↗

USGS2015

A comparison of methods to predict historical daily streamflow time series in the southeastern United States

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.

Scientific Investigations Report↗

USGS2013

An objective and parsimonious approach for classifying natural flow regimes at a continental scale

Hydro-ecological stream classification-the process of grouping streams by similar hydrologic responses and, by extension, similar aquatic habitat-has been widely accepted and is considered by some to be one of the first steps towards developing ecological flow targets. A new classification of 1543 streamgauges in the contiguous USA is presented by use of a novel and parsimonious approach to understand similarity in ecological streamflow response. This novel classification approach uses seven fundamental daily streamflow statistics (FDSS) rather than winnowing down an uncorrelated subset from 200 or more ecologically relevant streamflow statistics (ERSS) commonly used in hydro-ecological classification studies. The results of this investigation demonstrate that the distributions of 33 tested ERSS are consistently different among the classification groups derived from the seven FDSS. It is further shown that classification based solely on the 33 ERSS generally does a poorer job in grouping similar streamgauges than the classification based on the seven FDSS. This new classification approach has the additional advantages of overcoming some of the subjectivity associated with the selection of the classification variables and provides a set of robust continental-scale classes of US streamgauges. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

River Research and Applications↗

USGS2013

Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

Hydrology and Earth System Sciences↗

USGS2013

Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers

Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals) at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.

Geoscientific Model Development↗

USGS2013

A national streamflow network gap analysis

The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations. The analysis indicated that there is variability across the Nation’s streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics. At ungaged locations, information can be transferred from nearby streamgages if there is sufficient similarity between the gaged watersheds and the ungaged watersheds of interest. Areas where streamgages exhibit high correlation are most likely to be suitable for this type of information transfer. The areas with the most highly correlated streamgages appear to coincide with mountainous areas of the United States. Lower correlations are found in the Central United States and coastal areas of the Southeastern United States. Information transfer from gaged basins to ungaged basins is also most likely to be successful when basin attributes show high similarity. At the scale of the analysis completed in this study, the attributes of basins upstream of USGS streamgages cover the full range of basin attributes observed at potential locations of interest fairly well. Some exceptions included very high or very low elevation areas and very arid areas.

Puerto Rico↗

USGS2013

Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

Iowa↗

USGS2012

Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990-2009

The U.S. Geological Survey evaluated 20 years of total phosphorus (P) and total nitrogen (N) concentration data for 18 Lake Champlain tributaries using a new statistical method based on weighted regressions to estimate daily concentration and flux histories based on discharge, season, and trend as explanatory variables. The use of all the streamflow discharge values for a given date in the record, in a process called "flow-normalization," removed the year-to-year variation due to streamflow and generated a smooth time series from which trends were calculated. This approach to data analysis can be of great value to evaluations of the success of restoration efforts because it filters out the large random fluctuations in the flux that are due to the temporal variability in streamflow. Results for the full 20 years of record showed a mixture of upward and downward trends for concentrations and yields of P and N. When the record was broken into two 10-year periods, for many tributaries, the more recent period showed a reversal in N from upward to downward trends and a similar reversal or reduction in magnitude of upward trends for P. Some measures of P and N concentrations and yields appear to be related to intensity of agricultural activities, point-source loads of P, or population density. Total flow-normalized P flux aggregated from the monitored tributaries showed a decrease of 30 metric tons per year from 1991 to 2009, which is about 15% of the targeted reduction established by the operational management plan for the Lake Champlain Basin.

Vermont;New York↗

USGS2012

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft 3 /s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft 3 /s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft 3 /s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft 3 /s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft 3 /s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft 3 /s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

Illinois;Iowa;Minnesota;Missouri;Nebraska;Wisconsi↗

USGS2011

Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0

The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs to assess the sensitivity of firm-yield estimates to errors in daily-streamflow input data. Results of the Monte Carlo simulations indicate that underestimation in the lowest stream inflows can cause firm yields to be underestimated by an average of 1 to 10 percent. Errors in the stage-storage relation can arise when the point density of bathymetric survey measurements is too low. Existing bathymetric surfaces were resampled using hypothetical transects of varying patterns and point densities in order to quantify the uncertainty in stage-storage relations. Reservoir-volume calculations and resulting firm yields were accurate to within 5 percent when point densities were greater than 20 points per acre of reservoir surface. Methods for incorporating summer water-demand-reduction scenarios into the firm-yield model were developed as well as the ability to relax the no-fail reliability criterion. Although the original firm-yield model allowed monthly reservoir releases to be specified, there have been no previous studies examining the feasibility of controlled releases for downstream flows from Massachusetts reservoirs. Two controlled-release scenarios were tested—with and without a summer water-demand-reduction scenario—for a scenario with a no-fail criterion and a scenario that allows for a 1-percent failure rate over the entire simulation period. Based on these scenarios, about one-third of the reservoir systems were able to support the flow-release scenarios at their 2000–2004 usage rates. Reservoirs with higher storage ratios (reservoir storage capacity to mean annual streamflow) and lower demand ratios (mean annual water demand to annual firm yield) were capable of higher downstream release rates. For the purposes of this research, all reservoir systems were assumed to have structures which enable controlled releases, although this assumption may not be true for many of the reservoirs studied.

Massachusetts↗

USGS2010

Map correlation method: Selection of a reference streamgage to estimate daily streamflow at ungaged catchments

Daily streamflow time series are critical to a very broad range of hydrologic problems. Whereas daily streamflow time series are readily obtained from gaged catchments, streamflow information is commonly needed at catchments for which no measured streamflow information exists. At ungaged catchments, methods to estimate daily streamflow time series typically require the use of a reference streamgage, which transfers properties of the streamflow time series at a reference streamgage to the ungaged catchment. Therefore, the selection of a reference streamgage is one of the central challenges associated with estimation of daily streamflow at ungaged basins. The reference streamgage is typically selected by choosing the nearest streamgage; however, this paper shows that selection of the nearest streamgage does not provide a consistent selection criterion. We introduce a new method, termed the map‐correlation method, which selects the reference streamgage whose daily streamflows are most correlated with an ungaged catchment. When applied to the estimation of daily streamflow at 28 streamgages across southern New England, daily streamflows estimated by a reference streamgage selected using the map‐correlation method generally provides improved estimates of daily streamflow time series over streamflows estimated by the selection and use of the nearest streamgage. The map correlation method could have potential for many other applications including identifying redundancy and uniqueness in a streamgage network, calibration of rainfall runoff models at ungaged sites, as well as for use in catchment classification.

New England↗

USGS2010

Weighted regressions on time, discharge, and season (WRTDS), with an application to Chesapeake Bay River inputs

A new approach to the analysis of long‐term surface water‐quality data is proposed and implemented. The goal of this approach is to increase the amount of information that is extracted from the types of rich water‐quality datasets that now exist. The method is formulated to allow for maximum flexibility in representations of the long‐term trend, seasonal components, and discharge‐related components of the behavior of the water‐quality variable of interest. It is designed to provide internally consistent estimates of the actual history of concentrations and fluxes as well as histories that eliminate the influence of year‐to‐year variations in streamflow. The method employs the use of weighted regressions of concentrations on time, discharge, and season. Finally, the method is designed to be useful as a diagnostic tool regarding the kinds of changes that are taking place in the watershed related to point sources, groundwater sources, and surface‐water nonpoint sources. The method is applied to datasets for the nine large tributaries of Chesapeake Bay from 1978 to 2008. The results show a wide range of patterns of change in total phosphorus and in dissolved nitrate plus nitrite. These results should prove useful in further examination of the causes of changes, or lack of changes, and may help inform decisions about future actions to reduce nutrient enrichment in the Chesapeake Bay and its watershed.

Maryland, Virginia↗

USGS2010

The Massachusetts Sustainable-Yield Estimator: A decision-support tool to assess water availability at ungaged stream locations in Massachusetts

Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed unregulated, daily mean streamflow at 18 streamgages located across southern New England. Nash-Sutcliffe efficiency goodness-of-fit values are between 0.69 and 0.98, and percent root-mean-square-error values are between 19 and 283 percent. The MA SYE tool provides an estimate of streamflow adjusted for current (2000-04) water withdrawals and discharges using a spatially referenced database of permitted groundwater and surface-water withdrawal and discharge volumes. For a user-selected basin, the database is queried to obtain the locations of water withdrawal or discharge volumes within the basin. Groundwater and surface-water withdrawals and discharges are subtracted and added, respectively, from the unregulated, daily streamflow at an ungaged site to obtain a streamflow time series that includes the effects of these withdrawals and discharges. Users also have the option of applying an analytical solution to the time-varying, groundwater withdrawal and discharge volumes that take into account the effects of the aquifer properties on the timing and magnitude of streamflow alteration. For the MA SYE tool, it is assumed that groundwater and surface-water divides are coincident. For areas of southeastern Massachusetts and Cape Cod where this assumption is known to be violated, groundwater-flow models are used to estimate average monthly streamflows at fixed locations. There are several limitations to the quality and quantity of the spatially referenced database of groundwater and surface-water withdrawals and discharges. The adjusted streamflow values do not account for the effects on streamflow of climate change, septic-system discharge, impervious area, non-public water-supply withdrawals less than 100,000 gallons per day, and impounded surface-water bodies.

Massachusetts↗

USGS2010

Indicators of streamflow alteration, habitat fragmentation, impervious cover, and water quality for Massachusetts stream basins

Massachusetts streams and stream basins have been subjected to a wide variety of human alterations since colonial times. These alterations include water withdrawals, treated wastewater discharges, construction of onsite septic systems and dams, forest clearing, and urbanization—all of which have the potential to affect streamflow regimes, water quality, and habitat integrity for fish and other aquatic biota. Indicators were developed to characterize these types of potential alteration for subbasins and groundwater contributing areas in Massachusetts. The potential alteration of streamflow by the combined effects of withdrawals and discharges was assessed under two water-use scenarios. Water-use scenario 1 incorporated publicly reported groundwater withdrawals and discharges, direct withdrawals from and discharges to streams, and estimated domestic-well withdrawals and septic-system discharges. Surface-water-reservoir withdrawals were excluded from this scenario. Water-use scenario 2 incorporated all the types of withdrawal and discharge included in scenario 1 as well as withdrawals from surface-water reservoirs—all on a long-term, mean annual basis. All withdrawal and discharge data were previously reported to the State for the 2000–2004 period, except domestic-well withdrawals and septic-system discharges, which were estimated for this study. The majority of the state’s subbasins and groundwater contributing areas were estimated to have relatively minor (less than 10 percent) alteration of streamflow under water-use scenario 1 (seasonally varying water use; no surface-water-reservoir withdrawals). However, about 12 percent of subbasins and groundwater contributing areas were estimated to have extensive alteration of streamflows (greater than 40 percent) in August; most of these basins were concentrated in the outer metropolitan Boston region. Potential surcharging of streamflow in August was most commonly indicated for main-stem river subbasins, although surcharging was also indicated for some smaller tributary subbasins. In the high-flow month of April, only 4.8 percent of subbasins and groundwater contributing areas had more than 10 percent potential flow alteration. A majority of the state’s subbasins and groundwater contributing areas were also indicated to have relatively minor alteration of streamflow under water-use scenario 2 (long-term average water use, including surface-water-reservoir withdrawals). Extensive alteration of mean annual flows was estimated for about 6 percent of the state’s subbasins and groundwater contributing areas. The majority of subbasins estimated to have extensive long-term flow alteration contained reservoirs that were specifically designed, constructed, and managed to supply drinking water to cities. Only a small number of subbasins and groundwater contributing areas (1 percent) were extensively surcharged on a long-term, mean annual basis. Because site-specific data concerning surface-water-reservoir storage dynamics and management practices are not available statewide, the seasonal effects of surface-water-reservoir withdrawals on downstream flows could not be assessed in this study. The impounded storage ratio (volume of impounded subbasin or groundwater-contributing-area storage divided by mean annual predevelopment outflow from the subbasin or contributing area, in units of days) indicates the potential for alteration of streamflow, sediment-transport, and temperature regimes by dams, independent of water use. Storage ratios were less than 1 day for 33 percent of the subbasins and groundwater contributing areas, greater than 1 month for about 40 percent of the cases, and greater than 1 year for 3.2 percent of the cases statewide. Dam density, an indicator of stream-habitat fragmentation by dams, averaged 1 dam for every 6.7 stream miles statewide. Many of these dams are not presently (2009) being managed. The highest dam densities were in portions of Worcester County and in the Plymouth-Carver region, respectively, reflecting the historical reliance of Massachusetts industry upon water power and agricultural water-management practices in southeastern Massachusetts. Impervious cover is a frequently used indicator of urban land use. About 33 percent of the state’s 1,429 subbasins and groundwater contributing areas are relatively undeveloped at the local scale, with a local impervious cover of less than 4 percent. About 18 percent of Massachusetts subbasins and contributing areas are highly developed, with a local impervious cover greater than 16 percent. The remaining 49 percent of subbasins and contributing areas have levels of urban development between these extremes (4 to 16 percent local impervious cover). Cumulative impervious cover, defined for the entire upstream area encompassed by each subbasin, shows a smaller range (0 to 55 percent) than local impervious cover. Both local and cumulative impervious cover were highest in metropolitan Boston and other urban centers. High elevated impervious-cover values were also found along major transportation corridors. The water-quality status of Massachusetts streams is assessed periodically by the Massachusetts Department of Environmental Protection pursuant to the requirements of the Federal Clean Water Act. Streams selected for assessment are commonly located in larger subbasins where some degree of impairment is expected. In the 72 percent of the state’s subbasins and groundwater contributing areas with assessed streams in 2002, more than 50 percent of the assessed stream miles were considered impaired. All of the assessed stream miles were considered impaired in 66 percent of the subbasins and groundwater contributing areas with assessed streams. Large streams, such as the main stems of rivers that make up most of the assessed stream miles, also are in many cases the receiving waters for treated wastewater discharges and for this reason may be more susceptible to water-quality impairments than smaller streams. Subbasins and contributing areas with large fractions of assessed stream miles that are listed as impaired are distributed across the state, but are more prevalent in eastern Massachusetts.

Massachusetts↗