Geology topics

Samantha L. Sullivan

Publications and source records attributed to Samantha L. Sullivan.

5 recordsLinked to original sources

USGS2025

Statistical streamflow comparison of current and historical 30-year periods for selected streams in New Jersey

As the population of New Jersey increases, supplying adequate drinking water to meet demand remains a high priority. To better understand potential streamflow trends over time, the U.S. Geological Survey completed a study comparing low flows at continuous- and partial-record streamgages in New Jersey between a historical period (1950–79) and a current period (1990–2019). Fourteen statistics (one median for each of the twelve monthly minimum 1-day flows, minimum 7-day average streamflow with a 10-year recurrence interval, and median of the daily mean flows for the month of September) were calculated to evaluate how streamflow conditions may differ between the two time periods. Percent change was also calculated to better understand the magnitude of difference between the periods at individual streamgages. A Paired Wilcoxon Signed-Rank Test was implemented to test for a change in distribution between the two time periods for each statistic of interest. Results indicated that the median of the minimum 1-day flows for the months of January, February, June, September, and December and the median of the daily mean flows for the month of September had a statistically significant difference in distribution between the time periods for continuous-record streamgages. None of the statistics had a statistically significant difference in distribution for the partial-record streamgages. The largest percent changes between time periods occurred in the northern part of the state, above the Fall Line. Precipitation, land cover, and water use changes were assessed to contribute to the understanding of these differences between time periods. The median of the minimum 1-day flows for the months of January and December generally increased across the state, whereas the median of the minimum 1-day flows for the months of May and September generally decreased throughout the state.

New Jersey↗

USGS2025

Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models

The report focuses on the screening of previously published concentration data associated with 12 elements of concern (aluminum, arsenic, cadmium, chromium, copper, iron, mercury, manganese, lead, selenium, uranium, and zinc) measured in stream surface waters of three hydrologic basins (Delaware River Basin, Illinois River Basin, and the Upper Colorado River Basin). The purpose of this analysis is to determine what subsets of the original dataset (containing more than 1,500,000 observations) may be most suitable for each of two types of modeling efforts. The first type of modeling envisions a machine learning approach to determine which geospatial attributes are most significant in describing the spatial distribution of elemental concentrations within a basin. The second type of modeling envisions a stepwise regression approach to develop multivariable models that can be used to determine high resolution time-series estimates of elemental concentrations or loads at discrete U.S. Geological Survey real-time stream surface water sites. These site-specific temporal models are based on continuous measurements of available discharge and (or) in situ sensor data (temperature, pH, turbidity, dissolved oxygen, specific conductance, and (or) fluorescent dissolved organic matter) as the explanatory variables. The data screening for both model types considered historical trends in analytical methods and detection quantitation limits, the extent of censored data, data density, and environmental relevance with respect to three U.S. Environmental Protection Agency water quality thresholds (drinking water guidelines, human health criteria, and aquatic life criteria). The result of this analysis was the production of a final list of potential models deemed suitable for further development based upon the data exclusion (or inclusion) scheme developed herein for each model type. In both cases, the final models included mostly the three crustal elements (iron, manganese, and aluminum) that are found at comparatively high concentrations in surface water, whereas most of the more pernicious elements were excluded from the final model lists owing to various data limitations. The one exception to this was arsenic, for which the existing data were sufficient at three U.S. Geological Survey real-time sites for potential further development of time-series models.

Colorado, Delaware, Illinois, Indiana, Maryland, N↗

USGS2024

Streamflow characteristics and trends in New Jersey, water years 1903–2017

As New Jersey’s population density remains high, so does its requirements for water management. Understanding the streamflow conditions throughout the state and how they may have changed over time is an important part of managing the water resources within the state. The New Jersey Department of Environmental Protection has many responsibilities related to protecting the environment and natural resources and among them is protecting the waters in the lakes, rivers, and streams of New Jersey for current and future use. To support this mission, the U.S. Geological Survey updated high- and low-streamflow statistics for 97 continuous-record streamgages and low-streamflow statistics for 719 partial-record streamgages throughout the state. The continuous-record streamgages included in the study had a minimum of 20 years of record, spanning from 1903 to 2017. This study is an update to previous studies that documented the high- and low-streamflow statistics for New Jersey streams in the 1970s and in 2005. The 1982 report by Gillespie and Schopp documented low-flow characteristics and flow duration for about 400 continuous and partial-record streamgages. The U.S. Geological Survey computed streamflow statistics including, but not limited to, maximum, minimum, and means for period of record, flow durations, nonexceedance high- and low-flow frequencies, base flow, runoff, peak-to-mean flow ratios, and September median streamflow. Overall, both high and low flows are generally increasing in New Jersey, though the results are not uniform across the State. Streamflow trends and changes to duration and frequency statistics can be influenced by local water use, in addition to climate variables. The resulting computations at some streamgages indicated considerable positive change while others showed considerable negative change. Water managers and regulators can use the data provided here and in the companion data release to assess individual stream reaches and watershed management areas to evaluate the available resources and changes, which may have developed during the periods for which streamflow statistics are available.

New Jersey↗

USGS2021

Factors affecting uncertainty of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data, 1985–2015—Evaluation of information sources, estimation methods, and data variability

The U.S. Geological Survey (USGS) Water-Use Program is responsible for compiling and disseminating the Nation's water-use data. Working in cooperation with local, State, and Federal agencies, the USGS has collected and published national water-use estimates every 5 years, beginning in 1950. These water-use data may vary because of actual changes in water use, because of changes in estimation methods, or because of errors. Comparison and interpretation of these data is difficult without first determining the factors that contribute to data variability. This report describes factors that may affect data quality and documents ways to investigate the variability of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data for the 1985–2015 compilations. The USGS produces national water-use estimates for various categories of water use for every county in the United States. Knowledge about the sources of data for county estimates is important because factors such as estimation methodology and reporting affect data uncertainty Determination of meaningful patterns and trends in the data are contingent on the use of consistent methodology throughout the period of interest. With the many ways that water-use data have been collected, assembled, and estimated, multiple factors likely contribute to data uncertainty, Data used to produce these estimates may be furnished from agencies that collect information from entities who report water use; gaps in reported data are typically estimated to achieve a comprehensive county estimate. For example, public supply and thermoelectric category data are based primarily on furnished site-specific data; whereas crop irrigation is often furnished or estimated at the county scale. Public supply deliveries for domestic use and self-supplied domestic withdrawals are most often estimated by USGS personnel using per capita use rate coefficients. Irrigation may be estimated using crop water requirements, application rates, or other soil water balance methods when furnished reported data are not available. Rates, percentages, medians, and interquartile ranges were used to investigate variability in the water-use data among States, regions, and years. The purposes of these evaluations were to (1) identify extreme values that may reflect changes in information sources, estimation methods, or errors; (2) indicate areas of variable or consistent values that are unexpected; and (3) indicate areas where values change because of local climate or other factors. Where factors are identified that contribute to data variability, such as a change in methodology, additional work could determine uncertainty because of these factors. These evaluations identified the availability of information that is needed to address data limitations. Factors such as estimation methodology affect data quality. Some updates to method codes assigned in 2015 and assignment of method codes to earlier compilation datasets for all categories would provide much needed metadata for users of the data. Improvements in data documentation describing sources of information and estimation methods and additional metadata information from agencies and entities that furnish water-use data, would enable a more complete understanding and depiction of water-use patterns and trends. Additional metadata are needed for users of the data to better understand the water-use data and interpret changes in water use across the United States and with time.

Scientific Investigations Report↗

USGS2018

Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey

The U.S. Geological Survey (USGS) uses Maintenance of Variance Extension Type 1 (MOVE.1) regression to transfer streamflows measured at long-term continuous-record streamgaging stations to partial-record (PR) streamgaging stations where intermittent base-flow measurements are available. MOVE.1 regression is used widely throughout the hydrologic community to extend historic low flows and low-flow statistics at continuous-record streamgaging stations to streamgaging stations that have access to only a partial record of low flows. The method correlates base-flow measurements at PR streamgaging stations with daily mean streamflows measured at index stations that exhibit similar streamflow characteristics. Following changes in the computing platform for storing, processing, retrieving, and publishing National Water Information System (NWIS) hydrologic data, legacy Statistical Analysis System (SAS) code developed by the USGS to implement the MOVE.1 regression was no longer suitable for reading and processing NWIS streamflow data. To migrate the MOVE.1 program so that it could continue to read streamflow data using the new hydrologic data platform, the SAS code was re-written in R, an open source programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The work described in this report was performed in a study conducted by USGS in cooperation with the New Jersey Department of Environmental Protection. During migration from SAS to R, graphical and tabular output generated by the R script was compared to output produced by the legacy SAS code to ensure that equations used to perform the MOVE.1 regression remained the same. An option to perform censored MOVE.1 regression was added to extend the MOVE.1 methodology to cases where one or more measured continuous-record or PR streamgaging station flows are zero valued. In addition to permitting censored regression, the new R script includes an option to perform piecewise MOVE.1 regression when the relation between PR station and index station low flows varies significantly across the range of index station streamflows. Together with traditional MOVE.1 regression, censored, and piecewise MOVE.1 regression methods implemented by the R script offer less biased estimates than ordinary least squares regression for the annual 7-day 10-year and other low-flow statistics at PR stations for a range of base-flow conditions. The R script is used to implement the MOVE.1 regression methods across a variety of computing platforms.

New Jersey↗