Geology topics

Catherine A. Chamberlin

Publications and source records attributed to Catherine A. Chamberlin.

5 recordsLinked to original sources

USGS2026

Low streamflows in Massachusetts: Variability over space and time and relations with climatic and basin variables

Streamflows in Massachusetts have set record lows in recent years despite generally wetter conditions than during the drought of the 1960s, and the reasons for this are not known. To analyse potential drivers of low streamflows in Massachusetts, six low-flow metrics were computed at 107 streamgages. These metrics represent low-flow magnitude, magnitude normalized to median flows, and duration. Multiple linear regressions were used to analyse the variability of low flows over space and time. Potential explanatory variables were computed using climatic, land use, water use, and basin data. For all low-flow metrics, the ratio of precipitation to potential evapotranspiration (P/PET) in July–August explained the most variability, with decreasing P/PET largely explained by lower precipitation. Water/wetland area was a significant explanatory variable in all the normalized-magnitude and duration models, with greater area associated with lower normalized magnitudes and with shorter durations of low flows. Human influence (characterized by development, population, water use, and artificial water storage) had mixed effects. Trends from 1983 to 2022 in summer P/PET and human influence have been strongest in the eastern part of the state where the strongest decreases in flows are observed. Low flows in Massachusetts seem to be driven by a combination of low summer precipitation and human effects, though the specific mechanisms of human influence on flow likely vary between basins.

Massachusetts↗

USGS2025

Water withdrawal and consumption trends for thermoelectric-power plants in the conterminous United States, 2008-2020

Freshwater-using utility-scale thermoelectric (TE) plant water-use estimates were evaluated for annual trends from 2008 to 2020 across the conterminous United States (CONUS) and within hydrologic regions. Overall, TE water withdrawal and consumption trends declined across CONUS by 14,335 and 278 million liters/day, respectively. Decreasing water withdrawal and consumption trends for TE plants are driven largely by switching from coal-fired plants to other generation technologies. TE plant cooling system technology has also changed, with large declining trends for TE plants using once-through cooling systems and small increasing consumption trends for TE plants using recirculating tower cooling systems. Fifteen hydrologic regions have decreasing trends in withdrawals and consumption. The largest decreases are for coal-fired plants using once-through freshwater cooling systems in the Great Lakes and Ohio hydrologic regions. Natural gas combined cycle plants with recirculating tower cooling systems have increased water consumption trends across most of the CONUS hydrologic regions. Some TE plants with recirculating tower or once-through cooling systems withdraw water volumes that on average are close to or exceed average simulated streamflows. Most of these situations occur in the central and eastern U.S., potentially leading to water availability issues among competing water needs, ecosystem impacts from thermal pollution, and power generation constraints.

conterminous United States↗

USGS2025

Automating physics-based models to estimate thermoelectric-power water use

Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).

Environmental Modelling and Software↗

USGS2024

Estimating domestic self-supplied water use in Rhode Island, 2014–21

Water withdrawal from private groundwater wells is often unaccounted for in water planning studies, and water from private wells can be a source of exposure to environmental contaminants. The sizes of populations that depend on private wells for domestic water use and the amounts of water that are withdrawn from these wells are generally poorly represented in data collection efforts because of the challenges of locating, metering, or gathering withdrawal information from individual property owners. To address this problem, the U.S. Geological Survey, in cooperation with the Rhode Island Water Resources Board, estimated the volume of water withdrawn from domestic self-supply wells and the populations who use them for the State of Rhode Island at a 30-meter pixel spatial resolution and one-month temporal resolution between July 2014 and June 2021. The number of people reliant on domestic self-supply wells has increased in Rhode Island over the study period; however, the statewide estimate of total water withdrawal has not statistically increased. Withdrawals from private wells are largest in the inland areas of the western part of the State, and the towns of Scituate and Charlestown have the highest estimated withdrawals. Statewide monthly withdrawals ranged from 3.987 million gallons per day in March 2018 to 7.767 million gallons per day in September 2016. The median per capita domestic water use rate was 46.0 gallons per capita per day.

Rhode Island↗

USGS2024

A predictive analysis of water use for Providence, Rhode Island

To explain the drivers of historical water use in the public water systems (PWSs) that serve populations in Providence, Rhode Island, and surrounding areas, and to forecast future water use, a machine-learning model (cubist regression) was developed by the U.S. Geological Survey in cooperation with Providence Water to model daily per capita rates of domestic, commercial, and industrial water use. The PWSs in this area form a connected network that sources water from the Scituate Reservoir in Rhode Island. The cubist regression model was trained and tested on daily per capita rates for three categories of water use (domestic, commercial, and industrial) that were developed from quarterly water sales data and U.S. Census Bureau population estimates within each PWS service area from January 2005 through December 2021. The model was then used to make forecasts of future water use under varying scenarios of climate change, population growth, and economic growth for the years 2030 and 2040. The resulting daily per capita rates, which were modeled from the historical data, had an r 2 value of 0.94 and root mean square error of 6.7 gallons per capita daily. Results of the model were used to estimate total water use (the product of daily per capita rates and population) for all public water systems over the historical study period. Daily per capita rates in the study area decreased from 2005 to 2021, while population increased during that same period. “Category of water use” was the variable with the greatest explanatory power for modeling daily per capita rates. Overall, both daily per capita rates and total water use were projected to decrease in 2030 and 2040, in comparison to historical values from 2005 to 2021. Daily per capita rates and total water use were forecasted to decrease as economic growth rates increase. Daily per capita rates were expected to decrease as population growth rates increase; however, total water use was less sensitive to population growth rates than daily per capita rates. Effects of climate change were minimal over the 2030 and 2040 forecasting horizon for the scenarios tested.

Rhode Island↗