Environmental streamflows in the United States: historical patterns and predictions Active
The term environmental streamflows refers to the magnitude, frequency, seasonal timing, duration, and rate of change of streamflows needed to sustain freshwater and estuary ecosystems and human wellbeing. It is important that environmental streamflow assessments by water managers consider changes in climate, land use, and water management; this cannot be done effectively without understanding variability and changes in environmental streamflows over time and space. A limited amount of research of this type has been published. Estimates of environmental streamflows also are needed for ungaged streams; machine-learning methods are likely useful for this. We will analyze historical change and variability at hundreds of streamflow gages across the United States for a suite of environmental streamflows and use machine-learning methods to estimate environmental streamflows for thousands of ungaged stream reaches. The current project builds on previous projects that focused on a limited number of environmental flows, such as the magnitude of low flows and flood flows.
Statement of Problem:
It is important that environmental streamflow assessments consider climatic and watershed changes; however, this requires understanding historical variability and changes in environmental streamflows. There is no known published work that quantifies the variability and change for a full suite of environmental streamflows in the United States at the regional or continental scale. There are many commonly used environmental streamflows that have not been systematically analyzed, such as the number and duration of high and low pulses in each year and measures of the rate of change of streamflows from day to day.
Thousands of streams within the United States do not have directly measured streamflow values (normally from USGS streamgages). Models to predict environmental streamflows for ungaged streams are an important tool for water resource managers. Data-driven models using machine-learning methods are increasingly being applied in hydrologic science and achieve predictive skill comparable to, or greater than, traditional process-based modeling methods. It would be very useful to know whether machine-learning methods can better predict environmental streamflows for ungaged rivers than traditional methods.
Why this Research is Important:
Managers use estimates of environmental streamflows as targets to approximate various aspects of natural streamflows. They can reach these targets by controlling flow from reservoirs. Approximating natural flow promotes the health of fish and other aquatic species. Little is known, however, about the historical variability of environmental flows over time and space. Our work will substantially help define this variability and provide important context for managing streamflow now and in the future.
Objective(s):
- Characterize temporal and spatial patterns for a suite of environmental streamflows across the conterminous United States based on streamflow data from hundreds of long-term streamflow gages. The environmental streamflows will include metrics of streamflow magnitude, frequency, seasonal timing, duration, and rate of change.
- Develop machine-learning models to estimate environmental streamflows for ungaged streams across the conterminous United States and compare results to streamflows estimated from traditional methods.
- In addition, we will focus on environmental flows specifically relevant to migratory marine fish in selected regions of the U.S.
Methods:
We will use trend-testing methods to analyze changes over time and space in environmental streamflows and analyze how much variability is explained by atmosphere-ocean patterns such as the Pacific Decadal Oscillation and the North Atlantic Oscillation. We will consider how changes in climate, reservoir regulation, and urban and agricultural land uses have impacted environmental streamflows.
We will develop machine learning models using variables such as basin soil characteristics and land use, precipitation, and temperature data. Multiple methods will be considered and evaluated.
The Influence of Climatic, Watershed, and Water-use Changes on Extreme Low Streamflows in the United States
Climate-driven variability in the occurrence of major floods across North America and Europe
Trends in snowmelt-related streamflow timing in the conterminous United States
Reference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends
Historical summer base flow and stormflow trends for New England rivers
River base flow is important to aquatic ecosystems, particularly because of its influence on summer water temperatures. Summer (June through September) daily mean streamflows were separated into base flow and stormflow components by use of an automated method at 25 stations in the New England region of the United States that drain predominantly natural basins. Summer monthly mean base flows increa
Streamflow changes in Alaska between the cool phase (1947–1976) and the warm phase (1977–2006) of the Pacific Decadal Oscillation: The influence of glaciers
- Overview
The term environmental streamflows refers to the magnitude, frequency, seasonal timing, duration, and rate of change of streamflows needed to sustain freshwater and estuary ecosystems and human wellbeing. It is important that environmental streamflow assessments by water managers consider changes in climate, land use, and water management; this cannot be done effectively without understanding variability and changes in environmental streamflows over time and space. A limited amount of research of this type has been published. Estimates of environmental streamflows also are needed for ungaged streams; machine-learning methods are likely useful for this. We will analyze historical change and variability at hundreds of streamflow gages across the United States for a suite of environmental streamflows and use machine-learning methods to estimate environmental streamflows for thousands of ungaged stream reaches. The current project builds on previous projects that focused on a limited number of environmental flows, such as the magnitude of low flows and flood flows.
Statement of Problem:
It is important that environmental streamflow assessments consider climatic and watershed changes; however, this requires understanding historical variability and changes in environmental streamflows. There is no known published work that quantifies the variability and change for a full suite of environmental streamflows in the United States at the regional or continental scale. There are many commonly used environmental streamflows that have not been systematically analyzed, such as the number and duration of high and low pulses in each year and measures of the rate of change of streamflows from day to day.
Thousands of streams within the United States do not have directly measured streamflow values (normally from USGS streamgages). Models to predict environmental streamflows for ungaged streams are an important tool for water resource managers. Data-driven models using machine-learning methods are increasingly being applied in hydrologic science and achieve predictive skill comparable to, or greater than, traditional process-based modeling methods. It would be very useful to know whether machine-learning methods can better predict environmental streamflows for ungaged rivers than traditional methods.
Why this Research is Important:
Managers use estimates of environmental streamflows as targets to approximate various aspects of natural streamflows. They can reach these targets by controlling flow from reservoirs. Approximating natural flow promotes the health of fish and other aquatic species. Little is known, however, about the historical variability of environmental flows over time and space. Our work will substantially help define this variability and provide important context for managing streamflow now and in the future.
Objective(s):
- Characterize temporal and spatial patterns for a suite of environmental streamflows across the conterminous United States based on streamflow data from hundreds of long-term streamflow gages. The environmental streamflows will include metrics of streamflow magnitude, frequency, seasonal timing, duration, and rate of change.
- Develop machine-learning models to estimate environmental streamflows for ungaged streams across the conterminous United States and compare results to streamflows estimated from traditional methods.
- In addition, we will focus on environmental flows specifically relevant to migratory marine fish in selected regions of the U.S.
Methods:
We will use trend-testing methods to analyze changes over time and space in environmental streamflows and analyze how much variability is explained by atmosphere-ocean patterns such as the Pacific Decadal Oscillation and the North Atlantic Oscillation. We will consider how changes in climate, reservoir regulation, and urban and agricultural land uses have impacted environmental streamflows.
We will develop machine learning models using variables such as basin soil characteristics and land use, precipitation, and temperature data. Multiple methods will be considered and evaluated.
- Science
The Influence of Climatic, Watershed, and Water-use Changes on Extreme Low Streamflows in the United States
Extreme low streamflows impact water availability for human systems and ecosystems. Numerous researchers have analyzed trends in low streamflows in the U.S. There is no known published work, however, on historical trends over time in the most extreme low streamflows—the flows with the largest impacts on human systems and ecosystems. The current study attempts to fill this gap. The wealth of... - Publications
Climate-driven variability in the occurrence of major floods across North America and Europe
Concern over the potential impact of anthropogenic climate change on flooding has led to a proliferation of studies examining past flood trends. Many studies have analysed annual-maximum flow trends but few have quantified changes in major (25–100 year return period) floods, i.e. those that have the greatest societal impacts. Existing major-flood studies used a limited number of very large catchmeAuthorsGlenn A. Hodgkins, Paul H. Whitfield, Donald H. Burn, Jamie Hannaford, Benjamin Renard, Kerstin Stahl, Anne K. Fleig, Henrik Madsen, Luis Mediero, Johanna Korhonen, Conor Murphy, Donna WilsonTrends in snowmelt-related streamflow timing in the conterminous United States
Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal windAuthorsRobert W. Dudley, Glenn A. Hodgkins, Michael McHale, Michael J. Kolian, Benjamin RenardReference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends
Identifying climate-driven trends in river flows on a global basis is hampered by a lack of long, quality time series data for rivers with relatively undisturbed regimes. This is a global problem compounded by the lack of support for essential long-term monitoring. Experience demonstrates that, with clear strategic objectives, and the support of sponsoring organizations, reference hydrologic netwoAuthorsPaul H. Whitfield, Donald H. Burn, Jamie Hannaford, Hélène Higgins, Glenn A. Hodgkins, Terry Marsh, Ulrich LooserHistorical summer base flow and stormflow trends for New England rivers
River base flow is important to aquatic ecosystems, particularly because of its influence on summer water temperatures. Summer (June through September) daily mean streamflows were separated into base flow and stormflow components by use of an automated method at 25 stations in the New England region of the United States that drain predominantly natural basins. Summer monthly mean base flows increa
AuthorsGlenn A. Hodgkins, Robert W. DudleyStreamflow changes in Alaska between the cool phase (1947–1976) and the warm phase (1977–2006) of the Pacific Decadal Oscillation: The influence of glaciers
Streamflow data from 35 stations in and near Alaska were analyzed for changes between the cool phase (1947–1976) and the warm phase (1977–2006) of the Pacific Decadal Oscillation. Winter, spring, and summer flow changes and maximum annual flow changes were different for glaciated basins (more than 10% glacier‐covered area) than for nonglaciated basins, showing the influence of glaciers on historicAuthorsGlenn A. Hodgkins - News