Through the National Water Census, USGS will provide national information on withdrawal, conveyance, consumptive use, and return flow by water-use category at spatial and temporal resolutions important for risk-informed water management decisions. Water-use data provide a foundation for water managers to analyze trends over time, plan more strategically, identify, and ultimately quantify vulnerability thresholds for adaptive water management. These data are vital to water-availability studies and assessments which seek to evaluate the balance between supply and demand and the relative influence of individual components in affecting that balance and achieving water security.
National Water Use Estimates
The U.S. Geological Survey is developing a combination of physics-based and data-driven models that rely on artificial intelligence/machine learning to estimate water withdrawal and consumptive use, replacing the previously used method of compiling and reviewing available data and making estimates to complete a national picture every 5-years. These models will allow for a consistent and more frequent reporting of water use information with an enhanced understanding of how water is used and what influences the variation in time and space. The models will be useful in identifying data gaps and data quality issues which in turn will inform future data collection and ultimately improve model predictions.
General model design requirements include:
- National scope (States and territories)
- Predict annual and sub-seasonal water withdrawals and consumptive use for publicly supplied and self-supplied water use for a historical period, near real-time conditions (1–2-month latency), short-term (months-to-years) and long-term (years-to-decades) forecasts and that can be regularly refreshed.
- 12-digit hydrologic unit code level watershed resolution
- Differentiate between water source (groundwater, surface water, water reuse)
- Incorporate quality-assured State and Federal agency data, where available.
Models for each use category will rely on different design strategies and development timelines following a set of prioritization factors, including the proportion of water use relative to the nation’s total water use, availability of data, availability of established modeling theories, and understanding of drivers of water use for each category. Model enhancements will be made to incorporate new data products and technological advancements in water use estimation research to maintain the highest levels of accuracy necessary to best align with water resource decision maker’s needs.
Development of models for the three categories that represent over 90% of total water use nationally--public supply, self-supplied thermoelectric power, and self-supplied crop irrigation--are underway. Withdrawal estimates for a 20-year reanalysis period of 2000 to 2020 for these three largest water use categories are anticipated for publication in early 2023. The estimates are for each month of that 20-year period for all watersheds at the 12-digit hydrologic unit code level in the continental United States. Other categories of use (self-supplied industrial, domestic, mining, livestock, aquaculture, and golf irrigation) will be available near the end of 2024, as the development of those models will be started in late 2022. All models will include Alaska, Hawaii, Puerto Rico, and the U.S. Virgin Islands and will be enhanced as new data and understanding is gained.
Models by Category
Public Water Supply
Statistical models, including machine learning, are being developed for estimating withdrawals and consumptive use for public supply water use. These models are data intensive and rely heavily on State, Federal and local information. To model public-supply water use effectively and accurately an understanding of the geographic extent of each system’s customer base (service area) and demographics are required. Information is needed that links the sources of water to the systems, the volume of water delivered to domestic and other uses (commercial, industrial, irrigation, and thermoelectric power), the water losses that happen during transport, and a multitude of climatic, economic, and social variables that influence public supply water use.
Thermoelectric Power (TE)
A hybrid physics-based and machine learning modeling approach is being used to characterize plant operations and water use requirements for near-real-time estimates and future forecasts. These models add capability to the physics-based models previously developed by the USGS in collaboration with the U.S. Energy Information Administration (EIA).
For each plant, the physics-based models calculate monthly and annual estimates of withdrawal and consumptive use based on linked heat-and-water-budget understanding that are constrained by power plant fuel consumption, electricity generation, cooling-system technology and environmental variables (air and water temperatures, wind speed, and elevation). Although processes and plant characteristics that affect water use are well developed and represented by the physics-based model, data requirements including gross electricity generation and fuel heat which are provided by the EPA and EIA are released quarterly. To provide a TE model that can estimate near-real-time and forecasted withdrawals, machine learning approaches are being used to predict gross electrical generation and fuel heat.
- Diel, T.H., Harris, M., Murphy, J.C., Hutson, S.S., and Ladd, D.E., 2013, Methods for estimating water consumption for thermoelectric power plants in the United States: U.S. Geological Survey Scientific Investigations Report 2013-5188, 78 p.
- Harris, M.A. and Diehl, T.H., 2017, A Comparison of Three Federal Datasets for Thermoelectric Water Withdrawals in the United States for 2010, Journal of the American Water Resources Association, Vol. 53, Issue 5, p. 1062-1080.
Irrigation
Models for estimating and identifying irrigated lands, crop water requirements, irrigation system types and efficiencies, and source-water information are all needed to construct high spatial and temporal-scale estimates of irrigation water use. Satellite-based surface energy balance models and a hydrologic soil-water balance model are coupled to calculate crop water consumption and applied irrigation. Crops get their water as a mixture of natural precipitation and applied irrigation and depending on the amount and timing of precipitation relative to the growing season, irrigation water requirements can be highly variable. The amount of water withdrawn relies on an understanding of irrigation system type and water conveyance efficiencies. Estimates for irrigated golf courses will be added to the model design after 2022.
Mining
Model development will begin in 2023 and will include minerals mining as well as oil and gas extraction activity. The information gained from model development for continuous oil and gas water use will be incorporated into the new modeling efforts, and methods developed for previous USGS county-scale mining estimates will be evaluated for inclusion.
Industrial
Model development will begin in 2023.
Livestock and Aquaculture
Model development will begin in 2023 and will include an evaluation of methods developed for previous USGS county-scale estimates.
- Lovelace, J.K., 2009, Method for Estimating Water Withdrawals for Livestock in the United States, 2005: U.S. Geological Survey Scientific Investigations Report 2009-5041, 7 p.
- Lovelace, J.K., 2009, Method for Estimating Water Withdrawals for Aquaculture in the United States, 2005: U.S. Geological Survey Scientific Investigations Report 2009-5042, 13 p.
Self-Supplied Domestic
Model development will begin in 2023 and will include an evaluation of methods developed for the public supply model and previous USGS approaches for quantifying domestic water use.
Water Use Data and Research Program
Water managers across the United States require more complete, timely, and accurate water-availability information to support policy and decision-making, specifically, data associated with water withdrawals and consumptive use. Recognizing the limitations of current water-use data, the SECURE Water Act authorized a program that supports activities related to data collection and methods research and development at the State level. The USGS Water-Use Data and Research program (WUDR) provides financial assistance through cooperative agreements with State water resource agencies to improve the availability, quality, compatibility, and delivery of water-use data that is collected or estimated by States.
Find out more about the Water Use Data and Research Program
Water Use Cooperative Matching Funds
Cooperative matching funds (CMF) are matched with State, local and tribal funds to work with partners to solve complex water resource issues in their area of interest and that serve the Federal interest. Many of the collaborative projects being performed across the country are funded at a 2:1 or 3:1 ratio by the participating cooperative entities. This is a testament to the value local, State and tribal cooperators place on the scientific contributions from the USGS. Cooperative projects funded by water-use research CMF typically address water use and the impacts that use has on hydrology and water allocations.
Learn more about the National Water Census.
National Water Census
- Overview
Through the National Water Census, USGS will provide national information on withdrawal, conveyance, consumptive use, and return flow by water-use category at spatial and temporal resolutions important for risk-informed water management decisions. Water-use data provide a foundation for water managers to analyze trends over time, plan more strategically, identify, and ultimately quantify vulnerability thresholds for adaptive water management. These data are vital to water-availability studies and assessments which seek to evaluate the balance between supply and demand and the relative influence of individual components in affecting that balance and achieving water security.
National Water Use Estimates
The U.S. Geological Survey is developing a combination of physics-based and data-driven models that rely on artificial intelligence/machine learning to estimate water withdrawal and consumptive use, replacing the previously used method of compiling and reviewing available data and making estimates to complete a national picture every 5-years. These models will allow for a consistent and more frequent reporting of water use information with an enhanced understanding of how water is used and what influences the variation in time and space. The models will be useful in identifying data gaps and data quality issues which in turn will inform future data collection and ultimately improve model predictions.
General model design requirements include:
- National scope (States and territories)
- Predict annual and sub-seasonal water withdrawals and consumptive use for publicly supplied and self-supplied water use for a historical period, near real-time conditions (1–2-month latency), short-term (months-to-years) and long-term (years-to-decades) forecasts and that can be regularly refreshed.
- 12-digit hydrologic unit code level watershed resolution
- Differentiate between water source (groundwater, surface water, water reuse)
- Incorporate quality-assured State and Federal agency data, where available.
Models for each use category will rely on different design strategies and development timelines following a set of prioritization factors, including the proportion of water use relative to the nation’s total water use, availability of data, availability of established modeling theories, and understanding of drivers of water use for each category. Model enhancements will be made to incorporate new data products and technological advancements in water use estimation research to maintain the highest levels of accuracy necessary to best align with water resource decision maker’s needs.
Development of models for the three categories that represent over 90% of total water use nationally--public supply, self-supplied thermoelectric power, and self-supplied crop irrigation--are underway. Withdrawal estimates for a 20-year reanalysis period of 2000 to 2020 for these three largest water use categories are anticipated for publication in early 2023. The estimates are for each month of that 20-year period for all watersheds at the 12-digit hydrologic unit code level in the continental United States. Other categories of use (self-supplied industrial, domestic, mining, livestock, aquaculture, and golf irrigation) will be available near the end of 2024, as the development of those models will be started in late 2022. All models will include Alaska, Hawaii, Puerto Rico, and the U.S. Virgin Islands and will be enhanced as new data and understanding is gained.
Models by Category
Public Water Supply
Statistical models, including machine learning, are being developed for estimating withdrawals and consumptive use for public supply water use. These models are data intensive and rely heavily on State, Federal and local information. To model public-supply water use effectively and accurately an understanding of the geographic extent of each system’s customer base (service area) and demographics are required. Information is needed that links the sources of water to the systems, the volume of water delivered to domestic and other uses (commercial, industrial, irrigation, and thermoelectric power), the water losses that happen during transport, and a multitude of climatic, economic, and social variables that influence public supply water use.
Thermoelectric Power (TE)
A hybrid physics-based and machine learning modeling approach is being used to characterize plant operations and water use requirements for near-real-time estimates and future forecasts. These models add capability to the physics-based models previously developed by the USGS in collaboration with the U.S. Energy Information Administration (EIA).
For each plant, the physics-based models calculate monthly and annual estimates of withdrawal and consumptive use based on linked heat-and-water-budget understanding that are constrained by power plant fuel consumption, electricity generation, cooling-system technology and environmental variables (air and water temperatures, wind speed, and elevation). Although processes and plant characteristics that affect water use are well developed and represented by the physics-based model, data requirements including gross electricity generation and fuel heat which are provided by the EPA and EIA are released quarterly. To provide a TE model that can estimate near-real-time and forecasted withdrawals, machine learning approaches are being used to predict gross electrical generation and fuel heat.
- Diel, T.H., Harris, M., Murphy, J.C., Hutson, S.S., and Ladd, D.E., 2013, Methods for estimating water consumption for thermoelectric power plants in the United States: U.S. Geological Survey Scientific Investigations Report 2013-5188, 78 p.
- Harris, M.A. and Diehl, T.H., 2017, A Comparison of Three Federal Datasets for Thermoelectric Water Withdrawals in the United States for 2010, Journal of the American Water Resources Association, Vol. 53, Issue 5, p. 1062-1080.
Irrigation
Models for estimating and identifying irrigated lands, crop water requirements, irrigation system types and efficiencies, and source-water information are all needed to construct high spatial and temporal-scale estimates of irrigation water use. Satellite-based surface energy balance models and a hydrologic soil-water balance model are coupled to calculate crop water consumption and applied irrigation. Crops get their water as a mixture of natural precipitation and applied irrigation and depending on the amount and timing of precipitation relative to the growing season, irrigation water requirements can be highly variable. The amount of water withdrawn relies on an understanding of irrigation system type and water conveyance efficiencies. Estimates for irrigated golf courses will be added to the model design after 2022.
Mining
Model development will begin in 2023 and will include minerals mining as well as oil and gas extraction activity. The information gained from model development for continuous oil and gas water use will be incorporated into the new modeling efforts, and methods developed for previous USGS county-scale mining estimates will be evaluated for inclusion.
Industrial
Model development will begin in 2023.
Livestock and Aquaculture
Model development will begin in 2023 and will include an evaluation of methods developed for previous USGS county-scale estimates.
- Lovelace, J.K., 2009, Method for Estimating Water Withdrawals for Livestock in the United States, 2005: U.S. Geological Survey Scientific Investigations Report 2009-5041, 7 p.
- Lovelace, J.K., 2009, Method for Estimating Water Withdrawals for Aquaculture in the United States, 2005: U.S. Geological Survey Scientific Investigations Report 2009-5042, 13 p.
Self-Supplied Domestic
Model development will begin in 2023 and will include an evaluation of methods developed for the public supply model and previous USGS approaches for quantifying domestic water use.
Water Use Data and Research Program
Water managers across the United States require more complete, timely, and accurate water-availability information to support policy and decision-making, specifically, data associated with water withdrawals and consumptive use. Recognizing the limitations of current water-use data, the SECURE Water Act authorized a program that supports activities related to data collection and methods research and development at the State level. The USGS Water-Use Data and Research program (WUDR) provides financial assistance through cooperative agreements with State water resource agencies to improve the availability, quality, compatibility, and delivery of water-use data that is collected or estimated by States.
Find out more about the Water Use Data and Research Program
Water Use Cooperative Matching Funds
Cooperative matching funds (CMF) are matched with State, local and tribal funds to work with partners to solve complex water resource issues in their area of interest and that serve the Federal interest. Many of the collaborative projects being performed across the country are funded at a 2:1 or 3:1 ratio by the participating cooperative entities. This is a testament to the value local, State and tribal cooperators place on the scientific contributions from the USGS. Cooperative projects funded by water-use research CMF typically address water use and the impacts that use has on hydrology and water allocations.
- Science
Learn more about the National Water Census.
National Water Census
The National Water Census will deliver routinely updated water availability information in the United States. - Publications