Assessment of Water Availability and Streamflow Characteristics in the Southeastern U.S. for Current and Future Climatic and Landscape Conditions
Information about streamflow and streamflow variability is critical to assist natural resource managers when they make decisions related to the water needs of both human communities and ecosystems. In order for managers to effectively plan for and adapt to future climate and land cover conditions, they require information on changes that could occur in the distribution and quantity of water resources. Yet every watershed has a unique set of characteristics – such as differing topographies and geology – that affect how much water is available, the sources of water, and how it flows through the system. This means that water availability in every watershed can be affected differently by changes in climate and land cover.
Flow can be monitored in a stream using a stream gage, which provides information about the amount and variability of surface water resources at a particular location. However, not every stream has a gage, and decisions about water resources in these ungaged watersheds still must be made. In the absence of measured streamflow information, hydrologic models can be used to provide estimates of streamflow characteristics. This project will use a modeling approach that groups watersheds that are gaged with watersheds that are not gaged to provide accurate estimates of water availability for all watersheds in the southeastern United States, under current and potential future climate and land cover conditions.
This work supports Secretary of Interior’s priority to create a conservation stewardship legacy by utilizing science to identify best practices for managing land and water resource and adapting to changes in the environment. For example, the National Park Service is currently assessing the hydrologic conditions of all national parks, and the results of this study can support this effort by providing information on current and potential future changes to water availability in the Southeast.
- Source: USGS Sciencebase (id: 5b9ffcbae4b08583a5c2776f)
Information about streamflow and streamflow variability is critical to assist natural resource managers when they make decisions related to the water needs of both human communities and ecosystems. In order for managers to effectively plan for and adapt to future climate and land cover conditions, they require information on changes that could occur in the distribution and quantity of water resources. Yet every watershed has a unique set of characteristics – such as differing topographies and geology – that affect how much water is available, the sources of water, and how it flows through the system. This means that water availability in every watershed can be affected differently by changes in climate and land cover.
Flow can be monitored in a stream using a stream gage, which provides information about the amount and variability of surface water resources at a particular location. However, not every stream has a gage, and decisions about water resources in these ungaged watersheds still must be made. In the absence of measured streamflow information, hydrologic models can be used to provide estimates of streamflow characteristics. This project will use a modeling approach that groups watersheds that are gaged with watersheds that are not gaged to provide accurate estimates of water availability for all watersheds in the southeastern United States, under current and potential future climate and land cover conditions.
This work supports Secretary of Interior’s priority to create a conservation stewardship legacy by utilizing science to identify best practices for managing land and water resource and adapting to changes in the environment. For example, the National Park Service is currently assessing the hydrologic conditions of all national parks, and the results of this study can support this effort by providing information on current and potential future changes to water availability in the Southeast.
- Source: USGS Sciencebase (id: 5b9ffcbae4b08583a5c2776f)