Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Phillip Goodling
Phillip Goodling is a hydrologist in the Water Budget Branch (Earth System Processes Division) of the US Geological Survey Water Resources Mission Area. He joined the US Geological Survey in 2018 and joined the Water Resources Mission Area in 2023.
Phillip's research interests include:
- Machine learning and artificial intelligence applications in the geosciences
- Characterizing and forecasting drought
- Karst groundwater systems
- Building tools and pipelines for reproducible data analysis
- Low-cost and non-contact sensor systems
Science and Products
North Atlantic-Appalachian AI/ML Capabilities
Artificial Intelligence (AI) and Machine Learning (ML) includes a broad suite of flexible data-driven empirical approaches to perform tasks that are difficult to implement using conventional methods. AI and ML harness the power of computing resources to evaluate the underlying patterns and relationships within a dataset without explicit instructions. The North Atlantic-Appalachian AI/ML Capability...
Eyes On Streams - The Short Story
Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Eyes On Streams - The Short Story (AD)
Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer
Imagery as Streamflow Data: Introducing the USGS Flow Photo ExplorerFlow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer
Imagery as Streamflow Data: Introducing the USGS Flow Photo ExplorerFlow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Science and Products
North Atlantic-Appalachian AI/ML Capabilities
Artificial Intelligence (AI) and Machine Learning (ML) includes a broad suite of flexible data-driven empirical approaches to perform tasks that are difficult to implement using conventional methods. AI and ML harness the power of computing resources to evaluate the underlying patterns and relationships within a dataset without explicit instructions. The North Atlantic-Appalachian AI/ML Capability...
Eyes On Streams - The Short Story
Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Eyes On Streams - The Short Story (AD)
Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer
Imagery as Streamflow Data: Introducing the USGS Flow Photo ExplorerFlow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer
Imagery as Streamflow Data: Introducing the USGS Flow Photo ExplorerFlow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)
Imagery as Streamflow Data: Introducing the USGS Flow Photo Explorer (AD)Flow is a critical variable in streams since it affects aquatic and riparian biological communities and human uses of water (i.e., recreation, public water supply, etc.). Flow regimes are changing due to anthropogenic (e.g., water withdrawals) and natural impacts (e.g., extreme weather events).