Luke Sturtevant
Luke Sturtevant is a Physical Scientist in the New England Water Science Center.
Science and Products
Filter Total Items: 14
Thirty- and ninety-year data sets of streamflow, groundwater recharge, and snowfall simulating potential hydrologic response to climate change in the 21st century in New Hampshire
The U.S. Geological Survey (USGS), in cooperation with the New Hampshire Department of Environmental Services (NHDES) and the Department of Health and Human Services (NHDHHS), has developed tools to assess the effects of short- and long-term climate change on hydrology in New Hampshire. A USGS Scientific Investigations Report (SIR) report documents tools and datasets developed by the USGS to (1) p
Data validating computation of boundary roughness from QL2 lidar derived digital elevation models for 2D hydraulic modeling applications
Calibration of hydraulic models require careful selection of input parameters to provide the best possible modeling outcome. Currently the selection of hydraulic resistance or 'n' values for these models is a subjective process potentially exposing models to critical review . A process is needed to objectively estimate n-values so everyone responsible for model calibration arrives at the same an
Science and Products
Filter Total Items: 14
Thirty- and ninety-year data sets of streamflow, groundwater recharge, and snowfall simulating potential hydrologic response to climate change in the 21st century in New Hampshire
The U.S. Geological Survey (USGS), in cooperation with the New Hampshire Department of Environmental Services (NHDES) and the Department of Health and Human Services (NHDHHS), has developed tools to assess the effects of short- and long-term climate change on hydrology in New Hampshire. A USGS Scientific Investigations Report (SIR) report documents tools and datasets developed by the USGS to (1) p
Data validating computation of boundary roughness from QL2 lidar derived digital elevation models for 2D hydraulic modeling applications
Calibration of hydraulic models require careful selection of input parameters to provide the best possible modeling outcome. Currently the selection of hydraulic resistance or 'n' values for these models is a subjective process potentially exposing models to critical review . A process is needed to objectively estimate n-values so everyone responsible for model calibration arrives at the same an