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Observations Documenting Premature Mortality Among Alaska's Pacific Salmon in 2019 Observations Documenting Premature Mortality Among Alaska's Pacific Salmon in 2019
These data are a compilation of geographically widespread observations of premature mortality in Pacific salmon across their range in Alaska in 2019. Premature mortality observations primarily spanned an area of western and southcentral Alaska that is approximately one million km2 and included all five species of Pacific salmon. Observations were obtained and compiled in a single...
USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics Data USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics Data
This package contains gravity and magnetics data and products generated for the Nevada Machine Learning (NVML) project (DE-FOA-0001956). Data products contained in this release consist of grids and vector data. Grids include: primary anomaly maps (isostatic and PSG), match-filtered maps, horizontal gradient (HG) maps, confidence maps, and maps showing density of specific key structural...
USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics, Heat Flow, Slip and Dilation Tendency USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics, Heat Flow, Slip and Dilation Tendency
This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project (DE-FOA-0001956), with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geophysics, heat flow, and fault dilation and slip tendencies) that cover a large portion of...
USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data
This package contains a map surface that depicts the estimated spatial variation of conductive heat flow (mW/m?) in a portion of northern Nevada, the extent of the ?Nevada Machine Learning Project? (DE-EE0008762). It was generated using well locations that had an estimated heat flow value from a measured thermal gradient and thermal conductivity, mainly using data from Southern Methodist
USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Slip and Dilation Tendency Data USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Slip and Dilation Tendency Data
This package contains data in a portion of northern Nevada, the extent of the ?Nevada Machine Learning Project? (DE-EE0008762). Slip tendency (TS) and dilation tendency (TD) were calculated for the all the faults in the Nevada ML study area. TS is the ratio between the shear components of the stress tensor and the normal components of the stress tensor acting on a fault plane. TD is the...
Hydrologic Data Collected at Leaky Weirs, Cienega Ranch, Willcox, AZ (March 2019 - October 2020) Hydrologic Data Collected at Leaky Weirs, Cienega Ranch, Willcox, AZ (March 2019 - October 2020)
This dataset contains hydrological data collected at a series of leaky weirs on a working ranchland site in a semiarid ecosystem in Cochise County, Arizona, from 2018-2020. Leaky weirs are a type of structure being experimented with by land managers in aridlands to reduce peak flow events and increase recharge to the aquifer. The weirs are constructed of rock cemented into place in areas...