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Modeled daily salinity derived from multiple machine learning methodologies for 91 salinity monitoring sites in the northern Gulf of Mexico, 1980–2021

Dates

Publication Date
Start Date
1980-01-01
End Date
2021-12-31

Citation

Myers, R.D., Asquith, W.H., Banks, S.M., and Rodgers, K.D., 2024, Modeled daily salinity derived from multiple machine learning methodologies for 91 salinity monitoring sites in the northern Gulf of Mexico, 1980–2021: U.S. Geological Survey data release, https://doi.org/10.5066/P90GZAZU.

Summary

This data release consists of statistical predictions of daily salinity time series generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope includes the predictions for 91 locations within bays and estuaries of the Gulf of Mexico, United States. The 91 locations are organized across 15 salinity groups and represented in the organizational structure of this data release. The input data files of imputed salinity (observations, response variable) and covariates (predictor variables) for the makESTUSAL [...]

Child Items (15)

Contacts

Point of Contact :
William H Asquith
Process Contact :
William H Asquith
Originator :
Ryder D Myers, William H Asquith, Sarah M Banks, Kirk D Rodgers
Metadata Contact :
Ryder D Myers
Publisher :
U.S. Geological Survey
SDC Data Owner :
Lower Mississippi-Gulf Water Science Center
USGS Mission Area :
Water Resources
Distributor :
U.S. Geological Survey - ScienceBase

Attached Files

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Purpose

The purpose of this dataset is to provide to the terminal output from statistical prediction of daily salinity values for locations along the Gulf Coast, United States for relay to other science endeavors.

Map

Spatial Services

ScienceBase WMS

Communities

  • USGS Data Release Products
  • USGS Lower Mississippi-Gulf Water Science Center

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Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P90GZAZU

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