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Input and results from boosted regression tree and artificial neural network models that predict daily maximum pH and daily minimum dissolved oxygen in Upper Klamath Lake, 2005-2019

Dates

Publication Date
Start Date
2005-08-09
End Date
2019-09-30

Citation

Wherry, S.A., and Schenk, L.N., 2023, Input and results from boosted regression tree and artificial neural network models that predict daily maximum pH and daily minimum dissolved oxygen in Upper Klamath Lake, 2005-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P971MB6W.

Summary

This data release contains the model inputs, outputs, and source code (written in R) for the boosted regression tree (BRT) and artificial neural network (ANN) models developed for four sites in Upper Klamath Lake which were used to simulate daily maximum pH and daily minimum dissolved oxygen (DO) from May 18th to October 4th in 2005-12 and 2015-19 at four sites, and to evaluate variable effects and their importance. Simulations were not developed for 2013 and 2014 due to a large amount of missing meteorological data. The sites included: 1) Williamson River (WMR), which was located in the northern portion of the lake near the mouth of the Williamson River and had a depth between 0.7 and 2.9 meters; 2) Rattlesnake Point (RPT), which [...]

Child Items (1)

Contacts

Point of Contact :
Susan Wherry
Originator :
Susan Wherry, Liam N Schenk
Metadata Contact :
Daniel R Wise
Publisher :
U.S. Geological Survey
Distributor :
U.S. Geological Survey - ScienceBase
SDC Data Owner :
Oregon Water Science Center
USGS Mission Area :
Water Resources

Attached Files

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klam_lake_brt_ann_models_metadata.xml
“Data release metadata file”
Original FGDC Metadata

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39.61 KB application/fgdc+xml
README.txt
“Describes contents of data release and instructions for running the models”
17.17 KB text/plain
cross_validation_holdout_years.csv
“List of years used for cross-validation training and hold-out testing by site”
1.92 KB text/csv
variable_list.csv
“List of variables in the model inputs with citations”
3.98 KB text/csv
klam_study_site_atts.csv
“Attributes for sites where data were collected and/or modeling was performed”
1.55 KB text/csv
model_programs.zip
“Compressed archive containing the model program files”
20.71 KB application/zip
model_output.zip
“Compressed archive containing the model output data files”
81.16 KB application/zip
model_input.zip
“Compressed archive containing the model input data files”
363.92 KB application/zip

Purpose

This data release provides the supporting information for the article “Examining the effect of physicochemical and meteorological variables on water quality indicators of harmful algal blooms in a shallow hypereutrophic lake using machine learning techniques” (https://doi.org/xxxxx).

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Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P971MB6W

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