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

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 was located near the southern portion of the lake and had a depth between 1.9 and 3.4 meters; 3) Mid-North (MDN), which was located in the northwest portion of the lake and a depth between 2.4 and 4.2 meters; 4) Mid-Trench (MDT) , which was located in the trench that runs along the western portion of the lake and had a depth between 13.2 and 15 meters.