Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

Dataset · Sat Jan 01 00:00:00 EST 2022

DOI:https://doi.org/10.15485/1854257· OSTI ID:1854257

Weierbach, Helen  ^[1]; Lima, Aranildo R.  ^[2]; Willard, Jared D.  ^[1]; Hendrix, Valerie C.  ^[1]; Christianson, Danielle S.  ^[1]; Lubich, Misha  ^[3]; Varadharajan, Charuleka  ^[1]

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1. Lawrence Berkeley National Laboratory
2. Aquatic Informatics
3. University of California Berkeley

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

• Research Organization: Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) (United States); Investigating the Impacts of Streamflow Disturbances on Water Quality Using a Data-Driven Framework
• Sponsoring Organization: U.S. DOE > Office of Science > Biological and Environmental Research (BER)
• OSTI ID: 1854257
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY
Machine Learning
XGBoost
Support Vector Regression
Stream Water Temperature
Catchments
Modeling
Predictions in Unmonitored Basins
ESS-DIVE File Level Metadata Reporting Format
EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > WATER TEMPERATURE
EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER > SURFACE WATER PROCESSES/MEASUREMENTS > DISCHARGE/FLOW
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC RADIATION > SOLAR RADIATION
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > SURFACE TEMPERATURE > MAXIMUM/MINIMUM TEMPERATURE
EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION AMOUNT