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7Q10 records and basin characteristics for 224 basins in South Carolina, Georgia, and Alabama (2015)

August 3, 2017

This data release provides the data and R scripts used for the 2017 submitted publication titled "Improving predictions of hydrological low-flow indices in ungaged basins using machine learning". There are two .csv files and 14 R-scripts included below. The lowflow_sc_ga_al_gagesII_2015.csv datafile contains the annual minimum seven-day mean streamflow with an annual exceedance probability of 90% (7Q10) for 224 basins in South Carolina, Georgia, and Alabama. The datafile also contains 231 basin characteristics from the Gages II dataset (https://water.usgs.gov/lookup/getspatial?gagesII_Sept2011). The "all_preds.csv" file contains the leave-one-out cross validated predictions for all the models. The paper associated with the data release compares the ability of eight machine-learning models (elastic net, gradient boosting, kernel-k-nearest neighbors, two variants of support vector machines, M5-cubist, random forest, and a meta-learning ensemble M5-cubist model) and four baseline models (ordinary kriging, a unit-area discharge model, and two variants of censored regression) to generate estimates of the 7Q10 at 224 unregulated sites in South Carolina, Georgia, and Alabama.

Citation Information

Publication Year 2017
Title 7Q10 records and basin characteristics for 224 basins in South Carolina, Georgia, and Alabama (2015)
DOI 10.5066/F7CR5S4T
Authors Worland Scott C., Farmer William H., Kiang Julie E
Product Type Data Release
Record Source USGS Digital Object Identifier Catalog
USGS Organization Lower Mississippi-Gulf Water Science Center

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