Regionalization of surface-water statistics using multiple linear regression
This report serves as a reference document in support of the regionalization of surface-water statistics using multiple linear regression. Streamflow statistics are quantitative characterizations of hydrology and are often derived from observed streamflow records. In the absence of observed streamflow records, as at unmonitored or ungaged locations, other techniques are required. Multiple linear regression is one tool that is widely used to regionalize or transfer information from gaged to ungaged locations. This report provides the background to support regression-based regionalization of streamflow statistics. This background includes tools for data assembly, exploratory data analysis, model estimation in a least-squares framework, and model evaluation.
Citation Information
Publication Year | 2019 |
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Title | Regionalization of surface-water statistics using multiple linear regression |
DOI | 10.3133/tm4A12 |
Authors | William H. Farmer, Julie E. Kiang, Toby D. Feaster, Ken Eng |
Publication Type | Report |
Publication Subtype | USGS Numbered Series |
Series Title | Techniques and Methods |
Series Number | 4-A12 |
Index ID | tm4A12 |
Record Source | USGS Publications Warehouse |
USGS Organization | WMA - Integrated Modeling and Prediction Division |