Date of Award

May 2013

Degree Type

Thesis

Degree Name

Master of Science

Department

Geography

First Advisor

Woonsup Choi

Committee Members

Mark D. Schwartz, Glen G. Fredlund

Keywords

Great Lakes Basin, Hydrologic Response, Prediction in Ungaged Basin, Regionalization, Regression Model, Runoff

Abstract

Methods for predicting streamflow in areas with limited or nonexistent measures of hydrologic response commonly rely on regionalization techniques, where knowledge pertaining to gaged watersheds is transferred to ungaged watersheds. Hydrologic response indices have frequently been employed in contemporary regionalization research related to predictions in ungaged basins. In this study, regionalization models were developed using multiple linear regression and regression tree analysis to derive relationships between hydrologic response and watershed physical characteristics for 163 watersheds in the Great Lakes basin. These models provide a means for predicting runoff in ungaged basins at a monthly time step without implementation of any process-based rainfall-runoff model. Major findings from this research study include (1) Monthly runoff in ungaged watersheds was predicted with reasonable skill using regression-based relationships between runoff ratio and watershed physical characteristics; (2) Predictions in ungaged watersheds were highly influenced by the temporal characterization of runoff ratio used to condition the regression models; (3) Watershed classification using regression tree and multiple linear regression techniques resulted in comparable model predictive skill.

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