Multivariate Elasticity of Extreme Streamflow in the United States. - Gumennik, Irina. (2017)
Abstract: Increasingly, hydrological research reveals that streamflow may be changing in response to changes in precipitation and land development. The concept of elasticity is used to investigate the generalized sensitivity of streamflow to changes in multiple basin characteristics. Multivariate regional regression models are developed for median annual high and low flows for 18 hydrologic units in the United States. The resulting coefficients of the multivariate regression models are shown to provide elasticity estimates for basin characteristics that capture several climatic, morphological, hydrological, and development influences on watersheds. Explanatory variables that consistently appear in the regression models reveal patterns that demonstrate the importance of employing a multivariate sensitivity approach. Regression estimates of precipitation elasticity based on single variable models are consistently biased when compared to more accurate multivariate approaches. Overall, precipitation and groundwater flow exhibit the strongest influence on streamflow with elasticity values that are an order of magnitude larger than for other explanatory variables. An increase in land development is associated with an increase in both high and low flows, but at an order of magnitude smaller compared to precipitation and groundwater.; Thesis (M.S.)--Tufts University, 2015.; Submitted to the Dept. of Civil Engineering.; Advisor: Richard Vogel.; Committee: Annalise Blum, and Jeffrey McCollum.; Keyword: Hydrologic sciences.