Estimating records of daily streamflow at ungaged locations in the southeast United States.
assessment and measurement of streamflow is essential to responsible and sustainable
management of the freshwater resources upon which our civilization depends. Streamflow
is typically monitored via streamgages, but these provide only a finite record of
streamflow in space and time. Continued economic development requires reliable
hydrologic information beyond the spatial ... read moreand temporal limits of physical streamgages.
Several methods are developed here to estimate daily streamflow records, at sparsely
gaged and completely ungaged locations. Though applicable globally, all tools are
developed on and analyses are conducted in unregulated basins in the southeast United
States. First, a comprehensive analysis of the spatial structure of daily streamflow
shows that the full range of the distribution of streamflow can only be assessed when
both positive and negative moment orders are considered. An exploration of the spatial
scaling of streamflow indicates that multiple regressions are needed to understand
hydrologic response. Coupling these findings with the behavior of flow duration curves
(FDCs) provides a hydrologic spatial scaling signature that characterizes regional
hydrologic response. In a parallel study, a robust rank-based evaluation technique is
introduced as a tool for assessing the performance of 19 alternative estimators of
spatially and temporally continuous daily streamflow records. Statistical,
direct-transfer techniques are contrasted with mechanistic rainfall-runoff models.
Methods for prediction are evaluated in terms of day-by-day performance as well as the
ability to reproduce streamflow signatures and other streamflow statistics. Streamflow
records estimated with a non-linear spatial interpolation using FDCs are shown to
perform better than existing alternatives. Finally, a new method of hydrologic kriging
is introduced; this technique leverages the spatial structure of daily streamflow to
provide continuous estimates of daily streamflow. Hydrologic kriging is shown to be
superior to previous, standard methods, while additionally providing uncertainty
estimates and a framework for understanding the mechanistic connections across
hydrologic landscapes. Motivating future research, initial analyses of the temporal
variability of spatial structure are explored. Coupling of hydrologic kriging and
mechanistic rainfall-runoff models is presented as an avenue towards improved hydrologic
understanding of ungaged regions.
Thesis (Ph.D.)--Tufts University, 2015.
Submitted to the Dept. of Civil Engineering.
Advisor: Richard Vogel.
Committee: Julie Kiang, Kenneth Strzepek, and Laurie Baise.
Keywords: Hydrologic sciences, Water resources management, and Environmental engineering.read less