Graduation Year


Document Type




Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department


Major Professor

Mark Rains, Ph.D.

Co-Major Professor

Mark T. Stewart, Ph.D.

Committee Member

Mahmood Nachabe, Ph.D.

Committee Member

Kenneth Trout, Ph.D.


Ground water, Hydrograph, Runoff, Specific conductance


Freshwater for ecosystems, drinking water, and water for various businesses are important resources and those resources are rapidly diminishing globally due to drought and overuse. In order to manage the availability of water for all concerned, good estimates of base flow (groundwater) is required. Base flow, a component of streamflow, is deduced by separating a stream hydrograph into two components, base flow and runoff. There are several techniques used to perform base flow separation; however two techniques are used in this study, chemical mass-balance and analytical methods. This dissertation explains how an analytical technique was derived from a mass-balance method, how that particular analytical method compares to several other analytical techniques, also the analytical and mass-balance method used with discrete data.

Chapter 2 explains how an analytical method, termed the power function method (PFM) in the form of aQb + cQ, was derived from the mass-balance technique called the conductivity mass-balance (CMB) method. Regardless of the method used to separate base flow, calibration is needed at each specific gage. The PFM or any other analytical base flow separation method is not as sensitive to base flow suppression at high discharges as the CMB method therefore, analytical methods may overestimate base flow at high discharges. Applying regionally–averaged coefficients of the PFM or uncalibrated analytical methods to estimate base flow may provide unreasonable large errors. The coefficients of the PFM are acquired from stream flow conductance obtained over many storm events. For single events, the PFM is not as accurate as the CMB or other tracer methods. It is more appropriate for assessing base flow contributions over longer periods than single events. However, the PFM coefficients are derived directly from a basin and gage dependent variable, specific conductance and use of the PFM for single events is more justifiable than applying uncalibrated analytical methods.

Chapter 3 compares six analytical base flow separation techniques to Stewart et al. (2007) conductivity mass-balance (CMB) method. Seven methods were used to determine the base flow index value (BFI) on 35 stream gages with each gage having two years of specific conductance data and 30 years of continuous discharge data. Base flow index is dimensionless and varies between 0 and 1. One of the six analytical base flow methods, the power function (aQb + cQ), is inherently calibrated and returns similar results as mass balance techniques. After calibrating the other analytical methods, they were able to replicate CMB base flow values. The results of this study suggest that analytical base flow method should be calibrated against a tracer or mass balance method.

Chapter 4 determines if base flow separation can be accomplished using discrete data instead of continuous data. The data from stream gages of the previous studies, Chapter 2 and Chapter 3, have over two years of continuously collected specific conductance data, however the norm at stream gage sites is discrete geochemical data.