The responsibility for mitigation of the ecological effects of urban stormwater runoff has been delegated to local government authorities through the Clean Water Act's National Pollutant Discharge Elimination Systems' Stormwater (NPDES SW), and Total Maximum Daily Load (TMDL) programs. These programs require that regulated entities reduce the discharge of pollutants from their storm drain systems to the "maximum extent practicable" (MEP), using a combination of structural and non-structural stormwater treatment — known as stormwater control measures (SCMs). The MEP regulatory paradigm acknowledges that there is empirical uncertainty regarding SCM pollutant reduction capacity, but that by monitoring, evaluation, and learning, this uncertainty can be reduced with time. The objective of this dissertation is to demonstrate the existing sources and magnitude of variability and uncertainty associated with the use of structural and non-structural SCMs towards the MEP goal, and to examine the extent to which the MEP paradigm of iterative implementation, monitoring, and learning is manifest in the current outcomes of the paradigm in Virginia. To do this, three research objectives were fulfilled. First, the non-structural SCMs employed in Virginia in response to the second phase of the NPDES SW program were catalogued, and the variability in what is considered a "compliant" stormwater program was evaluated. Next, the uncertainty of several commonly used stormwater flow measurement devices were quantified in the laboratory and field, and the importance of this uncertainty for regulatory compliance was discussed. Finally, the third research objective quantified the uncertainty associated with structural SCMs, as a result of measurement error and environmental stochasticity. The impacts of this uncertainty are discussed in the context of the large number of structural SCMs prescribed in TMDL Implementation Plans. The outcomes of this dissertation emphasize the challenge that empirical uncertainty creates for cost-effective spending of local resources on flood control and water quality improvements, while successfully complying with regulatory requirements. The MEP paradigm acknowledged this challenge, and while the findings of this dissertation confirm the flexibility of the MEP paradigm, they suggest that the resulting magnitude of SCM implementation has outpaced the ability to measure and functionally define SCM pollutant removal performance. This gap between implementation, monitoring, and improvement is discussed, and several potential paths forward are suggested. / Ph. D.