During the past decades, U.S. Environmental Protection Agency (EPA), U.S. Department of Agriculture (USDA) and other Federal program administrative and regulatory agencies spent considerable amounts of time and money to manage risks to surface waters associated with agricultural activities, urbanization and other avenues of nonpoint source pollution. A variety of best management practices (BMPs) exist for this purpose and have been installed throughout the country, yet very little is known about their overall effectiveness in reducing stressors at the watershed scale. The objective of this research is to explore and develop uniform methods for simple quantification of hydrology and water quality data, focusing on watersheds containing agricultural BMPs. A significant motivation for the research is to provide tools that can be used to identify and quantify the major factors that connect watershed hydrology and water quality (such as climate, soil type, slope, land use). These connecting factors are important for evaluating the effectiveness of agricultural and other BMPs, because they often determine stream and stressor management decisions. Research methods must take into account natural variability and uncertainty in watershed response to BMP installation and precipitation events.