The efficiency of a best management practice (BMP) is defined simply as a measure of how well the practice or series of practices removes targeted pollutants. While this concept is relatively simple, mathematical attempts to quantify BMP efficiency are numerous and complex. Intuitively, the pollutant removal capability of a BMP should be fundamental to the BMP selection process. However, as evidenced by the absence of removal efficiency as an influential criterion in many BMP selection procedures, it is typically not at the forefront of the BMP selection and design process. Additionally, of particular interest to any developer or municipal agency is the financial impact of implementing a BMP. Not only does the implementation cost exist, but there are long-term maintenance costs associated with almost any BMP. Much like pollutant removal efficiency, implementation and maintenance costs seem as though they should be integral considerations in the BMP selection process. However, selection flow charts and matrices employed by many localities neglect these considerations. Among the categories of criteria to consider in selecting a BMP for a particular site or objective are site-specific characteristics; local, state, and federal ordinances; and implementation and long-term maintenance costs. A consideration such as long-term maintenance cost may manifest itself in a very subjective fashion during the selection process. For example, a BMPs cost may be of very limited interest to the reviewing locality, whereas cost may be the dominant selection criterion in the eyes of a developer. By contrast, the pollutant removal efficiency of a BMP may be necessarily prioritized in the selection process because of the required adherence to governing legislation. These are merely two possible criteria influencing selection. As more and more selection criteria are considered, the task of objectively and optimally selecting a BMP becomes increasingly complex. One mathematical approach for optimization in the face of multiple influential criteria is the Analytic Hierarchy Process. "The analytic hierarchy process (AHP) provides the objective mathematics to process the inescapably subjective and personal preferences of an individual or a group in making a decision" (Schmoldt, 2001, pg. 15). This paper details the development of two categories of comprehensive BMP selection matrices expressing long-term pollutant removal performance and annual maintenance and operations cost respectively. Additionally, the AHP is applied in multiple scenarios to demonstrate the optimized selection of a single BMP among multiple competing BMP alternatives. Pairwise rankings of competing BMP alternatives are founded on a detailed literature review of the most popular BMPs presently implemented throughout the United States. / Master of Science

No description available.

This study focused on development of a continuous watershed-scale modelling approach capable of evaluating sediment removal performance of vegetative filter strips (VFS). This was done by integrating the single-event hydrologic and sediment transport model AGNPS with the event-based VFS model (VFSMOD) applying the methodology developed by Sebti and Rudra (2010), and also through the development and incorporation of sub-models capable of describing changes in hydrologic conditions between rainfall events into the integrated models. For modeling purposes, the buffer zone is divided to segments called “buffer cells”. The upstream source area corresponding to each buffer cell and the flow-path connecting the area to the stream are identified, and runoff and sediment generated within each area is simulated for each event applying AGNPS. Using VFSMOD, performance analysis of VFS is conducted for each buffer cell. By applying the developed “continuous simulation” sub-models the hydrologic conditions prior to each event were determined.

Nonpoint source (NPS) pollution is one of the leading causes of water quality problems in the United States. Bioretention has become one of the more frequently used stormwater management practices for addressing NPS pollution in urbanized watersheds in New England. Yet despite increased acceptance, bioretention is not widely practiced. This study explores and evaluates the efficacy of bioretention for protecting urban water quality. This research found that numerous monitoring methods are used by researchers and industry experts to assess the effectiveness of stormwater best management practices (BMPs) and low impact development (LID) practices that include bioretention. The two most common methods for analyzing and evaluating water quality data are pollutant removal efficiency and effluent quality. While effluent quality data is useful for characterizing classes of BMP treatment performance on a statistical basis, pollutant removal efficiency is more representative of the actual pollutant load being reduced by the stormwater treatment practice over time, and is used in Total Maximum Daily Load (TMDL) assessments. However, despite this difference, monitoring is still arguably the best method for determining the effectiveness of stormwater treatment practices. Monitoring of bioretention performance results is needed to inform improvements to design standards and guidance to aid state and local municipalities in the proper selection of bioretention/stormwater controls. This study advocates for instituting fine-scale, “safe-to-fail” design experiments as part of an adaptive management process that is used to advance bioretention design guidance and future applications of monitoring practice(s) that target reduction of pollutants in downstream receiving waterbodies. This innovative approach could result in increased use of bioretention in New England urban environments.