Browsing by Subject "Water quality"

Coastal eutrophication is a complex process that is caused largely by anthropogenic nutrient enrichment. Estuaries are particularly susceptible to nutrient impairment, owing to their intimate connection with the contributing watersheds. Estuaries experiencing accelerating eutrophication are subject to a loss of key ecological functions and services. This doctoral dissertation presents the development and implementation of an integrated approach toward assessing the water quality in the Neuse Estuary following the implementation of the total maximum daily load (TMDL) program in the Neuse River basin. In order to accomplish this task, I have developed a series of water quality models and modeling strategies that can be effectively used in assessing nutrient based eutrophication. Two watershed-level nutrient loading models that operate on a different temporal scale are developed and used to quantify nitrogen loading to the Neuse Estuary over time. The models are used to probabilistically assess the success of the adopted mitigation measures in achieving the 30 % load reduction goal stipulated by the TMDL. Additionally, a novel structure learning approach is adopted to develop a Bayesian Network (BN) model that describes chlorophyll dynamics in the Upper Neuse Estuary. The developed BN model is compared to pre-TMDL models to assess any changes in the role that nutrient loading and physical forcings play in modulating chlorophyll levels in that section of the estuary. Finally, a set of empirical models are developed to assess the water quality monitoring program in the estuary, while also exploring the possibility of incorporating remotely sensed satellite data in an effort to augment the existing in-situ monitoring programs.

Diverse ways of knowing have been recognized by scholars in many disciplines to contribute creative perspectives and novel problem-solving approaches. In the environmental sciences, those dependent on natural resources and working daily with those resources are in one of the best positions to observe and learn from subtle changes in the environment. In the coastal marine and estuarine environment, these experiential knowledge holders are the fishers and their families. In North Carolina, these fishers live in historic villages and, with scientists and policymakers, serve as the downstream stakeholders in watershed management. These three stakeholder groups all have perspectives to contribute to research and management of water quality in the watershed. This dissertation starts by documenting definitions and perspectives of water quality from these three stakeholder groups, establishing the base of information from which future research and management takes place. It then specifically addresses the details of negotiating co-production of knowledge through an ethnographic account of a collaborative research project investigating water pollution. The process of information sharing was highlighted during this process by a facilitated workshop asking participants to reflect upon their collective understanding of water quality more broadly and to plan a research project resulting from a new shared, understanding. The third component of my investigation of different ways of knowing uses North Carolina's Fishery Resource Grant program, which funds collaborative research between fishers and scientists, as a case study of an institution supporting co-produced knowledge about water quality and how the structure of collaboration in funded projects affects the success of the program both scientifically and socially. Together, the three chapters tell a story about the diverse forms of knowledge regarding water quality and how they might work together to better understand the causes and effects of water quality as well as tailor solutions to fit this better understanding. Though the story is of one case, specific to water quality and the coastal communities that depend on it, the story is also one of few optimistic cases in environmental science.