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Using Water Quality Models in Manage...

Irby, Isaac David.

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Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts./
作者:	Irby, Isaac David.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	206 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
Contained By:	Dissertation Abstracts International79-01B(E).
標題:	Physical oceanography. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10618056
ISBN:	9780355160123

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts.
Irby, Isaac David.

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 206 p.

Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.

Thesis (Ph.D.)--The College of William and Mary, 2017.

Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts.

ISBN: 9780355160123Subjects--Topical Terms:

3168433
Physical oceanography.

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts.
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500 $a Source: Dissertation Abstracts International, Volume: 79-01(E), Section: B.
500 $a Adviser: Marjorie A.M. Friedrichs.
502 $a Thesis (Ph.D.)--The College of William and Mary, 2017.
520 $a Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts.
520 $a First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions.
520 $a Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology.
520 $a Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the pollution diet in light of future projections for air temperature, sea level, and precipitation was examined. While a changing climate will reduce the ability of the nutrient reduction to improve oxygen concentrations, that effect is trumped by the improvements in dissolved oxygen stemming from the pollution diet itself. However, climate change still has the potential to cause the current level of nutrient reduction to be inadequate. This is primarily due to the fact that low-oxygen conditions are predicted to start one week earlier, on average, in the future, with the primary changes resulting from the increase in temperature.
520 $a Overall, this research lends an increased degree of confidence in the water quality modeling of the potential impact of the Chesapeake Bay pollution diet. This research also establishes the efficacy of utilizing a multiple model approach to examining projected changes in water quality while establishing that the pollution diet trumps the impact from climate change. This work will lead directly to advances in scientific understanding of the response of water quality, ecosystem health, and ecological resilience to the impacts of nutrient reduction and climate change.
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