語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
FindBook
Google Book
Amazon
博客來
Toward a Comprehensive Water Quality Model for the Chesapeake Bay Using Unstructured Grids.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Toward a Comprehensive Water Quality Model for the Chesapeake Bay Using Unstructured Grids./
作者:
Cai, Xun.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:
207 p.
附註:
Source: Dissertations Abstracts International, Volume: 83-11, Section: B.
Contained By:
Dissertations Abstracts International83-11B.
標題:
Water resources management. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29166101
ISBN:
9798426834804
Toward a Comprehensive Water Quality Model for the Chesapeake Bay Using Unstructured Grids.
Cai, Xun.
Toward a Comprehensive Water Quality Model for the Chesapeake Bay Using Unstructured Grids.
- Ann Arbor : ProQuest Dissertations & Theses, 2022 - 207 p.
Source: Dissertations Abstracts International, Volume: 83-11, Section: B.
Thesis (Ph.D.)--The College of William and Mary, 2022.
This item must not be sold to any third party vendors.
Chesapeake Bay is one of the most productive ecosystems on the US east coast which supports various living resources and habitat, and therefore has significant impacts on human beings and ecosystem health. Developing the capability of accurately simulating the water quality condition in the Chesapeake Bay, such as seasonal hypoxia, phytoplankton production, and nutrient dynamics, helps to better understand the interactions of hydrodynamical and biochemical processes, and more importantly, to predict conditions under changing climate and human intervention. Currently, most Chesapeake Bay models use structured grids that lack the flexibility for local refinements to fit complex geometry over both large and small scales, which hampers the allocation of local TMDLs for shallow water and small tributaries. In addition, few of them extend their simulations beyond the water column state variables, such as dissolved oxygen and nutrients, to include other living resources such as vegetation. These limitations motivate the model developments in this dissertation of: (1) a new comprehensive water quality model using high-resolution unstructured grids, which possesses the cross-scale capability to study interactions among water bodies and processes of different scales; and (2) a tightly coupled tidal marsh model, which is linked to the water quality model for water column to study the interactions between the marshes and surrounding aquatic system. The new modeling tool can be effectively utilized as a powerful tool for adaptive management in the Chesapeake Bay and can also be exported to other estuaries in the world. In this dissertation, Chapter 2 focuses on the development of a high-resolution water quality model in the water column and sediment flux part of the water quality model. This part of this study also demonstrates the importance of the correct representation of geometry, and the detrimental effects of artificial bathymetry smoothing on model simulations. Chapter 3 of this dissertation studies the impacts of sea-level rise (SLR) on seasonal hypoxia and phytoplankton production in the Chesapeake Bay with the newly developed water quality model. SLR is predicted to increase the hypoxic volume in the Chesapeake Bay by altering the physical processes and enhancing the estuarine respirations. Phytoplankton production in the shallow shoals is also predicted to increase under SLR, as a result of increased light utilization. Chapter 4 of this dissertation focuses on developing a new marsh model in the hydrodynamic-water quality model framework. This new model extends the model coverage to the tidal wetlands which are periodically inundated. The tidal marshes are suggested to affect the estuarine oxygen, carbon, and nutrient dynamics through tidal exchange, e.g., contributing the diel DO cycle. Chapter 5 studies the impacts of SLR on the biochemical processes in the York River Estuary, a tributary of the Bay that has extensive tidal marshes, with the fully-coupled hydrodynamic-water quality-marsh model. The SLR is predicted to enhance the exchanges between the marshes and the adjacent channel, which in turn further impacts the estuarine biochemical processes.
ISBN: 9798426834804Subjects--Topical Terms:
794747
Water resources management.
Subjects--Index Terms:
Estuary
Toward a Comprehensive Water Quality Model for the Chesapeake Bay Using Unstructured Grids.
LDR
:04408nmm a2200385 4500
001
2348275
005
20220908123018.5
008
241004s2022 ||||||||||||||||| ||eng d
020
$a
9798426834804
035
$a
(MiAaPQ)AAI29166101
035
$a
AAI29166101
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Cai, Xun.
$3
3433933
245
1 0
$a
Toward a Comprehensive Water Quality Model for the Chesapeake Bay Using Unstructured Grids.
260
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2022
300
$a
207 p.
500
$a
Source: Dissertations Abstracts International, Volume: 83-11, Section: B.
500
$a
Advisor: Zhang, Y. Joseph;Shen, Jian.
502
$a
Thesis (Ph.D.)--The College of William and Mary, 2022.
506
$a
This item must not be sold to any third party vendors.
520
$a
Chesapeake Bay is one of the most productive ecosystems on the US east coast which supports various living resources and habitat, and therefore has significant impacts on human beings and ecosystem health. Developing the capability of accurately simulating the water quality condition in the Chesapeake Bay, such as seasonal hypoxia, phytoplankton production, and nutrient dynamics, helps to better understand the interactions of hydrodynamical and biochemical processes, and more importantly, to predict conditions under changing climate and human intervention. Currently, most Chesapeake Bay models use structured grids that lack the flexibility for local refinements to fit complex geometry over both large and small scales, which hampers the allocation of local TMDLs for shallow water and small tributaries. In addition, few of them extend their simulations beyond the water column state variables, such as dissolved oxygen and nutrients, to include other living resources such as vegetation. These limitations motivate the model developments in this dissertation of: (1) a new comprehensive water quality model using high-resolution unstructured grids, which possesses the cross-scale capability to study interactions among water bodies and processes of different scales; and (2) a tightly coupled tidal marsh model, which is linked to the water quality model for water column to study the interactions between the marshes and surrounding aquatic system. The new modeling tool can be effectively utilized as a powerful tool for adaptive management in the Chesapeake Bay and can also be exported to other estuaries in the world. In this dissertation, Chapter 2 focuses on the development of a high-resolution water quality model in the water column and sediment flux part of the water quality model. This part of this study also demonstrates the importance of the correct representation of geometry, and the detrimental effects of artificial bathymetry smoothing on model simulations. Chapter 3 of this dissertation studies the impacts of sea-level rise (SLR) on seasonal hypoxia and phytoplankton production in the Chesapeake Bay with the newly developed water quality model. SLR is predicted to increase the hypoxic volume in the Chesapeake Bay by altering the physical processes and enhancing the estuarine respirations. Phytoplankton production in the shallow shoals is also predicted to increase under SLR, as a result of increased light utilization. Chapter 4 of this dissertation focuses on developing a new marsh model in the hydrodynamic-water quality model framework. This new model extends the model coverage to the tidal wetlands which are periodically inundated. The tidal marshes are suggested to affect the estuarine oxygen, carbon, and nutrient dynamics through tidal exchange, e.g., contributing the diel DO cycle. Chapter 5 studies the impacts of SLR on the biochemical processes in the York River Estuary, a tributary of the Bay that has extensive tidal marshes, with the fully-coupled hydrodynamic-water quality-marsh model. The SLR is predicted to enhance the exchanges between the marshes and the adjacent channel, which in turn further impacts the estuarine biochemical processes.
590
$a
School code: 0261.
650
4
$a
Water resources management.
$3
794747
650
4
$a
Biological oceanography.
$3
2122748
650
4
$a
Chemical oceanography.
$3
516760
653
$a
Estuary
653
$a
Hypoxia
653
$a
Marsh
653
$a
Numerical modeling
653
$a
Sea-level rise
653
$a
Water quality
690
$a
0595
690
$a
0416
690
$a
0403
710
2
$a
The College of William and Mary.
$b
School of Marine Science.
$3
3281332
773
0
$t
Dissertations Abstracts International
$g
83-11B.
790
$a
0261
791
$a
Ph.D.
792
$a
2022
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29166101
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9470713
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入