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
Designing River Basin Storage Using ...
~
Burrow, Andrew.
FindBook
Google Book
Amazon
博客來
Designing River Basin Storage Using Optimization.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Designing River Basin Storage Using Optimization./
作者:
Burrow, Andrew.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
142 p.
附註:
Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
Contained By:
Dissertations Abstracts International80-09B.
標題:
Climate Change. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13422785
ISBN:
9780438905467
Designing River Basin Storage Using Optimization.
Burrow, Andrew.
Designing River Basin Storage Using Optimization.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 142 p.
Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
Thesis (Ph.D.)--Colorado School of Mines, 2019.
This item must not be sold to any third party vendors.
As populations and economies grow in regions with changing climates, water demand quickly increases beyond what natural supply can sustain. This scenario is playing out in the western United States, including northeastern Colorado, where growth is enhancing an already growing water supply gap. In order to help reduce this growing gap, the state recognizes the need for additional reservoir storage to "bank" water during times of excess for use during times of dearth. Thus, we develop a methodology which uses simulation, combined with optimization, to design reservoir storage based on river flow over a 50-year time horizon. We use the State of Colorado's Stream Simulation Model to identify locations of water excess and unmet demand along 150 miles of the Lower South Platte River which we use as input to a mixed integer-linear optimization model. Model 1 minimizes the cost of meeting demands by designing additional storage for, and assigning network flow of, excess water while adhering to constraints that force the physical and topographical structures of the river. Next, we extend this deterministic work to incorporate characteristics of the food-energy-water nexus by using mixed-integer linear programming to consider the impact of nexus decisions related to agricultural irrigation, water storage, and power generation. Model 2 minimizes the cost of mitigating agricultural water shortages before identifying the location of the highest, most consistent volume to facilitate thermal power generation. We further apply this methodology using a multi-period, two-stage stochastic optimization model to design reservoir storage that is robust against a wide array of future climate scenarios such as historic trends of the past, reduced mean flow, and seasonally shifted flow. Model 3 minimizes the cost of meeting demands and we test solutions against a wide array of climate scenarios; our results indicate the optimal design to be multiple, smaller reservoirs of varying type. Our model develops solutions that mitigate between 90-100\\% of all demands over any of our chosen climate scenarios. We also identify solutions which integrate new reservoir construction with the expansion of existing infrastructure to capture the excess water in the river.
ISBN: 9780438905467Subjects--Topical Terms:
894284
Climate Change.
Designing River Basin Storage Using Optimization.
LDR
:03378nmm a2200349 4500
001
2263318
005
20200316071944.5
008
220629s2019 ||||||||||||||||| ||eng d
020
$a
9780438905467
035
$a
(MiAaPQ)AAI13422785
035
$a
(MiAaPQ)mines:11663
035
$a
AAI13422785
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Burrow, Andrew.
$3
3540405
245
1 0
$a
Designing River Basin Storage Using Optimization.
260
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2019
300
$a
142 p.
500
$a
Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
500
$a
Publisher info.: Dissertation/Thesis.
500
$a
Advisor: Newman, Alexandra;Illangasekare, Tissa.
502
$a
Thesis (Ph.D.)--Colorado School of Mines, 2019.
506
$a
This item must not be sold to any third party vendors.
520
$a
As populations and economies grow in regions with changing climates, water demand quickly increases beyond what natural supply can sustain. This scenario is playing out in the western United States, including northeastern Colorado, where growth is enhancing an already growing water supply gap. In order to help reduce this growing gap, the state recognizes the need for additional reservoir storage to "bank" water during times of excess for use during times of dearth. Thus, we develop a methodology which uses simulation, combined with optimization, to design reservoir storage based on river flow over a 50-year time horizon. We use the State of Colorado's Stream Simulation Model to identify locations of water excess and unmet demand along 150 miles of the Lower South Platte River which we use as input to a mixed integer-linear optimization model. Model 1 minimizes the cost of meeting demands by designing additional storage for, and assigning network flow of, excess water while adhering to constraints that force the physical and topographical structures of the river. Next, we extend this deterministic work to incorporate characteristics of the food-energy-water nexus by using mixed-integer linear programming to consider the impact of nexus decisions related to agricultural irrigation, water storage, and power generation. Model 2 minimizes the cost of mitigating agricultural water shortages before identifying the location of the highest, most consistent volume to facilitate thermal power generation. We further apply this methodology using a multi-period, two-stage stochastic optimization model to design reservoir storage that is robust against a wide array of future climate scenarios such as historic trends of the past, reduced mean flow, and seasonally shifted flow. Model 3 minimizes the cost of meeting demands and we test solutions against a wide array of climate scenarios; our results indicate the optimal design to be multiple, smaller reservoirs of varying type. Our model develops solutions that mitigate between 90-100\\% of all demands over any of our chosen climate scenarios. We also identify solutions which integrate new reservoir construction with the expansion of existing infrastructure to capture the excess water in the river.
590
$a
School code: 0052.
650
4
$a
Climate Change.
$3
894284
650
4
$a
Engineering.
$3
586835
650
4
$a
Water Resource Management.
$3
1669219
650
4
$a
Operations research.
$3
547123
690
$a
0404
690
$a
0537
690
$a
0595
690
$a
0796
710
2
$a
Colorado School of Mines.
$b
Mechanical Engineering.
$3
2092097
773
0
$t
Dissertations Abstracts International
$g
80-09B.
790
$a
0052
791
$a
Ph.D.
792
$a
2019
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13422785
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
W9415552
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