干旱区生态环境知识资源中心(Arid): Reservoir operation under influence of the joint uncertainty of inflow and evaporation

Arid

DOI	10.1007/s10668-021-01560-4
	Reservoir operation under influence of the joint uncertainty of inflow and evaporation
	Bozorg-Haddad, Omid; Yari, Pouria; Delpasand, Mohammad; Chu, Xuefeng
通讯作者	Bozorg-Haddad, O (corresponding author), Univ Tehran, Coll Agr & Nat Resources, Dept Irrigat & Reclamat Engn, Karaj, Iran.
来源期刊	ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
ISSN	1387-585X
EISSN	1573-2975
出版年	2021-06
英文摘要	Reservoirs play a major role as an essential source of surface water, especially in arid and semi-arid regions. To optimize the operation of a reservoir and determine its storage, which varies in time, the uncertainties of major influencing factors such as its inflow and evaporation should be considered. The objective of this study is to examine the effects of joint uncertainties of the inflow and evaporation of Durudzan reservoir on its performance for the first time. The Monte Carlo simulation is used for uncertainty assessment. Specifically, the monthly time series of inflow and evaporation were generated by using artificial neural networks and the standard operation policy was used for reservoir operation. Furthermore, the probabilistic distributions of four performance indices, including time-based reliability, volumetric reliability, vulnerability, and resiliency were calculated to assess the effects of the joint uncertainties of inflow and evaporation as well as the physical parameters on the reservoir variables (e.g., water release, storage, and spill). The results showed that the highest and lowest uncertainties of the reservoir water release occurred in July and May, respectively. In addition, the highest and lowest uncertainties were, respectively, observed in March and October for the reservoir storage, and in March and May for the water spill. The results also showed that the volumetric reliability had the highest uncertainty with a coefficient of variation (CV) of 0.158, while the resiliency had the lowest uncertainty with a CV of 0.020.
英文关键词	Reservoir operation management Artificial neural network (ANN) Probability distribution Uncertainty analysis Monte Carlo simulation Reservoir performance indices
类型	Article ; Early Access
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000661767800001
WOS关键词	PERFORMANCE ; RULES ; DAM
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/352142
作者单位	[Bozorg-Haddad, Omid; Yari, Pouria] Univ Tehran, Coll Agr & Nat Resources, Dept Irrigat & Reclamat Engn, Karaj, Iran; [Delpasand, Mohammad] Univ Tehran, Coll Agr & Nat Resources, Fac Agr Engn & Technol, Dept Irrigat & Reclamat Engn, Tehran, Iran; [Chu, Xuefeng] North Dakota State Univ, Dept Civil & Environm Engn, Dept 2470, Fargo, ND 58108 USA
推荐引用方式 GB/T 7714	Bozorg-Haddad, Omid,Yari, Pouria,Delpasand, Mohammad,et al. Reservoir operation under influence of the joint uncertainty of inflow and evaporation[J],2021.
APA	Bozorg-Haddad, Omid,Yari, Pouria,Delpasand, Mohammad,&Chu, Xuefeng.(2021).Reservoir operation under influence of the joint uncertainty of inflow and evaporation.ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY.
MLA	Bozorg-Haddad, Omid,et al."Reservoir operation under influence of the joint uncertainty of inflow and evaporation".ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY (2021).