气候变化领域集成服务门户(CCPortal): A robust decision-making framework to improve reservoir water quality using optimized selective withdrawal strategies

CCPortal

DOI	10.1016/j.jhydrol.2024.131153
	A robust decision-making framework to improve reservoir water quality using optimized selective withdrawal strategies
	Nikoo, Mohammad Reza; Bahrami, Nafiseh; Madani, Kaveh; Al-Rawas, Ghazi; Vanda, Sadegh; Nazari, Rouzbeh
发表日期	2024
ISSN	0022-1694
EISSN	1879-2707
起始页码	635
卷号	635
英文摘要	In arid locations such as Oman, improving the quality of water released from a reservoir can be daunting. This is particularly true for Wadi Dayqah Dam, which struggles to provide sufficient, high-quality water for downstream needs. The study's objective was to establish more reliable operational guidelines, as well as identify vulnerable outlets and release ratios. To do so, a multi-objective optimization algorithm (NSGA-II) was combined with a selective withdrawal approach, using CE-QUAL-W2 and an Artificial Neural Network to simulate water quality in a reservoir. Then, a Robust Decision Making (RDM) approach was utilized to diagnose solutions that maintain acceptable water quality according to users' requirements. Finally, scenario discovery models (Patient Rule Induction Method (PRIM) and Classification and Regression Tree (CART)) were used to calculate vulnerable outlets and release ratios based on the established threshold. The study adopted an XLRM framework to manage a proposed model under climate change scenarios and specify the effects of involved factors. XLRM stands for eXogenous factors, Levers used by the policy-makers, Relationships between L and X, and Measurement matrix to evaluate scenarios. This study found that a higher-quality reservoir release correlated with more activated outlets and decreased pollutant concentration. Evaluating robust solutions showed that vulnerability increased under scenarios with lower annual rainfall, and water released from low and mid-level outlets was more vulnerable than that from the surface. To enhance operational stability and reduce vulnerability, the suggestions advocate for a strategic approach in releasing varying water ratios from outlets situated at different levels. Specifically, the proposal emphasizes the controlled release of both smaller and larger volumes of water from outlets positioned at lower and higher levels within the dam structure, respectively. This deliberate variation in water release aims to bolster the overall resilience of the operational framework, contributing to a more robust and reliable system.
英文关键词	Selective withdrawal; Robust decision making (RDM); Patient Rule Induction Method (PRIM); Classification and Regression Tree (CART); XLRM framework; ANN
语种	英语
WOS研究方向	Engineering ; Geology ; Water Resources
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS记录号	WOS:001226079600001
来源期刊	JOURNAL OF HYDROLOGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/304229
作者单位	Sultan Qaboos University; Iran University Science & Technology; City University of New York (CUNY) System; City College of New York (CUNY); Shiraz University; University of Alabama System; University of Alabama Birmingham
推荐引用方式 GB/T 7714	Nikoo, Mohammad Reza,Bahrami, Nafiseh,Madani, Kaveh,et al. A robust decision-making framework to improve reservoir water quality using optimized selective withdrawal strategies[J],2024,635.
APA	Nikoo, Mohammad Reza,Bahrami, Nafiseh,Madani, Kaveh,Al-Rawas, Ghazi,Vanda, Sadegh,&Nazari, Rouzbeh.(2024).A robust decision-making framework to improve reservoir water quality using optimized selective withdrawal strategies.JOURNAL OF HYDROLOGY,635.
MLA	Nikoo, Mohammad Reza,et al."A robust decision-making framework to improve reservoir water quality using optimized selective withdrawal strategies".JOURNAL OF HYDROLOGY 635(2024).