干旱区生态环境知识资源中心(Arid): Balancing irrigation planning and risk preference for sustainable irrigated agriculture: A fuzzy credibility-based optimization model with the Hurwicz criterion under uncertainty

Arid

DOI	10.1016/j.agwat.2021.106949
	Balancing irrigation planning and risk preference for sustainable irrigated agriculture: A fuzzy credibility-based optimization model with the Hurwicz criterion under uncertainty
	Zhang, Chenglong; Li, Xuemin; Guo, Ping; Huo, Zailin
通讯作者	Huo, ZL (corresponding author), China Agr Univ, Ctr Agr Water Res China, Tsinghuadong St 17, Beijing 100083, Peoples R China.
来源期刊	AGRICULTURAL WATER MANAGEMENT
ISSN	0378-3774
EISSN	1873-2283
出版年	2021
卷号	254
英文摘要	The challenge of irrigation planning is that it involves various system components, which is further exacerbated by uncertainties and risk preference in making decisions. This study presents a simulation-optimization framework under uncertainty by incorporating fuzzy credibility-based optimization model with the Hurwicz criterion and daily water balance simulation for irrigation planning. The developed methodology can effectively handle fuzzy uncertainty in the objective function and constraints and readily analyze tradeoffs between optimal solutions of irrigation planning and risks associated with the decision-makers' preferences. It can also derive several physical parameters expressed as water depth from the water balance of root zone for determining optimal irrigation water amount. The Hurwicz criterion, fuzzy credibility constraints and other irrigation-related constraints are imposed on the study system through the developed framework. Then, its applicability is illustrated with a real case study in the Jiefangzha irrigation subarea in the Hetao Irrigation District, northwest China, which is an arid area. Optimal results using three risk-related parameters, i.e., nine preference weights (lambda = 0.1, 0.2, ... and 0.9) of objective function, and three credibility levels (alpha = 0.7, 0.8 and 0.9, beta = 0.7, 0.8 and 0.9) of fuzzy constraints, have been generated for supporting irrigation planning. Based on these outcomes, system benefits resulting from agricultural production have a slight growth with preference weights increase from 0.1 to 0.9, showing that optimistic criterion plays a decisive role in optimal irrigation planning solutions, especially when preference weights are greater than 0.7. Daily groundwater depth is presented in the given 81 scenarios for comparison, showing the usefulness of the developed framework in practical applications. Therefore, these findings are helpful for supporting irrigation planning and balancing tradeoffs between irrigation planning and risk preference for sustainable irrigated agriculture.
英文关键词	Irrigation planning Fuzzy programming Simulation-optimization framework Hurwicz criterion Risk preference
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000661233300004
WOS关键词	YELLOW-RIVER BASIN ; PROGRAMMING MODEL ; WATER ALLOCATION ; SYSTEMS ; DESIGN ; HETAO
WOS类目	Agronomy ; Water Resources
WOS研究方向	Agriculture ; Water Resources
来源机构	中国农业大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/349354
作者单位	[Zhang, Chenglong; Li, Xuemin; Guo, Ping; Huo, Zailin] China Agr Univ, Ctr Agr Water Res China, Tsinghuadong St 17, Beijing 100083, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Chenglong,Li, Xuemin,Guo, Ping,et al. Balancing irrigation planning and risk preference for sustainable irrigated agriculture: A fuzzy credibility-based optimization model with the Hurwicz criterion under uncertainty[J]. 中国农业大学,2021,254.
APA	Zhang, Chenglong,Li, Xuemin,Guo, Ping,&Huo, Zailin.(2021).Balancing irrigation planning and risk preference for sustainable irrigated agriculture: A fuzzy credibility-based optimization model with the Hurwicz criterion under uncertainty.AGRICULTURAL WATER MANAGEMENT,254.
MLA	Zhang, Chenglong,et al."Balancing irrigation planning and risk preference for sustainable irrigated agriculture: A fuzzy credibility-based optimization model with the Hurwicz criterion under uncertainty".AGRICULTURAL WATER MANAGEMENT 254(2021).