Arid
DOI10.1016/j.jhydrol.2022.127428
Enhancing irrigation water productivity and controlling salinity under uncertainty: A full fuzzy dependent linear fractional programming approach
Zhang, Chenglong; Li, Xuemin; Guo, Ping; Huo, Zailin; Huang, Guanhua
通讯作者Huo, ZL
来源期刊JOURNAL OF HYDROLOGY
ISSN0022-1694
EISSN1879-2707
出版年2022
卷号606
英文摘要An integrated simulation-optimization framework is developed under uncertainty to enhance irrigation water productivity and control salinity in an arid area. A full fuzzy dependent linear fractional programming approach is formulated by incorporating fuzzy dependent-chance programming, fuzzy credibility-constrained programming and linear fractional programming within a general framework of irrigation planning. Then, simulation module concerning water, salt balance process and crop water-salt production functions enables to quantify daily physical process of water and salt movement among the soil water, crop root zone and groundwater aquifers. Thus, this study can readily handle fuzzy uncertainty existing concurrently in the ratio objective (i.e., economic water productivity) through the concept of fuzzy dependent chance and double-sided constraints. It can also simultaneously provide the maximum credibility level that the objective is achievable and credibility levels implying that optimal solutions are believable. Besides, daily variations of simulated physical parameters are illustrated corresponding to management strategies. To demonstrate its applicability, it's then applied to a case study of irrigation planning in the Jiefangzha Irrigation Subarea in Hetao Irrigation District, northwest China. Results can clearly analyze tradeoffs among satisfaction degree of fuzzy objective, fuzzy constraints and optimal solutions. Moreover, by examining different management targets and salt accumulation constraints, this study demonstrates the merits and importance of the work to promote irrigation water productivity and control salinity. Dynamic decision making of irrigation planning is possibly made by coupling daily simulation and optimization modules. Therefore, these findings can support decision makers to identify appropriate solutions for irrigation planning.
英文关键词Economic water productivity Salinity control Management targets Fuzzy mathematical programming Irrigation planning Uncertainty
类型Article
语种英语
收录类别SCI-E
WOS记录号WOS:000752577400001
WOS关键词RESOURCES MANAGEMENT ; OPTIMIZATION MODEL ; ALLOCATION ; EFFICIENCY ; POLLUTION ; DISTRICT ; IMPACTS ; SYSTEMS ; DESIGN ; MAIZE
WOS类目Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向Engineering ; Geology ; Water Resources
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/376243
推荐引用方式
GB/T 7714
Zhang, Chenglong,Li, Xuemin,Guo, Ping,et al. Enhancing irrigation water productivity and controlling salinity under uncertainty: A full fuzzy dependent linear fractional programming approach[J],2022,606.
APA Zhang, Chenglong,Li, Xuemin,Guo, Ping,Huo, Zailin,&Huang, Guanhua.(2022).Enhancing irrigation water productivity and controlling salinity under uncertainty: A full fuzzy dependent linear fractional programming approach.JOURNAL OF HYDROLOGY,606.
MLA Zhang, Chenglong,et al."Enhancing irrigation water productivity and controlling salinity under uncertainty: A full fuzzy dependent linear fractional programming approach".JOURNAL OF HYDROLOGY 606(2022).
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