中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A decision-making framework to model environmental flow requirements in oasis areas using bayesian networks

文献类型:期刊论文

作者Xue, Jie1,2,3,4; Gui, Dongwei1,2; Zhao, Ying1,5; Lei, Jiaqiang1,2; Zeng, Fanjiang1,2; Feng, Xinlong6; Mao, Donglei7; Shareef, Muhammad1,2,3,4
刊名Journal of hydrology
出版日期2016-09-01
卷号540页码:1209-1222
关键词Bayesian network Environmental flows Oasis Decision-making Northwest china
ISSN号0022-1694
DOI10.1016/j.jhydrol.2016.07.017
通讯作者Gui, dongwei(guidwei@163.com) ; Lei, jiaqiang(desert@ms.xjb.ac.cn)
英文摘要The competition for water resources between agricultural and natural oasis ecosystems has become an increasingly serious problem in oasis areas worldwide. recently, the intensive extension of oasis farmland has led to excessive exploitation of water discharge, and consequently has resulted in a lack of water supply in natural oasis. to coordinate the conflicts, this paper provides a decision-making framework for modeling environmental flows in oasis areas using bayesian networks (bns). three components are included in the framework: (1) assessment of agricultural economic loss due to meeting environmental flow requirements; (2) decision-making analysis using bns; and (3) environmental flow decision-making under different water management scenarios. the decision-making criterion is determined based on intersection point analysis between the probability of large-level total agro-economic loss and the ratio of total to maximum agro-economic output by satisfying environmental flows. an application in the qira oasis area of the tarim basin, northwest china indicates that bns can model environmental flow decision-making associated with agricultural economic loss effectively, as a powerful tool to coordinate water-use conflicts. in the case study, the environmental flow requirement is determined as 50.24%, 49.71% and 48.73% of the natural river flow in wet, normal and dry years, respectively. without further agricultural economic loss, 1.93%, 0.66% and 0.43% of more river discharge can be allocated to eco-environmental water demands under the combined strategy in wet, normal and dry years, respectively. this work provides a valuable reference for environmental flow decision-making in any oasis area worldwide. (c) 2016 elsevier b.v. all rights reserved.
WOS关键词YELLOW-RIVER ESTUARY ; CLIMATE-CHANGE ; TARIM RIVER ; ECOSYSTEM SERVICES ; WATER-RESOURCES ; NORTHWEST CHINA ; MANAGEMENT ; BASIN ; PERSPECTIVE ; CHALLENGES
WOS研究方向Engineering ; Geology ; Water Resources
WOS类目Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
语种英语
WOS记录号WOS:000382269500094
出版者ELSEVIER SCIENCE BV
URI标识http://www.irgrid.ac.cn/handle/1471x/2375245
专题中国科学院大学
通讯作者Gui, Dongwei; Lei, Jiaqiang
作者单位1.Chinese Acad Sci, State Key Lab Desert & Oasis Ecol, Xinjiang Inst Ecol & Geog, Urumqi 830011, Xinjiang, Peoples R China
2.Cele Natl Stn Observat & Res Desert Grassland Eco, Cele 848300, Xinjiang, Peoples R China
3.Chinese Acad Sci, Key Lab Biogeog & Bioresource Arid Zone, Urumqi 830011, Xinjiang, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Northwest A&F Univ, Key Lab Plant Nutr & Agrienvironm Northwest China, Minist Agr, Yangling 712100, Peoples R China
6.Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China
7.Xinjiang Normal Univ, Coll Geog Sci & Tourism, Urumqi 830046, Xinjiang, Peoples R China
推荐引用方式
GB/T 7714
Xue, Jie,Gui, Dongwei,Zhao, Ying,et al. A decision-making framework to model environmental flow requirements in oasis areas using bayesian networks[J]. Journal of hydrology,2016,540:1209-1222.
APA Xue, Jie.,Gui, Dongwei.,Zhao, Ying.,Lei, Jiaqiang.,Zeng, Fanjiang.,...&Shareef, Muhammad.(2016).A decision-making framework to model environmental flow requirements in oasis areas using bayesian networks.Journal of hydrology,540,1209-1222.
MLA Xue, Jie,et al."A decision-making framework to model environmental flow requirements in oasis areas using bayesian networks".Journal of hydrology 540(2016):1209-1222.

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来源:中国科学院大学

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