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多不确定性下灌溉水资源优化分配的不精确分式规划模型。

An inexact fractional programming model for irrigation water resources optimal allocation under multiple uncertainties.

机构信息

Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region, Ministry of Education, Xi'an, Shaanxi Province, China.

School of Environmental Science and Engineering, Chang'an University, Xi'an, Shaanxi Province, China.

出版信息

PLoS One. 2019 Jun 13;14(6):e0217783. doi: 10.1371/journal.pone.0217783. eCollection 2019.

Abstract

In reality, severe water shortage crisis has made bad impact on the sustainable development of a region. In addition, uncertainties are inevitable in the irrigation system. Therefore, a fully fuzzy fractional programming model for optimization allocation of irrigation water resources, which aimed at not only irrigation water optimization but also improving water use efficiency. And then the developed model applied to a case study in Minqin County, Gansu Province, China, which selected maximum economic benefit of per unit water resources as planning objective. Moreover, surface and underground water are main water sources for irrigation. Thus, conjunctive use of surface and underground water was taken under consideration in this study. By solving the developed model, a series of optimal crop area and planting schemes, which were under different α-cut levels, were offered to the decision makers. The obtained results could be helpful for decision makers to make decision on the optimal use of irrigation water resources under multiple uncertainties.

摘要

实际上,严重的水资源短缺危机已经对一个地区的可持续发展造成了不良影响。此外,灌溉系统中存在不确定性是不可避免的。因此,建立了一个充分模糊分数规划模型,用于优化灌溉水资源的配置,该模型不仅旨在优化灌溉用水,还旨在提高水的利用效率。然后,将所开发的模型应用于中国甘肃省民勤县的案例研究,选择单位水资源的最大经济效益作为规划目标。此外,地表水和地下水是灌溉的主要水源。因此,本研究考虑了地表水和地下水的联合利用。通过求解所建立的模型,为决策者提供了一系列在不同α-截断水平下的最优作物面积和种植方案。所得结果有助于决策者在多种不确定性下做出最优灌溉水资源利用决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f049/6563986/9ac13cb4adfd/pone.0217783.g001.jpg

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