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dc.contributor.authorSong, Geen_US
dc.contributor.authorDai, Chaoen_US
dc.contributor.authorTan, Qianen_US
dc.contributor.authorZhang, Shanen_US
dc.identifier.citationSong, G., Dai, C., Tan, Q., & Zhang, S. (2019). Agricultural water management model based on grey water footprints under uncertainty and its application. Sustainability, 11(20), 5567-. doi:10.3390/su11205567en_US
dc.description.abstractThe grey water footprint theory was introduced into a fractional programming model to alleviate non-point source pollution and increase water-use effciency through the adjustment of crop planting structure. The interval programming method was also incorporated within the developed framework to handle parametric uncertainties. The objective function of the model was the ratio of economic benefits to grey water footprints from crop production, and the constraints contained water availability constraints, food security constraints, planting area constraints, grey water footprint constraints and non-negative constraints. The model was applied to the Hetao Irrigation District of China. It was found that, based on the data in the year of 2016, the optimal planting plans generated from the developed model would reduce 34,400 m3 of grey water footprints for every 100 million Yuan gained from crops. Under the optimal planting structure, the total grey water footprints would be reduced by 21.9 million m3, the total economic benefits from crops would be increased by 1.138 billion Yuan, and the irrigation water would be saved by 44 million m3. The optimal results could provide decision-makers with agricultural water use plans with reduced negative impacts on the environment and enhanced economic benefits from crops.en_US
dc.rights© 2019 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license
dc.subjectEngineering::Civil engineeringen_US
dc.titleAgricultural water management model based on grey water footprints under uncertainty and its applicationen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US
dc.description.versionPublished versionen_US
dc.subject.keywordsGrey Water Footprinten_US
dc.subject.keywordsFractional Programming Modelen_US
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