Agricultural water management model based on grey water footprints under uncertainty and its application

The 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 handl...

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Main Authors: Song, Ge, Dai, Chao, Tan, Qian, Zhang, Shan
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/142706
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1427062020-06-29T01:16:18Z Agricultural water management model based on grey water footprints under uncertainty and its application Song, Ge Dai, Chao Tan, Qian Zhang, Shan School of Civil and Environmental Engineering Engineering::Civil engineering Grey Water Footprint Fractional Programming Model The 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. Published version 2020-06-29T01:16:18Z 2020-06-29T01:16:18Z 2019 Journal Article Song, 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/su11205567 2071-1050 https://hdl.handle.net/10356/142706 10.3390/su11205567 2-s2.0-85073773008 20 11 en Sustainability © 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 http://creativecommons.org/licenses/by/4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Civil engineering
Grey Water Footprint
Fractional Programming Model
spellingShingle Engineering::Civil engineering
Grey Water Footprint
Fractional Programming Model
Song, Ge
Dai, Chao
Tan, Qian
Zhang, Shan
Agricultural water management model based on grey water footprints under uncertainty and its application
description The 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.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Song, Ge
Dai, Chao
Tan, Qian
Zhang, Shan
format Article
author Song, Ge
Dai, Chao
Tan, Qian
Zhang, Shan
author_sort Song, Ge
title Agricultural water management model based on grey water footprints under uncertainty and its application
title_short Agricultural water management model based on grey water footprints under uncertainty and its application
title_full Agricultural water management model based on grey water footprints under uncertainty and its application
title_fullStr Agricultural water management model based on grey water footprints under uncertainty and its application
title_full_unstemmed Agricultural water management model based on grey water footprints under uncertainty and its application
title_sort agricultural water management model based on grey water footprints under uncertainty and its application
publishDate 2020
url https://hdl.handle.net/10356/142706
_version_ 1681058404069539840