Optimal allocation of agricultural water and land resources integrated with virtual water trade : A perspective on spatial virtual water coordination

Copyright © 2023 Elsevier Ltd. All rights reserved..

Agricultural production consumes the majority of global freshwater resources. The worsening water scarcity has imposed significant stress on agricultural production when regions seek food self-sufficiency. To seek optimal allocation of spatial agricultural water and land resources in each water function zone of the objective region, a multi-objective optimization model was developed to tackle the trade-offs between the water-saving objective and the economic benefit objective considering virtual water trade (VWT). The cultivated area of each crop in each water function zone was taken into account as the decision variable, while a set of strong constraints were used to restrict land resources and water availability. Then, a decomposition-simplex method aggregation algorithm (DSMA) was proposed to solve this nonlinear, bounding-constrained, and multi-objective optimization model. Based on the quantitative analysis of the spatial blue and green virtual water in each agricultural product, the proposed methodology was applied to a real-world, provincial-scale region in China (i.e., Jiangsu Province). The optimized results provided 18 Pareto solutions to reallocate the land resources in the 21 IV-level water function zones of Jiangsu Province, considering four major rainy-season crops and two dry-season crops. Compared to the actual scenario, the superior scheme increased by 7.95% (5.6 × 109 RMB) for economic trade and decreased by 1.77% (2.0 × 109 m3) for agricultural water consumption. It was mainly because the potential of spatial blue and green virtual water in Jiangsu was fully exploited by improving spatial land resource allocation. The food security of Jiangsu could be guaranteed by achieving self-sufficiency in the superior scheme, and the total VWT in the optimal scheme was 2.2 times more than the actual scenario. The results provided a systematic decision-support methodology from the perspective of spatial virtual water coordination, yet, the methodology is widely applicable.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:347

Enthalten in:

Journal of environmental management - 347(2023) vom: 01. Dez., Seite 119189

Sprache:

Englisch

Beteiligte Personen:

Cheng, Haomiao [VerfasserIn]
Jiang, Xuecheng [VerfasserIn]
Wang, Menglei [VerfasserIn]
Zhu, Tengyi [VerfasserIn]
Wang, Liang [VerfasserIn]
Miao, Lingzhan [VerfasserIn]
Chen, Xin [VerfasserIn]
Qiu, Jinxian [VerfasserIn]
Shu, Ji [VerfasserIn]
Cheng, Jilin [VerfasserIn]

Links:

Volltext

Themen:

059QF0KO0R
Blue virtual water
Cropping pattern
Journal Article
Multi-objective optimization
Pareto front
Water
Water footprint
Water management

Anmerkungen:

Date Completed 02.11.2023

Date Revised 02.11.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.jenvman.2023.119189

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM362870152