干旱区生态环境知识资源中心(Arid): Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network

Arid

DOI	10.1038/s41598-024-68523-3
	Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network
	Ma, Yantao; Xue, Jie; Feng, Xinlong; Zhao, Jianping; Tang, Junhu; Sun, Huaiwei; Chang, Jingjing; Yan, Longke
通讯作者	Feng, XL
来源期刊	SCIENTIFIC REPORTS
ISSN	2045-2322
出版年	2024
卷号	14 期号:1
英文摘要	Enhancing crop water productivity is crucial for regional water resource management and agricultural sustainability, particularly in arid regions. However, evaluating the spatial heterogeneity and temporal dynamics of crop water productivity in face of data limitations poses a challenge. In this study, we propose a framework that integrates remote sensing data, time series generative adversarial network (TimeGAN), dynamic Bayesian network (DBN), and optimization model to assess crop water productivity and optimize crop planting structure under limited water resources allocation in the Qira oasis. The results demonstrate that the combination of TimeGAN and DBN better improves the accuracy of the model for the dynamic prediction, particularly for short-term predictions with 4 years as the optimal timescale (R2 > 0.8). Based on the spatial distribution of crop suitability analysis, wheat and corn are most suitable for cultivation in the central and eastern parts of Qira oasis while cotton is unsuitable for planting in the western region. The walnuts and Chinese dates are mainly unsuitable in the southeastern part of the oasis. Maximizing crop water productivity while ensuring food security has led to increased acreage for cotton, Chinese dates and walnuts. Under the combined action of the five optimization objectives, the average increase of crop water productivity is 14.97%, and the average increase of ecological benefit is 3.61%, which is much higher than the growth rate of irrigation water consumption of cultivated land. It will produce a planting structure that relatively reduced irrigation water requirement of cultivated land and improved crop water productivity. This proposed framework can serve as an effective reference tool for decision-makers when determining future cropping plans.
英文关键词	Dynamic planting distribution TimeGAN Dynamic Bayesian network Crop water productivity Crop suitability assessment
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001283344000012
WOS关键词	FOOTPRINT ; IMPACTS
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/405574
推荐引用方式 GB/T 7714	Ma, Yantao,Xue, Jie,Feng, Xinlong,et al. Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network[J],2024,14(1).
APA	Ma, Yantao.,Xue, Jie.,Feng, Xinlong.,Zhao, Jianping.,Tang, Junhu.,...&Yan, Longke.(2024).Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network.SCIENTIFIC REPORTS,14(1).
MLA	Ma, Yantao,et al."Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network".SCIENTIFIC REPORTS 14.1(2024).