干旱区生态环境知识资源中心(Arid): Spatiotemporal Variation and Future Predictions of Soil Salinization in the Werigan-Kuqa River Delta Oasis of China

Arid

DOI	10.3390/su151813996
	Spatiotemporal Variation and Future Predictions of Soil Salinization in the Werigan-Kuqa River Delta Oasis of China
	He, Baozhong; Ding, Jianli; Huang, Wenjiang; Ma, Xu
通讯作者	Ding, JL
来源期刊	SUSTAINABILITY
EISSN	2071-1050
出版年	2023
卷号	15 期号:18
英文摘要	Soil salinization is a serious global issue; by 2050, without intervention, 50% of the cultivated land area will be affected by salinization. Therefore, estimating and predicting future soil salinity is crucial for preventing soil salinization and investigating potential arable land resources. In this study, several machine learning methods (random forest (RF), Light Gradient Boosting Machine (LightGBM), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGBoost)) were used to estimate the soil salinity in the Werigan-Kuqa River Delta Oasis region of China from 2001 to 2021. The cellular automata (CA)-Markov model was used to predict soil salinity types from 2020 to 2050. The LightGBM method exhibited the highest accuracy, and the overall prediction accuracy of the methods had the following order: LightGBM > RF > GBRT > XGBoost. Moderately saline, severely saline, and saline soils were dominant in the east and south of the research area, while non-saline and mildly saline soils were widely distributed in the inner oasis area. A marked decreasing trend in the soil salt content was observed from 2001 to 2021, with a decreasing rate of 4.28 g/kg10 a(-1). The primary change included the conversion of mildly and severely saline soil types to non-saline soil. The generalized difference vegetation index (51%), Bio (30%), and temperature vegetation drought index (27%) had the greatest influence, followed by variables associated with soil attributes (soil organic carbon and soil organic carbon stock) and terrain (topographic wetness index, slope, aspect, curvature, and topographic relief index). Overall, the CA-Markov simulation resulted exhibited suitable accuracy (kappa = 0.6736). Furthermore, areas with non-saline and mildly saline soils will increase while areas with other salinity levels will continue to decrease from 2020 to 2050. From 2046 to 2050, numerous areas with saline soil will be converted to non-saline soil. These results can provide support for salinization control, agricultural production, and soil investigations in the future. The gradual decline in soil salinization in the research area in the past 20 years may have resulted from large-scale land reclamation, which has turned saline alkali land into arable land and is also related to effective measures taken by the local government to control salinization.
英文关键词	soil salinization machine learning CA-Markov model spatiotemporal change
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:001076819700001
WOS关键词	TEMPERATURE/VEGETATION INDEX SPACE ; SALINITY ; XINJIANG ; MOISTURE ; REGION ; FOREST
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/398837
推荐引用方式 GB/T 7714	He, Baozhong,Ding, Jianli,Huang, Wenjiang,et al. Spatiotemporal Variation and Future Predictions of Soil Salinization in the Werigan-Kuqa River Delta Oasis of China[J],2023,15(18).
APA	He, Baozhong,Ding, Jianli,Huang, Wenjiang,&Ma, Xu.(2023).Spatiotemporal Variation and Future Predictions of Soil Salinization in the Werigan-Kuqa River Delta Oasis of China.SUSTAINABILITY,15(18).
MLA	He, Baozhong,et al."Spatiotemporal Variation and Future Predictions of Soil Salinization in the Werigan-Kuqa River Delta Oasis of China".SUSTAINABILITY 15.18(2023).