AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (2.8 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Spatiotemporal variability of soil salinity and the driving factors of cultivated land in Xinjiang, China

International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
College of Water Resources Science and Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Lab of Big Earth Data and Sustainable Development Goal (BASL), Kashi Aerospace Information Research Institute, Kashgar 844000, China
Xinjiang Soil and Fertilizer Station, Urumqi 830006, China
College of Land Science and Technology, China Agricultural University, Beijing 100193, China
Cultivated Land Quality Monitoring and Protection Center, Ministry of Agriculture and Rural Affairs, Beijing 100125, China
Ordos Agriculture and Animal Husbandry Ecology and Resource Protection Center, Ordos 017001, Inner Mengulia, China
Agricultural and Animal Husbandry Technology Extension Center, Dalat Banner, Ordos 014300, Inner Mengulia, China
Show Author Information

Abstract

Soil salinization poses a major challenge to agricultural production, food security, and sustainability in arid and semi-arid regions worldwide. Effectively addressing this issue requires a thorough understanding of the spatiotemporal variations in soil salinity and its driving factors. This study investigates soil salinity in Xinjiang, China, using geostatistical methods to analyze its spatial distribution in cultivated lands across the region and its southern and northern sub-regions in 2021. Additionally, it examines the spatiotemporal changes in soil salinity from 2011 to 2021 in Bachu County (southern Xinjiang) and Nileke County (northern Xinjiang), which serve as representative areas. The results showed that in 2021, soil salinity across Xinjiang ranged from 0.1 to 27.7 g/kg, with an average of 2.8 g/kg and a coefficient of variation of 130.4%, indicating significant variability. Soil salinity levels were higher in southern Xinjiang (3.8 g/kg) compared to northern Xinjiang (2.0 g/kg), showing a spatial trend of “increasing salinity from north to south.” Key drivers of spatial variation included available potassium, mean annual precipitation, alkali-hydrolyzable nitrogen, elevation, and soil pH. Between 2011 and 2021, soil salinity in cultivated lands increased significantly by 2.0 g/kg in Bachu County, while it decreased by 4.2 g/kg in Nileke County, with these changes mainly influenced by climatic factors such as precipitation, evapotranspiration, and surface temperature. These findings provide critical insights and data support for monitoring and managing soil salinization in Xinjiang, offering valuable guidance for improving agricultural sustainability in the region.

References

【1】
【1】
 
 
International Journal of Agricultural and Biological Engineering
Pages 197-207

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Zhang Y, Ye H, Liu R, et al. Spatiotemporal variability of soil salinity and the driving factors of cultivated land in Xinjiang, China. International Journal of Agricultural and Biological Engineering, 2025, 18(2): 197-207. https://doi.org/10.25165/j.ijabe.20251802.9486

903

Views

42

Downloads

0

Crossref

8

Web of Science

8

Scopus

Received: 03 November 2024
Accepted: 20 February 2025
Published: 30 April 2025
© The Author(s) 2025

We adopt the latest version of license CC BY 4.0, https://creativecommons.org/licenses/by/4.0/