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Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China

Author

Listed:
  • Danying Du

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830017, China)

  • Baozhong He

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830017, China)

  • Xuefeng Luo

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830017, China)

  • Shilong Ma

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830017, China)

  • Yaning Song

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830017, China)

  • Wen Yang

    (College of Geographical and Remote Science, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
    Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830017, China)

Abstract

In order to investigate the mechanism of environmental factors in soil salinization, this study focused on analyzing the temporal-spatial variation of soil salinity in the Ogan-Kuqa River Oasis in Xinjiang, China. The research aimed to predict soil salinity using a combination of satellite data, environmental covariates, and advanced modeling techniques. Firstly, Boruta and ReliefF algorithms were employed to select variables that significantly affect soil salinity from the Sentinel-2 satellite data and environmental covariates. Subsequently, a soil salinity inversion model was established using three advanced strategies: comprehensive variable analysis, a Boruta-based variable selection algorithm, and a ReliefF-based variable selection algorithm. Each strategy was modeled using a Light Gradient Boosting Machine (LightGBM), an Extreme Learning Machine (ELM), and a Support Vector Machine (SVM). Finally, the Boruta-LightGBM strategy was proven to be the most effective in predicting soil electrical conductivity (EC), with a coefficient of determination ( R 2 ) of 0.72 and a Root Mean Square Error (RMSE) of 12.49 ds/m. The experimental results show that the red-edge band index is the foremost variable in predicting soil salinity, succeeded by the salinity index and soil attribute data, while the topographic index has the least influence, which further demonstrates that proper variable selection could significantly improve model functionality and predictive precision. Furthermore, the Multiscale Geographically Weighted Regression (MGWR) model was utilized to reveal the influence and temporal-temporal-spatial heterogeneity of environmental factors such as soil organic carbon (SOC), precipitation (PRE), pH value, and temperature (TEM) on soil EC. This research offers not just a viable methodological framework for monitoring soil salinization but also new perspectives on the environmental drivers of soil salinity changes, which have implications for sustainable land management and provide valuable information for decision-making in soil salinity control and mitigation efforts.

Suggested Citation

  • Danying Du & Baozhong He & Xuefeng Luo & Shilong Ma & Yaning Song & Wen Yang, 2024. "Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China," Sustainability, MDPI, vol. 16(7), pages 1-22, March.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2706-:d:1363666
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    References listed on IDEAS

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    1. Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
    2. Vinod Phogat & Tim Pitt & Paul Petrie & Jirka Šimůnek & Michael Cutting, 2023. "Optimization of Irrigation of Wine Grapes with Brackish Water for Managing Soil Salinization," Land, MDPI, vol. 12(10), pages 1-29, October.
    3. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
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