IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i16p6971-d1456230.html
   My bibliography  Save this article

Influence of Soil Moisture in Semi-Fixed Sand Dunes of the Tengger Desert, China, Based on PLS-SEM and SHAP Models

Author

Listed:
  • Haidi Qi

    (Centre for Quantitative Biology, College of Science, Gansu Agricultural University, Lanzhou 730070, China)

  • Dinghai Zhang

    (Centre for Quantitative Biology, College of Science, Gansu Agricultural University, Lanzhou 730070, China)

  • Zhishan Zhang

    (Shapotou Desert Research and Experimental Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Youyi Zhao

    (Centre for Quantitative Biology, College of Science, Gansu Agricultural University, Lanzhou 730070, China)

  • Zhanhong Shi

    (Centre for Quantitative Biology, College of Science, Gansu Agricultural University, Lanzhou 730070, China)

Abstract

Drought stress significantly limits the function and stability of desert ecosystems. This research examines the distribution characteristics of soil moisture across different microtopographic types in the semi-fixed dunes located at the southeastern edge of the Tengger Desert. We constructed a path model to examine the direct and indirect impacts of topography, shrub vegetation, and herbaceous vegetation. The data encompassed soil moisture, topography, and vegetation variables, which were collected from field experiments to ensure their accuracy and relevance. Furthermore, SHAP models based on machine learning algorithms were utilized to elucidate the specific mechanisms through which key factors influence soil moisture. The results of the descriptive statistics indicate the highest surface soil moisture content, recorded at 1.21%, was observed at the bottom of the dunes, while the leeward slopes demonstrated elevated moisture levels in the middle and deep soil layers, with measurements of 2.25% and 2.43%, respectively. Soil moisture at different depths initially decreases and then increases with greater herbaceous cover and slope direction, while surface soil moisture follows a similar trend in terms of height difference, with 3 m serving as the boundary for trend changes. Middle and deep soil moistures initially increase and then decrease with greater biomass and shrub coverage, with 30 g and 40% serving as the boundary for trend changes respectively. This study elucidates the spatial distribution patterns and influencing factors of soil moisture in semi-fixed dunes, offering valuable references for the establishment of sand-stabilizing vegetation in desert regions.

Suggested Citation

  • Haidi Qi & Dinghai Zhang & Zhishan Zhang & Youyi Zhao & Zhanhong Shi, 2024. "Influence of Soil Moisture in Semi-Fixed Sand Dunes of the Tengger Desert, China, Based on PLS-SEM and SHAP Models," Sustainability, MDPI, vol. 16(16), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:6971-:d:1456230
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/16/6971/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/16/6971/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cheng, Minghan & Jiao, Xiyun & Liu, Yadong & Shao, Mingchao & Yu, Xun & Bai, Yi & Wang, Zixu & Wang, Siyu & Tuohuti, Nuremanguli & Liu, Shuaibing & Shi, Lei & Yin, Dameng & Huang, Xiao & Nie, Chenwei , 2022. "Estimation of soil moisture content under high maize canopy coverage from UAV multimodal data and machine learning," Agricultural Water Management, Elsevier, vol. 264(C).
    2. Theo Dijkstra & Jörg Henseler, 2011. "Linear indices in nonlinear structural equation models: best fitting proper indices and other composites," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(6), pages 1505-1518, October.
    3. Gong, Xinghui & Zhang, Hongbo & Ren, Chongfeng & Sun, Dongyong & Yang, Jiantao, 2020. "Optimization allocation of irrigation water resources based on crop water requirement under considering effective precipitation and uncertainty," Agricultural Water Management, Elsevier, vol. 239(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meng Luo & Shengwei Zhang & Lei Huang & Zhiqiang Liu & Lin Yang & Ruishen Li & Xi Lin, 2022. "Temporal and Spatial Changes of Ecological Environment Quality Based on RSEI: A Case Study in Ulan Mulun River Basin, China," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
    2. Deng, Juntao & Pan, Shijia & Zhou, Mingu & Gao, Wen & Yan, Yuncai & Niu, Zijie & Han, Wenting, 2023. "Optimum sampling window size and vegetation index selection for low-altitude multispectral estimation of root soil moisture content for Xuxiang Kiwifruit," Agricultural Water Management, Elsevier, vol. 282(C).
    3. Junhao Liu & Zhe Hao & Jianli Ding & Yukun Zhang & Zhiguo Miao & Yu Zheng & Alimira Alimu & Huiling Cheng & Xiang Li, 2024. "Ensemble Machine-Learning-Based Framework for Estimating Surface Soil Moisture Using Sentinel-1/2 Data: A Case Study of an Arid Oasis in China," Land, MDPI, vol. 13(10), pages 1-21, October.
    4. Sarstedt, Marko & Hair, Joseph F. & Ringle, Christian M. & Thiele, Kai O. & Gudergan, Siegfried P., 2016. "Estimation issues with PLS and CBSEM: Where the bias lies!," Journal of Business Research, Elsevier, vol. 69(10), pages 3998-4010.
    5. Radha Yadav & Dharmendra Kumar & Anil Kumar & Sunil Luthra, 2023. "How does anticipatory trauma reaction and climate‐friendly behaviour make an affect at the individual level? The role of social norms and self‐efficacy," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4028-4045, November.
    6. Yizhen Jia & Xiaodong Yan, 2024. "Multi-Objective Optimization of the Planting Industry in Jiangsu Province and Analysis of Its “Water-Energy-Carbon” Characteristics," Sustainability, MDPI, vol. 16(7), pages 1-24, March.
    7. Xianli Wang & Zhigang Zhao & Feilong Jie & Jingjing Xu & Sheng Li & Kun Hao & Youliang Peng, 2024. "A Copula Function–Monte Carlo Method-Based Assessment of the Risk of Agricultural Water Demand in Xinjiang, China," Agriculture, MDPI, vol. 14(11), pages 1-23, November.
    8. Luo Muchen & Rosita Hamdan & Rossazana Ab-Rahim, 2022. "Data-Driven Evaluation and Optimization of Agricultural Environmental Efficiency with Carbon Emission Constraints," Sustainability, MDPI, vol. 14(19), pages 1-22, September.
    9. Florian Schuberth, 2021. "Confirmatory composite analysis using partial least squares: setting the record straight," Review of Managerial Science, Springer, vol. 15(5), pages 1311-1345, July.
    10. Santos, José Manuel & Ortiz Martínez, Esther & Marín Hernández, Salvador, 2021. "Centros Especiales de Empleo ¿Objetivo mercantil o social? Un análisis a través del estudio de su situación económico-financiera," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 51, pages 83-105.
    11. Jörg Henseler, 2018. "Partial least squares path modeling: Quo vadis?," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 1-8, January.
    12. Zhang, Shuo & Kang, Yan & Gao, Xuan & Chen, Peiru & Cheng, Xiao & Song, Songbai & Li, Lingjie, 2023. "Optimal reservoir operation and risk analysis of agriculture water supply considering encounter uncertainty of precipitation in irrigation area and runoff from upstream," Agricultural Water Management, Elsevier, vol. 277(C).
    13. Li, Mo & Cao, Xiaoxu & Liu, Dong & Fu, Qiang & Li, Tianxiao & Shang, Ruochen, 2022. "Sustainable management of agricultural water and land resources under changing climate and socio-economic conditions: A multi-dimensional optimization approach," Agricultural Water Management, Elsevier, vol. 259(C).
    14. Hao Yang & Wei He & Yu Li, 2022. "Optimization of Ecological Water Replenishment Scheme Based on the Interval Fuzzy Two-Stage Stochastic Programming Method: Boluo Lake National Nature Reserve, Jilin Province, China," IJERPH, MDPI, vol. 19(9), pages 1-17, April.
    15. Wenju Zhao & Fangfang Ma & Haiying Yu & Zhaozhao Li, 2023. "Inversion Model of Salt Content in Alfalfa-Covered Soil Based on a Combination of UAV Spectral and Texture Information," Agriculture, MDPI, vol. 13(8), pages 1-16, August.
    16. Joseph F. Hair & G. Tomas M. Hult & Christian M. Ringle & Marko Sarstedt & Kai Oliver Thiele, 2017. "Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods," Journal of the Academy of Marketing Science, Springer, vol. 45(5), pages 616-632, September.
    17. Bin Yang & Ying Wang & Yan Li & Lizi Mo, 2023. "Empirical Investigation of Cultivated Land Green Use Efficiency and Influencing Factors in China, 2000–2020," Land, MDPI, vol. 12(8), pages 1-17, August.
    18. Theo Dijkstra & Karin Schermelleh-Engel, 2014. "Consistent Partial Least Squares for Nonlinear Structural Equation Models," Psychometrika, Springer;The Psychometric Society, vol. 79(4), pages 585-604, October.
    19. Showkat Ahmad Busru & G. Shanmugasundaram & Shariq Ahmad Bhat, 2020. "Corporate Governance an Imperative for Stakeholders Protection: Evidence from Risk Management of Indian Listed Firms," Business Perspectives and Research, , vol. 8(2), pages 89-116, July.
    20. José Alberto Martínez-González & Urszula Kobylinska & Francisco J. García-Rodríguez & Lukasz Nazarko, 2019. "Antecedents of Entrepreneurial Intention among Young People: Model and Regional Evidence," Sustainability, MDPI, vol. 11(24), pages 1-29, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:6971-:d:1456230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.