IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i2p648-d719401.html
   My bibliography  Save this article

Effects of Content of Soil Rock Fragments on Soil Erodibility in China

Author

Listed:
  • Miaomiao Yang

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

  • Keli Zhang

    (College of Geography, Beijing Normal University, Beijing 100875, China)

  • Chenlu Huang

    (College of Tourist (Institute of Human Geography), Xi’an International Studies University, Xi’an 710127, China)

  • Qinke Yang

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

Abstract

Soil erosion is serious in China—the soil in plateau and mountain areas contain a large of rock fragments, and their content and distribution have an important influence on soil erosion. However, there are still no complete results for calculating soil erodibility factor (K) that have corrected rock fragments in China. In this paper, the data available on rock fragments in the soil profile (RFP); rock fragments on the surface of the soil (RFS); and environmental factors such as elevation, terrain relief, slope, vegetation coverage (characterised by normalised difference vegetation index, NDVI), land use, precipitation, temperature, and soil type were used to explore the effects of content of soil rock fragments on calculating of K in China. The correlation analysis, typical sampling area analysis, and redundancy analysis were applied to analyse the effects of content of soil rock fragments on calculating of K and its relationship with environment factors. The results showed that (1) The rock fragments in the soil profile (RFP) increased K. The rock fragments on the surface (RFS) of the soil reduced K. The effect of both RFP and RFS reduced K. (2) The effect of rock fragments on K was most affected by elevation, followed by terrain relief, NDVI, slope, soil type, temperature, and precipitation, but had little correlation with land use. (3) The result of redundancy analysis showed elevation to be the main predominant factor of the effect of rock fragments on K. This study fully considered the effect of rock fragments on calculating of K and carried out a quantitative analysis of the factors affecting the effect of rock fragments on K, so as to provide necessary scientific basis for estimating K and evaluating soil erosion status in China more accurately.

Suggested Citation

  • Miaomiao Yang & Keli Zhang & Chenlu Huang & Qinke Yang, 2022. "Effects of Content of Soil Rock Fragments on Soil Erodibility in China," IJERPH, MDPI, vol. 19(2), pages 1-19, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:2:p:648-:d:719401
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/2/648/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/2/648/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. J. Johansson, 1981. "An extension of Wollenberg's redundancy analysis," Psychometrika, Springer;The Psychometric Society, vol. 46(1), pages 93-103, March.
    2. Abby Israels, 1984. "Redundancy analysis for qualitative variables," Psychometrika, Springer;The Psychometric Society, vol. 49(3), pages 331-346, September.
    3. Tomislav Malvić & Josip Ivšinović & Josipa Velić & Jasenka Sremac & Uroš Barudžija, 2020. "Application of the Modified Shepard’s Method (MSM): A Case Study with the Interpolation of Neogene Reservoir Variables in Northern Croatia," Stats, MDPI, vol. 3(1), pages 1-16, March.
    4. Arnold Wollenberg, 1977. "Redundancy analysis an alternative for canonical correlation analysis," Psychometrika, Springer;The Psychometric Society, vol. 42(2), pages 207-219, June.
    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. Dianna Smith, 2024. "Looking back: Selected contributions by C. R. Rao to multivariate analysis," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(4), pages 1393-1424, December.
    2. Pasquale Dolce & Vincenzo Esposito Vinzi & Natale Carlo Lauro, 2018. "Non-symmetrical composite-based path modeling," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(3), pages 759-784, September.
    3. Vittadini, Giorgio & Minotti, Simona C. & Fattore, Marco & Lovaglio, Pietro G., 2007. "On the relationships among latent variables and residuals in PLS path modeling: The formative-reflective scheme," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5828-5846, August.
    4. Hanafi, Mohamed & Kiers, Henk A.L., 2006. "Analysis of K sets of data, with differential emphasis on agreement between and within sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1491-1508, December.
    5. Kazi-Aoual, Frederique & Hitier, Simon & Sabatier, Robert & Lebreton, Jean-Dominique, 1995. "Refined approximations to permutation tests for multivariate inference," Computational Statistics & Data Analysis, Elsevier, vol. 20(6), pages 643-656, December.
    6. Cook, Judith A. & Razzano, Lisa & Cappelleri, Joseph C., 1996. "Canonical correlation analysis of residential and vocational outcomes following psychiatric rehabilitation," Evaluation and Program Planning, Elsevier, vol. 19(4), pages 351-363, November.
    7. Kargin, V. & Onatski, A., 2008. "Curve forecasting by functional autoregression," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2508-2526, November.
    8. Minjung Kyung & Ju-Hyun Park & Ji Yeh Choi, 2022. "Bayesian Mixture Model of Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 946-966, September.
    9. Tenenhaus, Michel & Vinzi, Vincenzo Esposito & Chatelin, Yves-Marie & Lauro, Carlo, 2005. "PLS path modeling," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 159-205, January.
    10. Wayne DeSarbo & Heungsun Hwang & Ashley Stadler Blank & Eelco Kappe, 2015. "Constrained Stochastic Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 516-534, June.
    11. Abby Israëls, 1986. "Reviews," Psychometrika, Springer;The Psychometric Society, vol. 51(3), pages 495-497, September.
    12. Takane, Yoshio & Jung, Sunho, 2009. "Regularized nonsymmetric correspondence analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3159-3170, June.
    13. Martínez-Ventura, Constanza & Mariño-Martínez, Ricardo & Miguélez-Márquez, Javier, 2023. "Redundancy of Centrality Measures in Financial Market Infrastructures," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(4).
    14. John Zilvinskis & Anthony A. Masseria & Gary R. Pike, 2017. "Student Engagement and Student Learning: Examining the Convergent and Discriminant Validity of the Revised National Survey of Student Engagement," Research in Higher Education, Springer;Association for Institutional Research, vol. 58(8), pages 880-903, December.
    15. Ariyawardana, A. & Bailey, W.C, 2002. "The Relationship between Core Resources and Strategies of Firms: The Case of Sri Lankan Value-Added Tea Producers," Sri Lankan Journal of Agricultural Economics, Sri Lanka Agricultural Economics Association (SAEA), vol. 4, pages 1-19.
    16. Lazraq, Aziz & Cléroux, Robert, 2001. "Statistical Inference Concerning Several Redundancy Indices," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 71-88, October.
    17. Dray, Stephane, 2008. "On the number of principal components: A test of dimensionality based on measurements of similarity between matrices," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2228-2237, January.
    18. Jos Berge, 1985. "On the relationship between Fortier's simultaneous linear prediction and van den Wollenberg's redundancy analysis," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 121-122, March.
    19. Susana Mendes & M. Jos� Fernández-Gómez & Mário Jorge Pereira & Ulisses Miranda Azeiteiro & M. Purificación Galindo-Villardón, 2012. "An empirical comparison of Canonical Correspondence Analysis and STATICO in the identification of spatio-temporal ecological relationships," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 979-994, October.
    20. Michel Tenenhaus & Arthur Tenenhaus & Patrick J. F. Groenen, 2017. "Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 737-777, September.

    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:jijerp:v:19:y:2022:i:2:p:648-:d:719401. 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.