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A Multivariate Geomorphometric Approach to Prioritize Erosion-Prone Watersheds

Author

Listed:
  • Jesús A. Prieto-Amparán

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

  • Alfredo Pinedo-Alvarez

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

  • Griselda Vázquez-Quintero

    (Facultad de Ciencias Agrotecnológicas, Universidad Autónoma de Chihuahua, Chihuahua 31350, Mexico)

  • María C. Valles-Aragón

    (Facultad de Ciencias Agrotecnológicas, Universidad Autónoma de Chihuahua, Chihuahua 31350, Mexico)

  • Argelia E. Rascón-Ramos

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

  • Martin Martinez-Salvador

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

  • Federico Villarreal-Guerrero

    (Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua 31453, Mexico)

Abstract

Soil erosion is considered one of the main degradation processes in ecosystems located in developing countries. In northern Mexico, one of the most important hydrological regions is the Conchos River Basin (CRB) due to its utilization as a runoff source. However, the CRB is subjected to significant erosion processes due to natural and anthropogenic causes. Thus, classifying the CRB’s watersheds based on their erosion susceptibility is of great importance. This study classified and then prioritized the 31 watersheds composing the CRB. For that, multivariate techniques such as principal component analysis (PCA), group analysis (GA), and the ranking methodology known as compound parameter ( Cp ) were used. After a correlation analysis, the values of 26 from 33 geomorphometric parameters estimated from each watershed served for the evaluation. The PCA defined linear-type parameters as the main source of variability among the watersheds. The GA and the Cp were effective for grouping the watersheds in five groups, and provided the information for the spatial analysis. The GA methodology best classified the watersheds based on the variance of their parameters. The group with the highest prioritization and erosion susceptibility included watersheds RH24Lf, RH24Lb, RH24Nc, and RH24Jb. These watersheds are potential candidates for the implementation of soil conservation practices.

Suggested Citation

  • Jesús A. Prieto-Amparán & Alfredo Pinedo-Alvarez & Griselda Vázquez-Quintero & María C. Valles-Aragón & Argelia E. Rascón-Ramos & Martin Martinez-Salvador & Federico Villarreal-Guerrero, 2019. "A Multivariate Geomorphometric Approach to Prioritize Erosion-Prone Watersheds," Sustainability, MDPI, vol. 11(18), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:5140-:d:268894
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    References listed on IDEAS

    as
    1. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    2. P. Singh & Virendra Kumar & R. Purohit & Mahesh Kothari & P. Dashora, 2009. "Application of Principal Component Analysis in Grouping Geomorphic Parameters for Hydrologic Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(2), pages 325-339, January.
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