Open AccessSpatial distribution of soil organic carbon by digital mapping: the case of the Medio Aguanaval river sub-basin
Author(s) -
Georgina Pérez-Rodríguez,
AUTHOR_ID,
Armando López-Santos,
Miguel Agustín Velásquez-Valle,
José VillanuevaDíaz,
J. L. García-Rodríguez,
AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2021
Publication title -
ingeniería agrícola y biosistemas (en línea)/ingeniería agrícola y biosistemas
Language(s) - English
Resource type - Journals
eISSN - 2007-4026
pISSN - 2007-3925
DOI - 10.5154/r.inagbi.2021.03.055
Subject(s) - soil carbon , environmental science , kriging , soil science , standard deviation , spatial distribution , drainage basin , vegetation (pathology) , spatial variability , interpolation (computer graphics) , structural basin , hydrology (agriculture) , remote sensing , geology , soil water , statistics , mathematics , geography , cartography , geomorphology , computer science , geotechnical engineering , medicine , pathology , animation , computer graphics (images)
ntroduction: Carbon is found mainly in geological reservoirs, oceans, atmosphere and land. Soil organic carbon (SOC) is determined by the quantity and vertical distribution of vegetation, intrinsic soil properties and climate, but variability is influenced by anthropogenic interference. SOC stocks are not static; modeling their spatial, vertical and horizontal distribution involves the creation of baseline estimates to quantify these stocks. Objective: To estimate the magnitude of SOC stocks in the Medio Aguanaval River sub-basin (ScRMA) and to analyze the sensitivity of four interpolation methods to minimize the error of digital mapping for the ScRMA. Methodology: The study consisted of five stages: 1) search, download and analysis of soil data, 2) data processing, 3) selection of verification sites, 4) laboratory analysis and 5) processing of data from verification sites. Results: SOC values ranged from 9 to 133 t·ha-1, with a mean of 36.31 t·ha-1 and standard deviation of 23.83 t·ha-1. The ordinary exponential Kriging interpolator was the best representation for SOC of the ScRMA based onstatistics. The results of the analysis of the verification sites yielded a mean SOC of 24.4 t·ha-1. Limitations of the study: Soil profile density for the region and the lack of information on bulk density. Originality: The baseline distribution of SOC at the sub-basin level was used to analyze its dynamics. Conclusions: The highest concentration of SOC (61 to 129 t·ha-1) was found in the municipalities of Cuencamé and Santa Clara, while the lowest records (10 to 30 t·ha-1) were located in the municipalities of Torreón and Viesca.