14 Sep 2022
 | 14 Sep 2022
Status: this preprint is currently under review for the journal ESSD.

Improving Latin American Soil Information Database for Digital Soil Mapping enhances its usability and scalability

Sergio Díaz-Guadarrama, Iván Lizarazo, Mario Guevara, Marcos Angelini, Gustavo A. Araujo-Carrillo, Jainer Argeñal, Daphne Armas, Rafael A. Balta, Adriana Bolivar, Nelson Bustamante, Ricardo O. Dart, Martin Dell Aqua, Arnulfo Encina, Hernán Figueredo, Fernando Fontes, Joan S. Gutiérrez-Diaz, Wilmer Jiménez, Raúl S. Lavado, Jesús F. Mansilla-Baca, Maria de Lourdes Mendonça-Santos, Lucas M. Moretti, Iván D. Muñoz, Carolina Olivera, Guillermo Olmedo, Christian Omuto, Sol Ortiz, Carla Pascale, Marco Pfeiffer, Iván A. Ramos, Danny Ríos, Rafael Rivera, Lady M. Rodríguez, Darío M. Rodríguez, Albán Rosales, Kenset Rosales, Guillermo Schulz, Victor Sevilla, Leonardo M. Tenti, Ronald Vargas, Viviana M. Varón-Ramírez, Gustavo M. Vasques, Yusuf Yigini, and Yolanda Rubiano

Abstract. Spatial soil databases can help model complex phenomena in which soils are decisive, for example, evaluating agricultural potential or estimating carbon storage capacity. The Soil Information System for Latin America and the Caribbean, SISLAC, is a regional initiative promoted by the FAO's South American Soil Partnership to contribute to the sustainable management of soil. SISLAC includes data coming from 49,084 soil profiles distributed unevenly across the continent, making it the region's largest soil database. However, some problems hinder its usages, such as the quality of the data and its high dimensionality. The objective of this research is twofold. First, to evaluate the quality of SISLAC and its data values and generate a new, improved version that meets the minimum quality requirements to be used by different interests or practical applications. Second, to demonstrate the potential of improved soil profile databases to generate more accurate information on soil properties, by conducting a case study to estimate the spatial variability of the percentage of soil organic carbon using 192 profiles in a 1473 km2 region located in the department of Valle del Cauca, Colombia. The findings show that 15 percent of the existing soil profiles had an inaccurate description of the diagnostic horizons. Further correction of an 4.5 additional percent of existing inconsistencies improved overall data quality. The improved database consists of 41,691 profiles and is available for public use at (Díaz-Guadarrama, S. & Guevara, M., 2022). The updated profiles were segmented using algorithms for quantitative pedology to estimate the spatial variability. We generated segments one centimeter thick along with each soil profile data, then the values of these segments were adjusted using a spline-type function to enhance vertical continuity and reliability. Vertical variability was estimated up to 150 cm in-depth, while ordinary kriging predicts horizontal variability at three depth intervals, 0 to 5, 5 to 15, and 15 to 30 cm, at 250 m-spatial resolution, following the standards of the GlobalSoilMap project. Finally, the leave-one-out cross-validation provides information for evaluating the kriging model performance, obtaining values for the RMSE index between 1.77 % and 1.79 % and the R2 index greater than 0.5. The results show the usability of SISLAC database to generate spatial information on soil properties and suggest further efforts to collect a more significant amount of data to guide sustainable soil management.

Sergio Díaz-Guadarrama et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-291', Jinshi Jian, 08 Oct 2022
    • AC1: 'Reply on RC1', Sergio Diaz, 28 May 2023
  • RC2: 'Comment on essd-2022-291', José Lucas Safanelli, 12 Oct 2022
    • AC2: 'Reply on RC2', Sergio Diaz, 28 May 2023

Sergio Díaz-Guadarrama et al.

Data sets

Revised database of the Soil Information System of Latin America and the Caribbean, SISLAC Sergio Díaz-Guadarrama, Mario Guevara

Sergio Díaz-Guadarrama et al.


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Short summary
In this work, the SISLAC database was revised to generate an improved version of the data. Then, through a practical exercise of digital soil mapping we show the potential of the data to generate spatial information of soil organic carbon. The results (R2 > 0.5) show the suitability and usability of the data to generate information that can help mitigate problems such as food security and global warming.