Preprints
https://doi.org/10.5194/essd-2022-291
https://doi.org/10.5194/essd-2022-291
 
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-Guadarrama1, Iván Lizarazo1, Mario Guevara2,3,4, Marcos Angelini5, Gustavo A. Araujo-Carrillo6, Jainer Argeñal7, Daphne Armas8, Rafael A. Balta9, Adriana Bolivar10, Nelson Bustamante11, Ricardo O. Dart12, Martin Dell Aqua13, Arnulfo Encina14, Hernán Figueredo15, Fernando Fontes13, Joan S. Gutiérrez-Diaz16, Wilmer Jiménez17, Raúl S. Lavado18, Jesús F. Mansilla-Baca12, Maria de Lourdes Mendonça-Santos12, Lucas M. Moretti19, Iván D. Muñoz20, Carolina Olivera5, Guillermo Olmedo5, Christian Omuto5, Sol Ortiz21, Carla Pascale22, Marco Pfeiffer23, Iván A. Ramos24, Danny Ríos25, Rafael Rivera26, Lady M. Rodríguez20, Darío M. Rodríguez27, Albán Rosales28, Kenset Rosales29, Guillermo Schulz27, Victor Sevilla30, Leonardo M. Tenti27, Ronald Vargas5, Viviana M. Varón-Ramírez6, Gustavo M. Vasques12, Yusuf Yigini5, and Yolanda Rubiano1 Sergio Díaz-Guadarrama et al.
  • 1Departamento de Agronomía, Facultad de Ciencias Agrarias. Universidad Nacional de Colombia, Bogotá, Colombia
  • 2Centro de Geociencias - Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, 76230, México
  • 3University of California, Riverside, Department of Environmental Sciences, Riverside CA. 92507, USA
  • 4United States Department of Agriculture, Soil Salinity National Laboratory, Riverside CA. 92507, USA
  • 5FAO, Vialle de Terme di Caracalla, Rome, Italy
  • 6Corporación Colombiana de Investigación Agropecuaria AGROSAVIA, C.I. Tibaitatá, Bogotá, CO-0571, Colombia
  • 7Facultad de Ciencias/ Universidad Nacional Autónoma de Honduras, Honduras
  • 8Departamento de Agronomía, Edif. CITEIIB. Universidad de Almería. Almería, 04120, España
  • 9Dirección General de Asuntos Ambientales Agrarios, Ministerio de Desarrollo Agrario y Riego, Perú
  • 10Subdirección Agrología, Instituto Geográfico Agustín Codazzi, Bogotá, Colombia
  • 11Servicio Agrícola y Ganadero, Santiago de Chile, Chile
  • 12Embrapa Solos, Rio de Janeiro, 22460-000, Brasil
  • 13Direccion General de Recursos Naturales, Ministerio de Ganadería, Agricultura y Pesca, Montevideo, Uruguay
  • 14Facultad de Ciencias Agrarias de la Universidad Nacional de Asunción, Asunción, Paraguay
  • 15Sociedad Boliviana de la Ciencia del Suelo, La Paz, Bolivia
  • 16Department of Agroecology, Faculty of Science and Technology, Aarhus University, Tjele, DK-8830 Denmark
  • 17Ministerio de Agricultura y Ganadería, Quito, 170516, Ecuador
  • 18Facultad de Agronomía e INBA (CONICET/UBA), Universidad de Buenos Aires, Buenos Aires, 1417, Argentina
  • 19Estación Experimental Agropecuaria Cerro Azul, Instituto Nacional de Tecnología Agropecuaria, Misiones, Argentina
  • 20Subdirección de Geografía, Instituto Geográfico Agustín Codazzi - IGAC, Bogotá, 111321, Colombia
  • 21Secretaría de Agricultura y Desarrollo Rural, México
  • 22Ministerio de Agricultura, Ganadería y Pesca (MAGYP), Argentina
  • 23Departamento de Ingeniería y Suelos, Facultad de Ciencias Agronómicas, Universidad de Chile, Santiago, Chile
  • 24Instituto de Investigación Agropecuaria de Panamá, Ciudad de Panamá, Panamá
  • 25Departamento de Ciencias del Suelo y Ordenamiento Territorial, Universidad Nacional de Asunción, Paraguay
  • 26Ministerio de Medio Ambiente, Santo Domingo, República Dominicana
  • 27Instituto de Suelos (CIRN), Instituto Nacional de Tecnología Agropecuaria, Hurlingham, Buenos Aires, B1686, Argentina
  • 28Instituto de Innovación en Transferencia y Tecnología Agropecuaria, San José, Costa Rica
  • 29Ministerio de Ambiente y Recursos Naturales, Guatemala
  • 30Universidad Central de Venezuela, Maracay, Venezuela

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 https://doi.org/10.5281/zenodo.6540710 (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: open (until 09 Nov 2022)

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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 https://doi.org/10.5281/zenodo.6540710

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.