Assessment of the soil-erosion-sediment for sustainable development of South America

Nelva B Riquetti; Carlos R Mello; Diuliana Leandro; Jorge A Guzman; Samuel Beskow

doi:10.1016/j.jenvman.2022.115933

Assessment of the soil-erosion-sediment for sustainable development of South America

J Environ Manage. 2022 Nov 1:321:115933. doi: 10.1016/j.jenvman.2022.115933. Epub 2022 Aug 13.

Authors

Nelva B Riquetti¹, Carlos R Mello², Diuliana Leandro¹, Jorge A Guzman³, Samuel Beskow¹

Affiliations

¹ Water Resources Graduate Program, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, 1, 96010-610, Pelotas, RS, Brazil.
² Water Resources Graduate Program, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, 1, 96010-610, Pelotas, RS, Brazil; Water Resources Department, Federal University of Lavras, Campus Universitário, CP 3037, 37200-900, Lavras, MG, Brazil. Electronic address: crmello@ufla.br.
³ Department of Agricultural and Biological Engineering, College of ACES, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.

PMID: 35973288
DOI: 10.1016/j.jenvman.2022.115933

Abstract

One of the greatest threats to maintaining sustainable agro-ecosystems is mitigating the episodic soil loss from farm operations, further exacerbated by meteorological extremes. The Revised Universal Soil Loss Equation (RUSLE) is a model that combines the effects of rain, soil erodibility, topography, land cover, and conservation practices for estimating the annual average soil losses. This study aims to quantify soil water erosion to continental South America (S.A.) through RUSLE using available datasets and characterizing the average sediment delivery rate (SDR) to the major S.A. basins. Soil erodibility was estimated from the Global Gridded Soil Information soil database. LS-factor's topographical parameter was derived from Digital Elevation Models using the "Shuttle Radar Topography Mission" dataset. The R-factor was estimated from a previous study developed for S.A. and the C-factor from the Global Land Cover (Copernicus Global Land Services) database. We used a modeling study for SDR that simulated the annual average sediment transport in 27 basins in S.A. RUSLE set up presented a satisfactory performance compared to other applications on a continental scale with an estimated averaged soil loss for S.A. of 3.8 t ha^-1 year^-1. Chile (>20.0 t ha^-1 year^-1) and Colombia (8.1 t ha^-1 year^-1) showed the highest soil loss. Regarding SDR, Suriname, French Guyana, and Guyana presented the lowest values (<1.0 t ha^-1 year^-1). The highest soil losses were found in the Andes Cordillera of Colombia and the Center-South Region of Chile. In the former, the combination of "high" K-factor, "very high" C-factor, and "very high" LS-factor were the leading causes. In the latter, agriculture, livestock, deforestation, and aggressive R-factor explained the high soil loss. Basins with the highest SDR were located in the North Argentina - South Atlantic basin (27.73%), Mar Chiquitita (2.66%), Amazon River basin (2.32%), Magdalena (2.14%) (in Andes Cordillera), and Orinoco (1.83%).

Keywords: RUSLE model; Sediment delivery rate; Spatial variability; Sustainability; Water erosion.

MeSH terms

Chile
Conservation of Natural Resources
Ecosystem
Environmental Monitoring*
Geographic Information Systems
Soil
Sustainable Development*

Substances

Soil