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Assessment of the soil-erosion-sediment for sustainable development of South America.
Riquetti, Nelva B; Mello, Carlos R; Leandro, Diuliana; Guzman, Jorge A; Beskow, Samuel.
Afiliação
  • Riquetti NB; Water Resources Graduate Program, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, 1, 96010-610, Pelotas, RS, Brazil.
  • Mello CR; 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.
  • Leandro D; Water Resources Graduate Program, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, 1, 96010-610, Pelotas, RS, Brazil.
  • Guzman JA; Department of Agricultural and Biological Engineering, College of ACES, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
  • Beskow S; Water Resources Graduate Program, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, 1, 96010-610, Pelotas, RS, Brazil.
J Environ Manage ; 321: 115933, 2022 Nov 01.
Article em En | MEDLINE | ID: mdl-35973288
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%).
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Desenvolvimento Sustentável Tipo de estudo: Prognostic_studies País como assunto: America do sul / Chile Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Desenvolvimento Sustentável Tipo de estudo: Prognostic_studies País como assunto: America do sul / Chile Idioma: En Ano de publicação: 2022 Tipo de documento: Article