African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6574

Full Length Research Paper

A comparison of predicted and measured pesticides concentrations in runoff of cotton farms in Brazil

Isaltino Alves Barbosa
  • Isaltino Alves Barbosa
  • Chemistry Department, Mato Grosso Federal University, Postgraduate Program in water resources Cuiabá, Brazil.
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Ricardo Santos Silva Amorim
  • Ricardo Santos Silva Amorim
  • Agronomy and Veterinary Medicine Faculty, Mato Grosso Federal University, Cuiabá, Brazil.
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Eliana Freire Gaspar de Carvalho Dores
  • Eliana Freire Gaspar de Carvalho Dores
  • Chemistry Department, University of Sao Paulo, São Paulo, Brazil.
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  •  Received: 11 March 2014
  •  Accepted: 17 December 2014
  •  Published: 15 January 2015

Abstract

The adjustment and evaluation of methods which allow estimation of runoff and the concentration of associated pesticides are important for the development of prognostics studies in agricultural areas, mainly in tropical regions. In this context, this study aimed to adjust a method to estimate the concentration of pesticides in run-off applied to a cotton plantation farm, located in the micro-region of Primavera do Leste – MT (Mato Grosso State) in Central-Western Brazil. The method was based on the association of the model of pesticides concentration in run-off, described by OECD (1999), with the methods of Curve Number (CN) and Water Balance on Soil Surface (BW) to estimate the run-off amount. The pesticides, diuron, alfa and beta endosulfan, metolachlor, were selected based on the frequency and applied amount in cotton crops. Among the studied pesticides, diuron was the one for whom the adjusted method performed better in the studied scenarios, in others words, the best performance of the SFIL for prediction the pesticides concentrations greater than 3 µg L-1. Thus the association of the OECD model to BW or CN performed well to predict the risk of surface waters contamination in cotton crop areas in tropical regions.

 

Key words: Modeling, contamination, surface waters, solute transport, tropical regions, agricultural areas.