~ ) Pergamon
Chemosphere, Vol.38, No. 6, pp. 1401-1407,1999
© 1999 Elsevier Science Ltd.All rightsreserved
0045-6535/99/$ - see frontmatter
P|I: S0045-6535(98)00542-6
SIMULATION OF HERBICIDE DEGRADATION IN DIFFERENT SOILS BY USE OF
PEDO-TRANSFER FUNCTIONS (PTF) AND NON-LINEAR KINETICS
N yon G6tz* and O Richter**
*BASF AG, Agricultural Center Limburgerhof Environmental Fate APD/RB,
P.O. Box 120, D-67114 Limburgerhof Germany
**Technical University of Braunschweig, Institute of Geoecology, Langer Kamp 19c,
D-38106 Braunschweig, Germany
Abstract
The degradation behaviour of bentazone in 14 different soils was examined at constant temperature and
moisture conditions. Two soils were examined at different temperatures. On the basis of these data the
influence of soil properties and temperature on degradation was assessed and modelled. Pedo-transfer
functions (PTF) in combination with a linear and a non-linear model were found suitable to describe the
bentazone degradation in the laboratory as related to soil properties. The linear PTF can be combined with a
rate related to the temperature to account for both soil property and temperature influence at the same time.
1 Introduction
For the judgement of pesticide behaviour in the environment, simulation models become more and more
important. The problem one faces in modelling degradation of pesticides in the field is the variability of the
degradation rate related to both the soil properties and the climatic factors temperature and moisture.
Whereas functions describing the influence of the latter on the degradation of pesticides are well established
in common simulation programs such as PESTLA, PELMO and others [1,2], the influence of soil properties
on the degradation is usually neglected. Depending on the nature of the pesticide, the soil properties organic
carbon content (Corg), clay or pH can be important for its degradation rate. Hence, for the development of.
pedo-transfer functions (PTF's) first the important soil properties have to be identified and then the relation
has to be quantified (e.g. with a regression function).
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