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In Denmark the supply of drinking water is based almost
solely on groundwater. During the past few decades Danish
groundwater monitoring has encountered numerous in-
stances of pollution with pesticides and their metabolites
(GEUS 2003a). As a result, some hundreds of abstraction
wells out of about 8000 in general water supply have been
closed. With this background, there is a particular concern
for reducing the leaching of pesticides into the groundwater.
In the present study an approach for identification of areas
potentially prone to pesticide leaching is described.
The potential risk of leaching of pesticides from agricul-
tural areas into groundwater is minimised through a proce-
dure of approval; however, some leaching still occurs (GEUS
2003b). The Danish counties are therefore obliged to identify
areas where there is a particular risk of pesticide leaching, and
where restrictions in use of pesticides may be introduced to
reduce the risk (Miljøstyrelsen 2000).
The Geological Survey of Denmark and Greenland
(GEUS) and the Danish Institute of Agricultural Sciences
(DJF) have carried out a project, focusing on sandy agricul-
tural areas, that attempts to establish the necessary back-
ground knowledge for identifying areas particularly prone to
pesticide leaching. The project aims to distinguish vulnerable
and less vulnerable areas, both locally and nationwide, in a
Aim and approach
The conditions under which pesticides leach from the ground
surface into aquifers have been intensively investigated (e.g.
Flury 1996; Worral et al. 2002). A general knowledge as to
the circumstances and parameters that determine the fate of
pesticides is thus already available. The objective of the pro-
ject has been to establish a consistent set of data for Danish
conditions, which will allow spatial comparison of pesticide
leaching vulnerability on the basis of parameters that are
known, or suspected to, influence leaching.
Since mapping is the key to the identification of vulnera-
ble areas, emphasis has been placed on generating a set of data
based on soil parameters that can be easily and relatively inex-
pensively obtained. For this purpose field sites have been cho-
sen within eight areas of western Denmark (Jutland) with
different geological settings (Fig. 1). For each site, measuring
of geological and pedological profiles have been carried out
and samples collected for analysis.
To determine which areas are the most vulnerable to leach-
ing, simulations have been carried out using the MACRO4.3
model (Jarvis 2002). The relationships between soil hydraulic
properties, pesticide sorption (sensu e.g. Dubus et al. 2001)
and disappearance (Beulke & Brown 2001), and the more
readily obtainable soil parameters (here termed `inherent soil
parameters'), have been investigated on the basis of data
obtained from the field sites, pre-existing databases and the
Studies have aimed at determining the extent to which
pesticides as a whole, or in characteristic groups, will leach
under similar boundary conditions and reflect different com-
binations of inherent soil parameters.
Pesticide leaching in Danish groundwater:
identification of vulnerable areas
Erik Nygaard, Vibeke Ernstsen, Carsten S. Jacobsen, Ole H. Jacobsen, René K. Juhler,
Peter van der Keur, Svend E. Olesen, Jim Rasmussen, Per Rosenberg and Henrik Vosgerau
Fig. 1. Location of the studied field sites in Jutland, Denmark. The soil
types of the eight selected areas are also shown.
Geological Survey of Denmark and Greenland Bulletin 4, 2528 (2004) © GEUS, 2004
The study of vulnerability to leaching is focused on criteria
that are robust with respect to climatic variation and land use.
All the field sites chosen were on pig farms, with normal crop
rotation, farm manure application, and the relevant pesti-
cides were applied to the maximum permitted. The pesticides
MCPA, metribuzin and glyphosat, and methyltriazinamin, a
transformation product of tribenuronmethyl, have been stu-
died in most detail.
For glyphosat, sorption values and disappearance rates are
so high that leaching could not be simulated.
Repeated model simulations (MonteCarlo type) for metri-
buzin indicated that leaching will occur at significant levels,
while no leaching could be simulated for MCPA and methyl-
triazinamin (Fig. 2).
To illustrate the possible relationships, e.g. the hydraulic
properties of the soil and the degree of leaching, eight differ-
ent combinations of sorption and degradation properties of
the topsoil and the lower soil were designed (Fig. 3). These
combinations represent a wide range in properties for which
the occurrence of leaching can be simulated. Such designed
compounds are therefore suitable for further analysis.
Keeping the sorption and disappearance parameters con-
stant, the influence of hydraulic properties on leaching can
also be studied (see below).
These simulations were undertaken for the sandy soil pro-
files stored in a DJF nationwide database (Fig. 2). The results
indicate that maintaining the disappearance rate constant,
the sorption properties of the topsoil will generally dictate the
level of leaching (Fig. 3). Cross-plots of the simulation results
for the designed compounds further indicate, by their good
correlation, that irrespective of the combination of designed
parameters, leaching will dominantly occur in the same soil
profiles (Fig. 4).
Fig. 2. Normalised concentration of metribuzin at a depth of 1 m in all
sandy soil profiles stored in a national database held at DJF (one profile
for every 50 km
Fig. 3. Number of investigated profiles ranked according to potential for
leaching of eight designed combinations of pesticides. The ranking array
of profiles is different for the eight curves; see also Fig. 4.
The input parameters for simulation (sorption, disappear-
ance and hydraulic properties) are expensive to establish and
therefore not viable for extensive or general mapping.
Consequently, using a correlation analysis, an attempt has
been carried out in order to substitute these parameters by
more readily available soil parameters. The key inherent soil
parameters evaluated are soil grain size distribution, soil bulk
density, organic carbon content, cation exchange capacity,
pH, the content of oxalate and dithionit extractable iron and
aluminium. Indicators of biological activity have also been
evaluated (arylsulphatase activity and substrate induced res-
Two methods of correlation analysis have been applied to
study the possible correlation between inherent soil proper-
ties, hydraulic properties and pesticide specific parameters:
neural network computing and multivariate data analysis.
Based on neural networking computing, soil water release
curves have been estimated from hydraulic properties, and a
satisfactory prediction of the soil-water release characteristics
obtained (Fig. 5).
Measured values of sorption and disappearance rate have
been correlated with the key inherent soil parameters by mul-
tivariate data analysis (Esbensen 2002). The sorption and dis-
appearance values were predicted at the 85% level of variance
for the investigated pesticides (Fig. 6).
The number of soil parameters required to obtain this cor-
relation vary according to pesticide type. The content of
organic carbon in the topsoil is generally the most important
soil parameter, but other soil parameters such as pH and clay
content were also important in some examples.
Grouping of pesticides
Extensive analyses have been carried out for a large group of
pesticides at a few localities, in order to clarify whether the
results with respect to the four intensely studied compounds
can be applied to a broader group of pesticides. This has been
investigated by correlation analysis between inherent soil
properties and sorption for all the compounds. These inves-
tigations suggest that pesticides may be arbitrarily grouped in
one or a few major groups, which have similar relationships
to inherent soil parameters. The two compounds that do not
correspond with the explanation (glyphosat and the meta-
bolite 4 isopropyl aniline from isoproturon) are relatively
strongly sorbing and degrading in sandy soils.
Fig. 4. Cross-plots of leaching of pairs of hypothetical pesticides in Fig.
3. The plots illustrate the extent to which the hypothetical pesticides leak
through the same profiles. A: Low correspondence between profiles with
the least leaking pesticides with high sorption in the topsoil and less in
the lower soil. B: High correspondence between profiles with interme-
diate leaking pesticides with high sorption in the topsoil and none in the
lower soil. C: High correspondence between profiles with the most leak-
ing pesticides with low sorption in the topsoil and none in the lower soil.
D: Two families of relatively high correspondence, where one profile has
high sorption and low disappearance in the topsoil, and the other has
low sorption and high disappearance in the topsoil.
Fig. 5. Measured versus neural-network predicted retention curves for
three of the investigated soil types.
Delineation in practice
Based on correlations of soil parameters and leaching, and
grouping of pesticides, the values of soil and other parameters
that may be useful for identifying soils where leaching may
occur, have been investigated. Knowing the rank of impor-
tance of the soil parameters, and possibly their critical values,
criteria have been established for a two-phase approach in
mapping. It is suggested that, initially, areas with little risk of
leaching may be identified and delineated based on the few
most descriptive soil parameters. These parameters can to
some extent be obtained from existing geographical data, and
the cost of establishing new data is relatively low. The remain-
ing areas particularly prone to leaching can be mapped on the
basis of soil parameters necessary for simulating and predict-
ing the leaching of the pesticides.
Beulke, S. & Brown, C.D. 2001: Evaluation of methods to derive pesti-
cide degradation parameters for regulatory modelling. Biology and
Fertility of Soils 33(6), 558564.
Dubus, I.G., Barriuso, E. & Calvet, R. 2001: Sorption of weak organic
acids in soils: clofencet, 2,4-D and salicylic acid. Chemosphere
Esbensen, K.H. 2002: Multivariate data analysis in practice, 598 pp. Oslo,
Norway: CAMO Process AS.
Flury, M. 1996: Experimental evidence of transport of pesticides through
field soils: a review. Journal of Environmental Quality 25, 2545.
GEUS 2003a: Grundvandsovervågning 2003, 110 pp. København,
Danmark: Danmarks og Grønlands Geologiske Undersøgelse.
GEUS 2003b: The Danish pesticide leaching assessment programme,
monitoring results, May 1999 to June 2002. Third report, 123 pp.
Copenhagen, Denmark: Geological Survey of Denmark and
Greenland, Danish Institute of Agricultural Sciences, National
Environmental Research Institute.
Jarvis, N.J. 2002: The MACRO model (Version 4.3). Technical description.
Available at: http://www.mv.slu.se/bgf/
Miljøstyrelsen 2000: Zonering. Vejledning 3, 156 pp. København,
Worral, F., Besien, T. & Koplin, D.W. 2002: Groundwater vulnerability:
interactions of chemicals and site properties. The Science of the Total
Environment 299, 131143.
Fig. 6. Measured versus model-predicted sorption (Kf) for MCPA using
multivariate data analysis.
E.N., V.E., C.S.J., R.K.J., P.v.d.K., J.R., P.R. & H.V., Geological Survey of Denmark and Greenland, Øster Voldgade 10, DK-1350
Copenhagen K, Denmark. E-mail: email@example.com
O.H.J. & S.E.O., Danish Institute of Agricultural Sciences, Blichers Allé, Postbox 50, 8830 Tjele, Denmark.