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www.elsevier.com/locate/scitotenv
Science of the Total Environm
Modelling through-soil transport of phosphorus to surface waters
from livestock agriculture at the field and catchment scale
M.B. McGechana,T, D.R. Lewisa, P.S. Hoodab
aResearch Division, Scottish Agricultural College (SAC), Bush Estate, Penicuik, Edinburgh EH26 0PH, UKbSchool of Earth Sciences and Geography, Kingston University, Kingston upon Thames, Surrey KT1 2EE, UK
Available online 29 March 2005
Abstract
A model of phosphorus (P) losses in a small dairy farm catchment has been set up based on a linkage of weather-driven
field-scale simulations using an adaptation of the MACRO model. Phosphorus deposition, both in faeces from grazing livestock
in summer and in slurry spread in winter, has been represented. MACRO simulations with both forms of P deposition had been
calibrated and tested at the individual field scale in previous studies. The main contaminant transport mechanism considered at
both field and catchment scales is P sorbed onto mobile colloidal faeces particles, which move through the soil by macropore
flow. Phosphorus moves readily through soil to field drains under wet conditions when macropores are water-filled, but in dry
soil the P carrying colloids become trapped so losses remain at a low level. In the catchment study, a dairy farm is assumed to be
composed of fields linked by a linear system of ditches which discharge into a single river channel. Results from linked
simulations showed reasonable fits to values of catchment outflow P concentrations measured at infrequent intervals. High
simulated outflow P concentrations occurred at similar times of year to high measured values, with some high loss periods
during the summer grazing season and some during the winter when slurry would have been spread. However, there was a lack
of information about a number parameters that would be required to carry out a more exact calibration and provide a rigorous
test of the modelling procedure. It was nevertheless concluded that through soil flow of colloid sorbed P by macropore flow
represents a highly plausible mechanism by which P is transported to river systems in livestock farming catchments. This
represents an alternative to surface runoff transport, a mechanism to which high P losses from livestock farming areas have
often been attributed. The occurrence of high simulated levels of loss under wet conditions indicates environmental benefits
from avoiding slurry spreading on wet soil or during rain, and from some forms of grazing management.
D 2005 Elsevier B.V. All rights reserved.
Keywords: Water contamination; Phosphorus; Livestock; Grazing; Slurry; Catchments; Modelling
0048-9697/$ - see front matter D 2005 Elsevier B.V. All rights reserved.
doi:10.1016/j.scitotenv.2005.02.015
T Corresponding author. Tel.: +44 131 535 3029; fax: +44 131
535 3031.
E-mail address: [email protected]
(M.B. McGechan).
1. Introduction
It is commonly thought that phosphorus (P)
pollution of surface waters arises mainly in arable
cropped fields, with much of the P transport asso-
ent 344 (2005) 185–199
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199186
ciated with soil-derived sediments detached and
mobilised as the result of tillage operations. However,
there is now a growing body of evidence that high
levels of P pollution can also arise from grassland
fields in pastoral farming areas. Hooda et al. (1997)
measured P losses to stream water in agricultural
catchments in Scotland, observing higher losses in
catchments with intensive dairy farming in the west
than in less intensively stocked/arable catchments in
the northeast. It was assumed at the time of this study
that the main transport route by which P moved to
streams was surface runoff (overland flow). However,
more recent field-scale modelling studies, supported
by measurements of P losses on a dairy farm (Hooda
et al., 1999) suggest that a form of through-soil
transport represents another route by which P can
pollute surface waters. This appears to arise both
during slurry spreading (McGechan et al., 2002;
McGechan, 2002), and during grazing (McGechan,
2003). In this paper the field-scale modelling
approach has been extended to the catchment scale,
in order to investigate whether this through-soil
transport mechanism can account for a proportion of
the high losses in dairy farming catchments measured
by Hooda et al. (1997).
2. Background to modelling soil phosphorus
transport
Whereas many models of field-scale soil nitrogen
(N) processes and dynamics have been developed,
with transformations between pools (representing
different forms of N) and transport of mobile (soluble)
forms in soil water to drainage systems, there are
comparatively few models of soil P processes. The
only known field-scale models which have their own
distinct representation of soil P dynamics (as reviewed
by Lewis and McGechan, 2002) are ANIMO (Groe-
nendijk and Kroes, 1997; Kroes and Rijtema, 1998),
EPIC (Jones et al., 1984; Sharpley and Williams,
1990) and CENTURY (Parton et al., 1987; Metherell
et al., 1993a,b). A further three models, CREAMS
(Knisel, 1988), GLEAMS (Leonard et al., 1987;
Knisel, 1993) and ICECREAM (Simes et al., 1998),
all have copies of the same set of basic equations for P
processes as EPIC. However, all these models were
initially developed as soil N dynamics models, but
additional routines have since been added to represent
P processes, generally by relatively simple adaptations
of the equations for soil N processes with representa-
tion of through-soil transport for soluble P only. Also
in EPIC and its associated models, there is an
emphasis on surface transport rather than through
the soil transport of P.
Catchment-scale modelling of P transport is
usually based on the use of Geographic Information
Systems, and has often been considered alongside N
transport. Models include AGNPS, which is an event-
based distributed parameter model that computes flow
and pollutant loadings for a single rainfall event.
AGNPS calculates runoff from agricultural watershed
and the transport processes of sediment, N and P
(Young et al., 1995). TOPCAT-P is a simplification of
TOPMODEL (Dayawansa, 2002) and uses soil
moisture stores and subsurface flow equations plus
representation of P processes as in EPIC. The
distributed catchment models SHETRAN (Ewen et
al., 2000) and SWAT (Arnold et al., 1994; Kirsh et al.,
2002) have also recently incorporated a P component
to predict event-based P loading to surface waters.
There are in fact significant differences between
the behaviour of N and P in the soil, particularly that
N compounds are very soluble to move with soil
water, whereas P has a lower solubility so is
transported extensively in particulate or colloidal
forms with various restrictions on their movements.
Also, P compounds are dreactive solutesT, so are
highly sorbed onto surfaces of soil components. In
early studies of soil P processes (e.g. Barrow, 1978,
1983, as reviewed by McGechan and Lewis, 2002a),
it was assumed its high sorbability would lead to P
being applied in mineral fertiliser or manure becoming
locked up in the soil, so it would not readily leach out
in water flows to drains. More recent studies have
drawn attention to the fact that a large proportion of
the area of sorbing surfaces in the soil is on the
smallest particles (such as clay), which readily
become detached from the soil matrix, and so become
highly mobile in soil water flows. It is now becoming
clear that sorption onto mobile suspended or colloidal
soil particles is an important mechanism leading to
leaching of P to drains. Slurry (liquid manure)
contains large quantities of finely divided insoluble
or colloidal particles of organic matter, onto which
inorganic compounds of P in the slurry tend to be
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199 187
attached by sorption. Also, faeces deposited on the
soil surface by grazing animals has similar character-
istics to slurry regarding the abundance of P-sorbing
colloidal particles. When slurry or dung is deposited
on the soil, some of these P carrying particles find
their way into water flows and to drains.
Particulate or colloidal material moves less freely
than solutes in moving soil water, since it can be
subjected to straining and filtration processes. How-
ever, restrictions on movements are greater for larger
particles and for flows through smaller pores (as
discussed in relation to literature on filtration theory
by McGechan and Lewis, 2002b). The largest soil
pores or dmacroporesT impose very little restriction on
movements of such particles, and also water flows in
macropores tend to be very fast leading to rapid
transport of pollutants to drains. High P loads have
been observed in field drains during the first week or
two following spreading slurry in winter, and also
during grazing by livestock in late autumn (Hooda et
al., 1999), which can only be accounted for by
macropore flow. There are a few other recent studies
from Europe reporting substantial through soil P
losses of a similar nature. Stamm et al. (1988)
observed raised concentrations of P during large
rainfall/drainage events in grassland soils. This
suggests mobilisation of colloid material, since if this
did not occur a lower concentration due to dilution of
the soil solution by incoming rain would be expected.
Similar raised P concentrations during rainfall events
have been observed in through soil leaching from
grassland by Hawkins and Scholefield (1996) and by
Haygarth et al. (1998), and in arable soils by Ulen
(1995) and Grant et al. (1996). These studies also
support the hypothesis that colloid facilitated transport
plays an important role in through soil leaching of P to
receiving waters, as represented by the modelling
exercise described in this paper.
The type of macropore flow considered here takes
place in very wet conditions in aggregated soils (as
opposed to that taking place in cracking clay under
dry conditions). Water-filled inter-aggregate spaces
provide an unrestricted route for rapid water move-
ment, and suspended colloidal particles also pass with
almost no restriction in such flows. Some simulation
models of soil water movement provide representation
of macropore flows, but with varying levels of
sophistication. Out of all known models, the MACRO
model (Jarvis, 1994) has the most comprehensive
treatment of macropore flow; it has representation of
distinct macropore and soil matrix pore regions (or
a domainsa ), with different equations governing water
movement and solute concentrations in each domain.
Recently developments of MACRO include a new
feature of colloid facilitated transport of reactive
(sorbed) contaminants (Jarvis et al., 1999). The main
application of MACRO up to now has been concerned
with movements of pesticides. However, some pesti-
cides exhibit behaviour similar to P, such as sorption
onto surfaces both on mobile colloidal particles and in
the static soil matrix. Parameterisation and testing of
the MACRO model to represent some of the
important soil P loss processes from grazed fields
and fields receiving slurry applications have been
described by McGechan et al. (2002) and McGechan
(2003). In this current paper the parameterised field-
scale model has been extended to carry out scenario
testing for a small catchment in a dairy farming area,
where cows are grazed during the summer months and
slurry is spread on various occasions throughout the
winter.
3. The MACRO model for representation of
phosphorus transport at the field scale
3.1. Basic features of model
The main features of the standard MACRO model,
including the basic equations for water and solute
transport in two ddomainsT, have been described in
detail by Jarvis (1994). A further evaluation of the
model and its equations has been presented by Larsson
and Jarvis (1999). All of these features are retained in
the special version of MACRO used in this study.
3.2. Hydrology
The MACRO model simulates water movements,
both vertically through the profile with a proportion
percolating to deep groundwater, and horizontally to
the back-filled trenches in which field (tile) drains are
located. The hydrological routines in MACRO are
similar to many other soil water models, with the
tension (water release) and hydraulic conductivity
relationships for specified layers in the soil profile
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199188
represented by mathematical functions, enabling
Richards’ (1931) equation to be solved at successive
timesteps. MACRO differs from other models in its
treatment of processes in the larger soil pores (macro-
pores) when capillary forces are very low, so water
movements can be assumed to be driven by gravita-
tional forces alone. The boundary between the macro-
pore and soil matrix (micropore) domains is
considered to occur at a soil water tension (ub) of
1.2 kPa, with corresponding water content (hb) and
hydraulic conductivity (Kb) values given by mathe-
matical functions (Fig. 1). In the soil matrix pore
region where both capillary and gravitational forces
must be considered, the hydraulic functions are as
described by Brooks and Corey (1964) and Mualem
(1976). In MACRO, contaminant transport is treated
separately with different concentrations in each of the
two domains. Calibration of the hydraulic processes,
including selection of parameters of the hydraulic
function equations for two soil types, has been
described by McGechan et al. (2002) and McGechan
(2002). Calibration also assumed that most of the
drainage water would pass to the field (tile) drains, but
a small proportion (estimated by a balance procedure
described by McGechan et al., 1997; McGechan,
2002) would pass to deep groundwater by percolation.
-1000Soil water tension, kPa
ϕ b
θs
θ b
Ks
Kb
Vol
umet
ric
soil
wat
er c
onte
nt
Log
hyd
raul
ic c
ondu
ctiv
ity
Soil matrix pores(micropores)
Macropores
Fig. 1. Two-domain representation of hydraulic properties assumed
in MACRO (Ks is the total saturated hydraulic conductivity, Kb is
the saturated conductivity of the soil matrix pores, hs is the total
saturated water content, hb is the saturated water content of the soil
matrix pores, and ub is the soil water tension at which the soil
matrix pores are saturated but the macropores contain no water);___, soil water tension; _ _ _ , hydraulic conductivity.
Upper boundary conditions with evapotranspiration
from a grass according to the Penman/Monteith
equation are represented using an option in the model
for a perennial crop.
3.3. Colloid facilitated contaminant transport
The special version of MACRO used in this study
has additional features to represent a contaminant
which is transported by attachment to mobile colloids
(Jarvis et al., 1999). Colloids can be soil-derived by
rainfall impact at the soil surface (not used here) or
added in an dirrigationT application of water to the soil.The so-called irrigation procedure is used here to
represent both winter slurry applications (McGechan
et al., 2002), and deposition of faeces by grazing
animals during summer months (McGechan, 2003).
Simulations are carried out describing transport both
of colloids and the contaminant (P in this case). The
concentrations of colloids and P in the applied
dirrigationT water must be specified.
3.4. Sorption
P is transported through the soil both in soluble
form and attached to mobile colloids by sorption. The
inorganic components of P in slurry (as in soil) are
particularly strongly sorbed onto mobile colloids as
discussed by McGechan and Lewis (2002a). In
MACRO, representation of sorption of the contami-
nant onto solid surfaces follows the Freundlich
equation:
Q ¼ KdCn ð1Þ
where Q is the quantity of P sorbed in g [P] kg�1
[soil], C is the concentration of P in solution in mg
l�1, Kd (or Kc for colloids) is the sorption coefficient
and n is an exponent indicating the non-linear form of
the equation.
In the special version of MACRO sorption can take
place onto both mobile colloids and static soil
components, with a separate set of coefficients in
Eq. (1) for each (and the exponent n constrained to a
value of unity for mobile colloids only). The same set
of coefficient values (specified according to layers for
the soil, Table 1) have been used here as selected in
previous studies for slurry (McGechan et al., 2002)
and faeces deposited by grazing animals (McGechan,
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Table 2
Physical and hydraulic parameters of silty clay loam grassland soil
Layers Topsoil Subsoil
Surface Lower
Layer depth (m) 0–0.1 0.1–0.3 0.3–1.0
Porosity, hs (%) 52.6 49.9 46.2
Dry bulk density (kg m�3) 1.26 1.33 1.43
Pore size distribution index
(Brooks and Corey, 1964)
0.026 0.023 0.035
Residual water content
(% volumetric basis)
4.0 4.0 4.0
Macroporosity, hs–hb (%) 2.35 3.01 1.08
dBreak pointT tension, ub (kPa) 1.21 1.20 1.20
Saturated hydraulic conductivity,
Ks (mm h�1)
375 208 166.7
Hydraulic conductivity at break
point, Kb (mm h�1)
1.746 0.84 0.175
Drain spacing (m) 7.0
Drain depth (m) 0.65
Table 1
Colloid and phosphorus (P) transport parameters
Parameter Parameter
value
Reference filter coefficient for macropores, (m�1) 0.5
Reference flow velocity in macropores (m h�1) 50
Filtering exponent in macropores (dimensionless) 1.8
Filter coefficient in soil matrix pores (m�1) 40
Freundlich sorption coefficient (linear) for
P sorption on colloids, Kc (m3 g�1)
2.7
Initial soil sorbed P (Olsen test P) (mg P kg�1 soil) 38
Freundlich sorption exponent for P sorption onto
soil, n
1.65
Freundlich sorption coefficient for P sorption onto
soil, Kd (ln mg1�n kg�1)
soil layer depth 0–0.1 m 203
0.1–0.2 m 307
0.2–0.3 m 350
0.3–0.4 m 4500
0.4–0.5 m 5500
0.5–1.5 m 6500
M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199 189
2003). Initial values of soil inorganic P set at the start
of simulations, based on information from the ‘Olsen
P’ test (a commonly used agronomic test for soil P
fertility), as measured by Hooda et al. (1999, 2000),
were retained from the earlier slurry study.
3.5. Colloid trapping
Trapping and filtration equations, and their
parameters, in the special version of MACRO used
here are described in detail by Jarvis et al. (1999)
and McGechan et al. (2002). Filtration in soil matrix
pores is described by a simple filtration coefficient,
while the macropore filtration coefficient is specified
at a reference flow velocity, then adjusted to the
actual flow velocity according to a power relation-
ship. Coefficient values (Table 1), selected to
simulate trapping most of the colloids if they enter
soil matrix pores but allow almost completely free
movement in macropores, have been retained from
the previous studies (McGechan et al., 2002;
McGechan, 2003).
3.6. Field sites for field-scale model calibration
The MACRO model has previously been cali-
brated and tested at the field scale for two Scottish
soil types, including a silty clay loam (USDA
classification) under grass with hydraulic parameters
listed in Table 2. Simulated results were tested against
measurements of water flows and P concentrations in
water at fields with drainflow measurement equip-
ment, at Bush near Edinburgh, and at the Crichton
Royal Farm, Dumfries in the predominantly dairy
farming area of SW Scotland. Details and layouts of
hydrologically isolated plots with equipment for
measurement of drainflow quantities and contaminant
concentrations, are described by Vinten et al. (1991,
1992, 1994), McGechan et al. (1997) and Hooda et al.
(1998, 1999). Near saturation hydraulic conductivities
were measured using a tension infiltrometer method
(Jarvis and Messing, 1995), and water release
characteristics had also been measured (McGechan
et al., 1997).
3.7. Phosphorus and colloids in slurry
Slurry was assumed to be applied at a rate of 50
m3 ha�1, the maximum permissible under codes of
practice for environmental protection (SEERAD,
2002). This gave an application of 5 mm of water
in the ‘irrigation’ routine in MACRO (at a specific
spatial location), which was assumed to take place
over a 0.0003 h (1.0 s) period commencing at 10:00
h on the application day. Two alternative sets of
assumptions were made regarding slurry composi-
tion. In the first set, concentrations of 3700 g m�3
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199190
of faecal colloids and 178 g m�3 of inorganic
phosphate were assumed, corresponding to the
slurry application on 21 November 1994 at the
Dumfries site reported by Hooda et al. (1999) and
McGechan et al. (2002). This represents a fairly
dilute slurry (dry matter content around 3.5%)
arising where dirty water, dairy washings and other
farm wastes have been added. The second set
represented a more concentrated slurry (7% dry
matter content) with concentrations double those for
the dilute slurry. A concentration of inorganic P of
356 g m�3 corresponds to a typical value for the
davailableT P2O5 component of 7% dry matter
content dairy cow slurry reported by Dyson
(1992). The quantity of slurry of 7% dry matter
content produced by 190 dairy cows (see Section
4.2) over a 26-week housing period is given by Dyson
(1992) as 2610 m3, which would require 53 ha of land
area for spreading at 50 m3 ha�1. On a 50-ha farm, the
more concentrated slurry would thus require a second
application each year on a small part of the land area,
whereas the more dilute slurry would require exten-
sive repeated applications.
3.8. Phosphorus and colloids in faeces from grazing
livestock
The daily average quantity of inorganic P
excreted in faeces by a dairy cow was estimated as
26.2 g. This was based on figures presented for a
model dairy farm by Haygarth et al. (1998), which in
turn was based on a similar study for N cycling on a
dairy farm by Jarvis (1993). The model dairy farm
had an autumn calving herd so P excretion was
much higher in winter than summer, whereas for a
spring calving herd the reverse would be the case, so
for the current study the average daily figure was
assumed. A similar daily value of 23.6 g P was
estimated from data presented by Dyson (1992) for
slurry produced by winter housed dairy cows.
Assumptions about dung patch dimensions were
based on values presented by Lantinga et al.
(1987), although broadly similar figures (or ranges
of values in some cases) were also presented by
MacLusky (1960) and Richards and Wolton (1976).
Adult dairy cows were assumed to produce 12
defaecations of 1.0 l, each day in the field. A dung
patch covers 0.05 m2, giving an initial height of 20
mm for the patch. However, it was further assumed
that about 15 mm of liquid (containing much of the
colloidal material and colloidally attached P) would
rapidly infiltrate the soil surface, leaving a patch of
height 5 mm containing the larger particles of dry
matter. Assumed concentrations of colloids and P in
the water infiltrating the soil surface were adapted
from those previously estimated for slurry (McGe-
chan, 2002, 2003). This gave concentrations of 65.5 g
l�1 of colloids and 3.15 g l �1of inorganic P in the
infiltrating water.
Petersen et al. (1956), Richards and Wolton
(1976) and Hack-ten Broeke et al. (1996) have
discussed the probability of both dung or urine
patches being deposited over areas contaminated by
recent previous defaecations or urinations. Petersen
et al. (1956) fitted a binomial distribution to
experimental data describing spatial distribution of
excreta from grazing animals. For a stocking density
of 3.8 cows ha�1, 12 daily defaecations cover
0.024% of the land area, so double contamination
over a time interval of a few days is a relatively rare
occurrence and has been ignored in this study. In the
simulations, results estimated from the land area
under dung patches were combined with those from
areas receiving no dung on that day, to give a
weighted average daily P loss for a daily inorganic P
input of 314.4 g ha�1 (from 26.2 g cow�1 day�1
and a stocking density of 3.8 cows ha�1). In this
combination calculation, an adjustment was made to
base the P losses on the hydrology and drainflows
from areas receiving no dung (McGechan, 2003).
This procedure set losses to zero on days where
drainflow appeared to take place in simulations
representing the dung patch area (0.023% of the
field area) with a 15-mm water application, but no
drainflows would have taken place over the whole
field which is dominated by the hydrology with no
additional water applied.
3.9. Calibration of field-scale model
Calibration and testing of the field-scale model has
been described in detail by McGechan et al. (2002),
McGechan (2002, 2003). An example of simulated
against measured P losses is shown in Fig. 2, for a
grassland field which was grazed by dairy cows
(stocking rate 4 cows/ha) from 27 September to 12
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Fig. 2. Comparison between simulated and measured cumulative phosphorus (P) flows to field drains at grassland site with autumn grazing
followed by a slurry application. Cumulation from the start of simulation period (1 October) and from slurry application date. ., measured total
inorganic P; _____ , simulated total inorganic P; _ . _ . _ . _ , simulated colloid-sorbed inorganic P; - - - - -, simulated dissolved inorganic P.
M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199 191
November 1994, and received a slurry application on
21 November 1994. This assumed parameter values as
listed in Tables 1 and 2, as well as P and colloid
quantities as described in Sections 3.7 and 3.8. Both
measured and simulated values illustrate the high
levels of P loss that can occur due to livestock faeces
deposition under wet soil conditions, and that the high
loss level lasts for only a short time following a slurry
application. Although measurements were only for
total inorganic P, simulated results indicate that losses
were predominantly of colloid sorbed P during
grazing and immediately after slurry spreading,
whereas the background loss occurring more than a
week after slurry spreading was almost entirely of
soluble P.
3.10. Field-scale predictive simulation procedure
Weather-driven simulation runs were carried out
using the special version of MACRO in predictive
mode to test the effect of spreading slurry each day
in October–March 1993–1994 and 1994–1995.
Similar simulations were carried out to test the
effect of a dung patch deposited each day in April–
September 1994 and 1995. Weather data included
daily rainfall recorded at the Caddell site where
catchment-scale P losses had been measured (Sec-
tion 4.2). However, in order to estimate evaporation
the MACRO model requires a number of other
weather parameters which had not been recorded at
the site, so use was made of values recorded at nearby
sites in Ayrshire (Prestwick Airport for of sunshine
hours and SAC Auchincruive for four other parame-
ters). Each simulation was run for a 3-month period
from the first of the month prior to the deposition date.
Simulated losses of soluble and colloid-sorbed inor-
ganic P were recorded for a period of 21 days
following deposition. A procedure was set up based
on DOS batch files to generate the MACRO
parameter files in the correct format and to run the
repeated paired simulations for all the deposition date
options. A separate single dhydrologicalT simulation
was carried out over the period October 1993–
September 1995 with water inputs as rainfall only,
to determine drainflows in the absence of additional
water in slurry or dung.
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199192
4. Catchment-scale modelling
4.1. General principles
A catchment-scale hydrological model operates in
a similar manner to a field-scale hydrological model
in many respects. However, most field-scale models
assume for simplicity that conditions are spatially
homogeneous over the area considered, but this is
not the case at the catchment scale. Water, which
originates as precipitation, moves along flowpaths
from high levels in the catchment to the receiving
water body. All along such a flowpath, additional
water containing soluble or colloidal contaminants is
added from branches in the system, so the concen-
tration of contaminant in the main flow can increase
or decrease. Water can be transported horizontally as
surface runoff, through field drains or ditches, and
through soil pores. One approach to catchment-scale
modelling is to set up a linkage between the
CADDELL
RESERVO
UPPE60% GG;
0 250 500 750m
NORTH
240+ +200
+120
+170
+240
106+
+120
Fig. 3. Cellular diagram o
drainage outputs of field-scale simulations of indi-
vidual fields or cells in the catchment. Here we
assume that the dominant mechanism for transport of
contaminants to a river system is through the field
drainage network. To be linked in this way, field-
scale models generally require some simplification,
particularly as it is not normally feasible to measure
detailed soil hydrological parameters at all positions
in the catchment. For the current study, a simple
linkage was made of results from field-scale
simulations with MACRO, and assuming that hydro-
logical parameters are the same for all soils in the
dairy farm area, as for one of the two soils (the silty
clay loam, Table 2) for which detailed parameters
were known.
4.2. Field site for model testing at the catchment scale
Out of six sites studied by Hooda et al. (1997),
the Caddell catchment (Fig. 3) was one of three
IR
R CATCHMENT 26% MOORLAND
+160
100+
+90
+75
95% GG
IN
80+
70+OUT
f Caddell catchment.
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199 193
located in Ayrshire, one of the most intensive dairy
farming regions of the UK. Swards were rotatonally
grazed by dairy cows and cut for silage. Slurry was
spread periodically during winter when cattle are
housed. The total catchment area is 750 ha. Soils in
the catchment were described as non-calcareous,
calcareous or humic gleys. Some information was
recorded about nutrient status, but no detailed
hydrological soil parameters were measured. Stream
water flows and P concentrations were measured at
the upstream and downstream ends of a 1.5-km
length of stream, which received field drain outflows
from a 50-ha intensive dairy farming area (Fig. 3)
with a stocking density of 3.8 cows ha�1 (total 190
cows). Sampling took place at 3-week intervals
during the first year (October 1993–September
1994) and at weekly intervals during the second
year (October 1994–September 1995). Daily rainfall
was also recorded over the period 9 March 1993–30
September 1995.
S2
S5
S3 S3
S4
S5
S4
S5
S4
S5
S3
S4
S5
S1
S2
S1 F1
DF1
RF1
Fig. 4. Hydraulic routine of drainage between system of linear storage chan
unlabelled intermediate tiers follow in order.
4.3. Fluvial geomorphology and timing of water
movements through a catchment
Water leaving an individual field in a catchment
does not immediately enter the receiving stream or
river. The delay which occurs depends on a number of
factors, including the direct field to river distance, the
routing of the flow path, and the current flow rate
(which is related to soil wetness and hence rainfall
history). Artificial drainage networks can be consid-
ered using the classical concepts of fluvial geo-
morphology in natural river basins. The quantitative
analysis of channel networks and classification of
stream orders was began by Horton (1945), and
extended by Mock (1971).
In the current study, the farm drainage network is
assumed to be a maximum of five orders, with an
average network length equal to 200 m. This allows us
to classify fields into five tiers according to their distance
and hydrological routing from the outlet (Fig. 4).
DF1
RF1
DF2
RF2
DF3
RF3
DF4
RF4
DF5
RF5
RIVER
TIER 1
TIER 2
TIER 3
TIER 4
TIER 5
F1
F3
F2
F4
F5
nels from fields in five tier categories. Tiers 1 and 5 only are labelled,
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199194
Furthermore in order to simplify the network we assume
that the width function which defines the average
network link distance from the outlet is linear. Hydraulic
routing of the drainage simulation of MACRO, between
a linear system of storage channels, is taken according to
a modification of the Muskingum Method for reservoir
routing (Bras, 1990). Under this methodology drainflow
DFi and runoff RFi from fields Fi passes into storage
channels Si (of order i) and is accordingly routed
towards the river. A minimum storage Smin of 2 m3 per
channel is assumed below which there is zero output
flow. The use of a minimum storage capacity in channel
reservoirs particularly effects summer fluxes of con-
taminants to the river.
4.4. Calculating stream P concentrations in
catchment
A procedure was set up in an Excel spreadsheet to
add up from the results of the individual simulations
the contribution to P losses on each day October
1993a September 1995 from deposition of slurry or
dung. For the summer period, the area covered each
day by dung patches was calculated for 190 cows. For
the winter period, a daily area for slurry spreading was
allocated (which could be zero on some days) such
that the total area spread over each winter was 53 or
106 ha (depending on the slurry dry matter content).
Since losses associated with slurry or dung deposition
on a particular day were recorded for the contami-
Tier 5
Tier 10
0.5
1
1.5
2
2.5
3
3.5
4
0 2 4 6 8
Drain flow
Del
ay (
days
)
Fig. 5. Duration of transit time for contaminant passing through catchment
field drainage rate for five tiers of fields with different field to stream dis
nated area for 21 days following, the total loss on a
particular day was potentially for 21 such areas each
contaminated by deposition on one of the previous 21
days. For both summer and winter periods, the
concentration of P in contaminated water on a
particular day from the relevant total contaminated
area was combined with the quantity of uncontami-
nated water from the remaining field area (given by
drainflows from the hydrological simulation) to give
the overall P concentration in drainflows from the
whole farm area.
For both slurry and dung patch drainage, delays are
introduced between release from a field and P
reaching the river, based on the concepts described
in Section 4.3 (Fig. 5). As there was no a priori
information regarding the spatial input distribution of
P in the form area, a uniform overall distribution has
been assumed. Finally, a calculation was carried out
using the upstream river flows and P concentrations
combined with those from the farm area to give an
estimate of the downstream river P concentration.
5. Results and discussion
5.1. Losses from individual simulations
The pattern of loss occurrence following deposition
of P in slurry or dung has been discussed in papers on
previous studies (McGechan et al., 2002; McGechan,
10 12 14 16 18 20
(mm day-1)
drainage system from field to receiving stream. Shown in relation to
tances.
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199 195
2002, 2003). In general, if deposition takes place when
soil is wet there is rapid transport with high P losses
over the first few days following deposition. After
about 3–4 days the rate of loss drops to a low level.
Losses are particularly high for the first few days if
rainfall occurs during that period. In contrast, if
deposition takes place when soil is relatively dry,
losses are generally at a low level. There is some rise in
loss levels if rain occurs soon after spreading, but not
to the same extent as if the soil had been wet at the time
of deposition. In general, high losses tend to be
predominantly of colloid sorbed P, whereas low losses
are predominantly of soluble P. This demonstrates the
importance of macropore flow of colloid-associated P
which occurs under wet soil conditions when macro-
pores are water-filled. In contrast, under dry conditions
only the smaller soil matrix pores (micropores) are
water-filled, so P carrying colloids become trapped
and P can only move in soluble form. Due to the high
sorbability and low solubility of P, soluble P losses
tend to be at a low level.
5.2. Stream outflow P concentration
Stream outflow P concentrations, calculated from
losses given by all the weather-driven simulations, are
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
93.8 94.0 94.2 94.4 94.6 9
Julia
Inor
gani
c P
conc
entr
atio
n (m
gP l -
1 )
Fig. 6. Simulated inorganic phosphorus (P) concentrations in Caddell str
during which slurry was spread. _____ , simulated concentration at outflow
inflow measurement point (sampled at weekly or three weekly intervals); xweekly or three weekly intervals).
shown alongside measured inflow and outflow P
concentrations in Fig. 6. Duplicate results were
determined based on simulations using soil hydraulic
parameters for each of the two soils for which they had
been measured in previous studies. In relation to slurry
spreading, results were also duplicated according to
whether the dilute or more concentrated slurry
composition had been assumed. Some manipulation
to improve fits (of predicted to measured outflow
concentrations) was carried out at this stage of areas
and days over and on which slurry was spread. This
was considered to be an acceptable procedure, since no
information had been recorded about when this slurry
spreading had taken place on the farm area, other than
the estimate of the total quantity which would have to
be disposed of.
Results based on simulations with hydraulic
parameter values for a clay loam soil show simulated
outflow P concentrations very much in excess of
measured values. In contrast, results based on the
hydraulic parameter values for the silty clay loam
soil with parameters listed in Table 2 show simulated
concentrations of a similar magnitude to measured
values (Fig. 6). Comparing results (shown in Fig. 6)
assuming spreading of the more concentrated (7%
dry matter) slurry with those for the more dilute
4.8 95.0 95.2 95.4 95.6 95.8
n date
eam outflow during two summer grazing seasons and two winters
measurement point (daily values); _____ , measured concentration at
, measured concentration at outflow measurement point (sampled at
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199196
(3.5% dry matter) slurry, losses were slightly higher
with the more dilute slurry. High simulated outflow
P concentrations occurred at similar times of year to
high measured values, with some high loss periods
during the summer grazing season and some during
the winter when slurry would have been spread.
However, there was a much larger day-to-day
fluctuation in concentrations than had been meas-
ured. Since spot measurements had only been made
on particular days at weekly at three weekly
intervals, such fluctuations would not be apparent
in the measured data. These simulated results were a
reasonable fit to the measured data with a chi-
squared per degree of freedom value of 0.11 (Lewis
et al., 1997), especially given the lack of hard
Fig. 7. Simulated inorganic phosphorus (P) concentrations in Caddell stream
(b) after introduction of network stores. __________ , simulated concentratio
concentration at inflow measurement point (sampled at weekly or three w
point (sampled at weekly or three weekly intervals).
information about a number of aspects which would
influence the results.
5.3. Effect of network storages
The major effect of storage channels with a
minimum storage below which there is zero channel
output is to delay the smaller field drainage flows and
to produce larger P fluxes in subsequent high flow
periods. This is exemplified in Fig. 7, which focuses
on the 1994 summer grazing season, and gives a
comparison of stream outlet fluxes for a system with
and without network stores. Several high P fluxes in
this period are due to accumulated P stored in the
channels, from small drainage discharges, prior to a
outflow during the low-flow grazing season in 1984. (a) before and
n at outflow measurement point (daily values); _____, measured
eekly intervals); x, measured concentration at outflow measurement
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M.B. McGechan et al. / Science of the Total Environment 344 (2005) 185–199 197
large hydrologic event, which then flushes P out of the
system.
6. Conclusions
In this study, a model of P losses in a small dairy
farm catchment has been set up based on a linkage of
weather-driven field-scale simulations using the
MACRO model. P deposition, both in faeces from
grazing livestock in summer and in slurry spread in
winter, has been represented. The main contaminant
transport mechanism considered has been P sorbed
onto mobile colloidal faeces particles, which move
through the soil by macropore flow. Phosphorus
moves readily through soil to field drains under wet
conditions when macropores are water-filled, but in
dry soil the P carrying colloids become trapped so
losses remain at a low level. The MACRO simulation
procedure had previously been calibrated and tested
for two soil types, and also both for P deposition in
slurry and in faeces from grazing animals.
Results based on linked simulations assuming
hydraulic parameter values for one particular soil
show reasonable fits to values of catchment outflow P
concentrations measured at infrequent intervals. The
catchment-scale measured data showed some periods
with high outflow P concentrations during the summer
grazing season and some during the winter when
slurry would have been spread. Results from the
linked simulations also showed some high outflow P
concentrations during both summer and winter, with
timing generally occurring at similar times of year to
high measured values. However, there was one period
during summer 1995 where high measured outflow P
concentrations were not reproduced in the simula-
tions. During this period the MACRO hydrological
simulations did not produce sufficient drainage flows.
It is of course possible to calibrate the field-scale
model to more accurately represent the catchment
hydrological outputs, but in this study we persisted
with the use of a single field calibration to characterise
the dairy farm area.
In general, the catchment-scale modelling work
was hampered by the infrequency of loss measure-
ments and a lack of information about a number of
parameters, which would be required to carry out a
more exact calibration and provide a rigorous test of
the procedure. In view of this limitation, the approach
taken could be regarded as scenario testing at the
catchment scale, based on a model which has been
rigourously calibrated and tested at the field scale. It
was nevertheless concluded that through soil flow of
colloid sorbed P by macropore flow represents a
highly plausible mechanism by which environmen-
tally harmful quantities of P are transported to river
systems in livestock farming catchments. This
represents an alternative explanation to supplement
or replace surface runoff transport, a mechanism to
which high P losses from livestock farming areas
have often been attributed. The occurrence of high
levels of loss under wet conditions indicates
environmental benefits from avoiding slurry spread-
ing on wet soil or during rain. There may also be
benefits during wet field condition in what would
normally be considered to be the grazing period,
from either housing the animals or moving them to
fields remote from the river or stream which drains
the catchment.
Acknowledgements
The author wishes to thank Professor Nick Jarvis
of the Swedish University of Agricultural Sciences for
assistance with adapting and using the MACRO
model. The Scottish Executive Environment and
Rural Affairs Department provided funds to carry
out the work.
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