Ibrahim et al. RIA

Ibrahim et al. RIA
T.G. Ibrahim, O. Fenton, K.G. Richards, R.M. Fealy and
M.G. Healy
T.G. Ibrahim,
O. Fenton
author; e-mail:
[email protected]
teagasc.ie) and K.G.
Richards, Teagasc
Research Centre,
Johnstown Castle,
Co. Wexford,
Ireland; R.M. Fealy,
Spatial Analysis Unit,
REDP, Teagasc,
Ashtown, Dublin 15,
Ireland; M.G. Healy,
Civil Engineering,
National University of
Ireland, Galway,
Cite as follows:
Ibrahim, T.G.,
Fenton, O., Richards,
K.G., Fealy, R.M. and
Healy, M.G. 2013
Spatial and temporal
variations of nutrient
loads in overland
flow and subsurface
drainage from a
marginal land site in
south-east Ireland.
Biology and
Proceedings of the
Royal Irish Academy
2013. DOI: 10.3318/
Received 13 March
2012. Accepted 13
June 2013. Published
3 November 2013.
In Ireland, Food Harvest 2020 focuses on increasing productivity while enhancing environmental
sustainability of agricultural land. On underutilised or marginal land, drainage systems may be
installed to expand agricultural enterprises. Mixed nutrient losses are inevitable from any drainage
system, but assessing processes leading to differences in nutrient speciation, fractionation and losses in
grasslands between locations or flow paths is important to achieve sustainability. This study
investigates these processes in overland flow and subsurface drains over three rainfall events from four
non-grazed plots recently converted from marginal land in the south-east of Ireland. A shallower
water table and smaller plot size resulted in greater water and nutrient losses in overland flow per unit
of land area. Nutrient losses were less in subsurface drains. Dissolved organic nitrogen (DON)
dominated, but dissolved inorganic nitrogen (DIN) was more abundant in the drains. Particulate
phosphorus generally dominated in drains, except in plots with a shallow water table where dissolved
unreactive phosphorus (DUP) was more abundant. In overland flow, a shallower water table resulted
in a switch from dissolved reactive phosphorus (DRP) to DUP. Fertilisation increased phosphorus
losses in overland flow, with DRP dominating. These results highlight the importance of an
integrated assessment of the controls on flow and nutrient losses to design drainage systems in
marginal lands.
In Ireland, Food Harvest 2020 (DAFF 2010) outlines
the future vision for Irish agriculture. It focuses on
increasing productivity while enhancing the environmental sustainability of agricultural land. Within
this framework, abolition of the European Union
(EU) dairy milk quota in 2015 (CEC 2008) will
allow for the expansion of the dairy sector.
Approximately 29% of Irish grasslands have poorly
drained soils (EEA 2009; Fealy et al. 2009). On such
marginal land, the water table in floodplains or in
areas of a perched aquifer is often shallow (Misstear
et al. 2009). These conditions, as well as high rainfall,
result in excess water in the soil, which can
significantly reduce grass yields, as well as limit
access to the fields by grazing animals and machinery
during wet periods (Mulqueen 1985; Brereton and
Hope-Cawdery 1988; Armstrong and Garwood
1991; Lalor and Schulte 2008). Often in these areas,
artificial drainage systems need to be installed to
allow sustainable grass production (Galvin 1983).
DOI: 10.3318/BIOE.2013.13
Thus, implementation of designed drainage systems (artificial pipes with drain spacing and depth
estimated using soil physical parameters) and
renovation or maintenance of existing systems
(tile drains and mole drains) on underutilised or
marginal land, is likely to increase in the coming
years in order to develop new grassland areas for
use by the dairy sector. In addition, previously
drained land will need modernization.
In agricultural landscapes, nutrients in water
can originate directly through fertiliser application
or animal excreta, or indirectly due to the effect of
poaching of land by cattle on nutrient infiltration
and cycling in soils (Watson and Foy 2001;
Richards et al. 2009). Enhancing the drainage
capacity of poorly drained soils can increase or
decrease losses of these nutrients to the environment (Skaggs et al. 1994). Artificially lowering the
water table can also result in bypassing areas of high
natural attenuation and further increase nutrient
losses (Gold et al. 2001). In turn, increasing nutrient
loading to surface water and groundwater bodies
ROYAL IRISH ACADEMY, VOL. 113B, NO. 2, 118 (2013).
above the natural recycling or retention capacity of
these ecosystems can lead to (1) exceeding drinking
water quality standards, as defined by the EU Water
Framework Directive (EU-WFD; European Parliament and Council 2000); (2) increasing primary
production favouring eutrophication in a surface
waterbody (Smith et al. 1999; Watson and Foy
2001; Khan and Ansari 2005; Rivett et al. 2008);
and (3) enhancing greenhouse gas emissions from
unsaturated and saturated zones (Watson and Foy
2001; Reay et al. 2003; Stark and Richards 2008b).
At present in Ireland, land drainage in agriculture areas is regulated through the European
Communities (Environmental Impact Assessment,
EIA) (Agriculture) Regulations 2011 (CEC 2011).
Under this legislation, an EIA has to be undertaken
for works involving more than 15ha of land or
where the farmer feels that drainage may have a
significant effect on the environment (DAFF 2011).
Nevertheless, this legislative framework does not
provide guidelines for the design of subsurface
drainage systems in Ireland. Failure in adapting a
drainage design to local soil, hydrogeologic or
climatic conditions can result in enhanced nutrient
losses from grassland fields (Skaggs et al. 1994;
Gilliam et al. 1999). There is a need to propose
guidelines for the design of drainage systems in
contrasting natural Irish settings for variable soil,
subsoil and aquifer types in different rainfall
Before such guidelines are developed, a sound
understanding of the controlling factors on nutrient
losses in surface and subsurface hydrological pathways is needed. Briefly, spatial and temporal
variations in surface and subsurface nutrient losses
relate to (1) anthropogenic factors, such as design of
drainage systems (Skaggs et al. 1994; Kladivko et al.
2004), timing of fertiliser application (Olness et al.
1980; Hart et al. 2004), excessive fertilisation
(Jordan et al. 2000; Watson and Foy 2001) or
modification of soil properties through the use of
machinery or animal grazing (Watson and Foy
2001); and (2) natural factors, such as variations in
event and antecedent hydrometeorological conditions (Heathwaite and Dils 2000; Hart et al. 2004;
Haygarth et al. 2004; Kurz et al. 2005; Doody et al.
2006), soil types and microbial activity (Daly et al.
2001; Watson et al. 2007; Stark and Richards
2008a; Ghani et al. 2010), plot size or slope, or
depth of the water table. Furthermore, spatial
and temporal patterns of total nutrient losses and
nutrient bioavailability from surface run-off and
subsurface drainage systems can differ strongly
(Gilliam et al. 1999). Overall, these differences
relate to the total amount of flow generated by
these systems for a given rainfall input, and to the
contribution of water from different surface and
subsurface flow paths (Haygarth et al. 2005; Ghani
et al. 2010), which will differ in terms of intensity of
soilwater interactions and/or groundwater inputs.
The objectives of the current study were to
investigate the division of nutrient speciation and
loads between surface and subsurface drainage over
three rainfall events. More specifically, the research
assesses to what extent spatial variations of plot size
and slope within a similar landscape position, soil
characteristics and groundwater patterns impact
flow generation, as well as losses and bioavailability
of nutrients in overland and subsurface drain flow
In order to address these issues, this paper
formulates the following hypotheses:
1. Spatial variations of flow and solutes between
plots are smaller than temporal variations for
each plot between rainfall events;
2. Nutrient load variability reflects overland and
subsurface flow patterns and anthropogenic
3. The occurrence and proportions of different
species and fractions of P and N are controlled
by the contribution of different proportions
of water originating from a rainfall event (event
water) or stored in the subsurface (pre-event
This study was conducted between January and
April 2009 on a 4.2-ha study area, divided into six
ungrazed grassland plots within the same landscape
position, located on a beef farm at the Teagasc,
Johnstown Castle, Environmental Research Centre, Co. Wexford, SE Ireland (52817?36ƒ N,
6831?6ƒW). The soil and subsoil onsite originate
from heterogeneous glacial parent material, which
is underlain by Pre-Cambrian greywacke, schist and
massive schistose quartzites that have been subjected to low-grade metamorphism (Fenton et al.
2009). Four plots (1, 2, 3 and 4) were used in the
study (Fig. 1). Plot areas and slope, and soil texture
and nutrient concentrations are presented in Tables
1 and 2. The design of the site ensures that no
overland flow from adjacent (1.5-m-deep drains) or
up-gradient (3-m-deep drains) sites can enter the
isolated plots. Overland flow was collected in a
surface drain at a low point within each plot and
transported offsite to a v-notch weir setup (Fig. 1).
The site had a subsurface groundwater drainage
system at 1m bgl (tapping into higher permeability
subsoil) made of corrugated pipes (100mm,
inner diameter) fitted with a gravel pack (washed
and 1040mm in size), with drain spacing of
10m (based on samples tested for sand/silt/clay
Fig. 1
(a) Map of the study area, (b) interpreted resistivity profiles.
percentage and equivalent hydraulic conductivity)
and connected to another set of v-notch weirs
(outflow of the drainage network). This allowed for
the monitoring and sampling of subsurface drain
flow. Flow through the v-notch weirs (for both
overland flow and drain flow) was measured using
a calibrated pressure transducer (Sigma, Hach
Company, USA). Three shallow piezometers
(4.5-m depth, screen interval 1m at end of casing)
were drilled to below lowest water strike within
each plot (Fig. 1), each fitted with a mini-diver
(Schlumberger Water Services, Delft, Netherlands)
to record variations of water level at 15-min
Plots received fertiliser inputs of nitrogen (N)
(applied twice a year) and phosphorus (P) and
potassium (K) (applied once a year). For the period
of study, P and K were applied on 21 and 22 March
2009 at a rate of 37kg ha1 P and 74kg ha1 K,
respectively, while N fertiliser application in the
form of urea was applied to all plots at a rate of
118kg ha 1 N on 23 March 2009. The plots were
re-seeded at establishment in 2001 and left ungrazed until the experiment started. All plots were
sown with mid-season yielding variety of Lolium
perenne. Subject to soil conditions, plots were cut
three times a year for silage (last week of May, last
week of July and last week of September/first week
of October). After the study period, a second
application of N, in the form of calcium ammonium nitrate (101.8kgha1 N), was applied after the
first cut. Plots received no other inputs.
Water samples from v-notch weirs were taken on a
flow-weighed basis using a 900 Max Portable autosampler (Sigma, Hach, USA). Filtered (0.45mm
membrane) and non-filtered water samples (20ml)
were analysed using a Thermo Konelab 20 analyser
(Technical Lab Services, Ontario, Canada). Total
dissolved nitrogen (TDN) consists of dissolved
inorganic nitrogen (DIN, sum of nitrate (NO3N), nitrite (NO2N), ammonia (NH3N) and
ammonium (NH4-N)) and dissolved organic nitrogen (DON TDNDIN). Total P consists of
particulate P (PP) and total dissolved P (TDP), with
TDP being the sum of dissolved reactive P (DRP)
and dissolved unreactive P (DUP).
The study area has a cool maritime climate, with
mean annual precipitation of 1002mm, effective
rainfall ranging 400500mm, and mean annual air
temperature of 9.68C (Ryan and Fanning 1996).
Daily weather data were recorded at the Johnstown
Castle Weather Station and were used to estimate
soil moisture deficit (SMD) for moderately drained
soil using the hybrid model (Schulte et al. 2005).
When compared to a 30-year average rainfall value,
the period JanuaryApril 2009 had 3.2mm less total
Table 1
Area (m2)
Slope (%)
Soil texture (010 cm)
Soil texture (030 cm)
(Top/middle/bottom of slope)
Top/middle/bottom of slope
Mean soil nutrient concentrations (mg l1) and standard deviation (mg l1, in
brackets) of TN, P, K and Mg at all plots from 0cm to 30cm depth soil samples.
KCl extraction; bMorgan’s soil nutrient concentration.
Several 2D resistivity profiles (to a depth of 50m)
and electromagnetic surveys (to a depth of 5m)
were used to develop a conceptual model of the
site, to ascertain soil/subsoil material and bedrock
type and quantify depth to bedrock onsite (Fig. 1).
Soil samples were taken from the top, middle and
bottom of each plot, and soil texture was obtained
using particle size distribution techniques using the
sieving and pipette method (BS 1796; BSI 1989)
(Table 1). Plot soil nutrient status (Table 2) was
determined on soil samples (00.3m) at the top,
middle and bottom segments of each plot and were
analysed using Morgan’s extractant (Morgan 1941)
for soil test P, K and magnesium Mg2. Total N
was analysed after KCl extraction on a TN analyser
(TNM-1, Shimadzu Corporation, Kyoto, Japan).
Plot area, slope and soil texture. Clay Loam (CL), Sandy Silt Loam (SSL), Sandy Clay
Loam (SCL), Sandy Loam (SL).
Plot number
Table 2
following a fertiliser application. Event 1 was the
first significant event occurring after a dry period
(peak of 12.9mm of SMD immediately before the
event), while Event 2 occurred during a wet period
(peak of 7.0mm of SMD immediately before the
event). Event 3 occurred in intermediate weather
conditions (SMD ranging from 4.7mm to
10.6mm before the event), at 36 days after fertiliser
application. Absence of rainfall for more than
twelve hours was used to separate one rainfall event
from the other (Kurz et al. 2005). The slopes of
cumulative overland and drain flow were computed
at hourly intervals. According to Vidon and Cuadra
(2010), the start of a flow event can be delineated
when a ‘perceptible rise in discharge’ occurs.
Accordingly, in the present study, the start of an
overland or subsurface drain flow event occurred
when the slope of the cumulative flow exceeded
the maximum slope observed for the twelve hours
preceding the rainfall event. Similarly, the end of
the flow event occurred when the slope of the
cumulative flow reached smaller value than the
maximum observed before the event.
Run-off coefficients in overland and subsurface
drain flow were defined as the ratio of total run-off
and rainfall depth (both in mm) for the event (Joel
et al. 2002; Macrae et al. 2010). Loads of dissolved
and particulate N and P species and fractions for a
time interval were calculated by multiplying the
mean concentration of the species and fractions by
the corresponding flow occurring during the interval (Kurz et al. 2005). Total loads for single flow
events were computed by adding the loads from
each sampling interval occurring during the event.
Fig. 2 Event precipitation characteristics (a) total
precipitation (Bulk P), maximum precipitation (Max P)
and rainfall intensity (R Int), (b) pre-event cumulative
precipitation for seven days (7DP), fourteen days (14DP)
and 30 days (30DP) preceding the event, (c) water table
depth at the start of the event for selected piezometers
(see Fig. 1 for position on the plots).
According to previous soil analysis (unpublished
Johnstown Castle soil and land use summary
report), carbon (C)/N ratios at the sites are between
8.3 and 11.4.
Three events, the first two in winter (Events 1 and
2, starting on 11 January and 24 January 2009,
respectively) and the third in spring (Event 3,
starting on 24 April 2009), were used in this study.
These events were chosen to represent contrasting
pre-event and event rainfall and SMD patterns (Figs
2 and 3) and to discuss incidental losses of nutrients
Total precipitation was the greatest for Event 3 and
the smallest for Event 2 (29.3mm and 12.3mm,
respectively, Fig. 2a), while rainfall intensity was
the greatest for Event 3 and the smallest for Event 1
(1.5mm h 1 and 0.5mm h1, respectively, Fig.
2a). Maximum rainfall intensities were more comparable between events, with a minimum value
observed for Event 2 and a maximum for Event 1
(3.6mm h 1 and 6.8mm h1, respectively). Preevent cumulative rainfall (Fig. 2b) was the lowest
for Event 1 (0.1mm in the pre-event fourteen days,
and 30.4mm in the 30 pre-event days) and the
highest for Event 2 (up to 92.5mm in the 30 preevent days), while Event 3 had intermediate values.
This resulted in generally (1) shallower groundwater depths before Event 2 (Fig. 2c) and larger
depths before Event 1 and (2) a sharp decrease from
positive to negative SMD at the start of Events 1
Fig. 3 (a) Precipitation and (b) soil moisture deficit (SMD) computed from the model by Schulte et al. (2005). Vertical
dashed lines indicate start of the three rainfall events and vertical plain lines dates of fertilisation and grass cut events.
and 3, and fluctuating negative SMD between
Events 1 and 2 (Fig. 3).
Flow variations across plots
Overland total flow values (Fig. 4a) and run-off
coefficients (Fig. 4c) for the three events increased
from Plot 2 to Plot 4 (Plot 2 B Plot 1 B Plot 3 B
Plot 4, up to 2.5 times more flow for Plot 4 than for
Plot 2). Subsurface drain total flow patterns (Fig.
4b) were less consistent (e.g. flow in Plot 4 was
higher than in Plots 1 and 2 for Events 2 and 3, but
smaller than for Plot 1 for Event 1). Nevertheless,
run-off coefficients for subsurface drain flow (Fig.
4d) were generally ordered in a similar way than
total flow values.
For all three events, there was between 2.1 and
6.9 more total flow measured in overland flow than
in the subsurface drains. For Event 1 and 2, Plot 1
had the smallest ratios of overland and subsurface
drain flow (down to 2.1), while Plot 4 had the
biggest (up to 4.9); in contrast, Plot 1 had a greater
ratio than Plot 4 for Event 3 (6.9 and 6.3,
Flow variations across events
In general, total overland flow (Fig. 4a) was slightly
smaller for Event 2 than for Event 1 and increased
greatly for Event 3 (up to 2.8 times more flow for
Plot 1 for Event 3 than for Event 1). Run-off
coefficients in overland flow (Fig. 4c) had different
patterns. They were minimal for Event 1 and
maximal for Event 2, except for Plot 1, where a
small increase was observed between Events 2 and
3; differences in run-off coefficients between Plots
1 and 2, and Plots 3 and 4 were also more variable,
with maximum differences observed for Event 2
(ratio 2.5 times higher for Plot 4 than for Plot 2).
As in overland flow (Fig. 4a), subsurface drain
total flows (Fig. 4b) decreased from Event 1 to
Event 2 for Plots 1 and 2 (up to 2.1 times less for
Plot 2). For these two plots, even if the flows
increased for Event 3, they remained lower than for
Event 1. A reverse pattern was observed for Plot 4:
an increase was observed between Events 1 and 2
(1.5 times more flow), and a subsequent decrease
between Events 2 and 3 (1.4 times less flow). Runoff coefficients in subsurface drain flow (Fig. 4d)
had similar patterns than total flow for Plot 4 (Fig.
4b), but they were reversed for Plots 1 and 2.
For Plots 1 and 2, ratios of overland and
subsurface drain total flow increased from Event 1
to Event 3 (up to 3.3 times greater for Plot 1). In
contrast, for Plot 4, they decreased from Event 1 to
Event 2 (1.6 times less), and increased from Event 2
to Event 3 (2.1 times more).
The concentrations of Particulate P, TDP, NH4-N
and NO3-N for selected piezometers sampled on 5
March 2009 are presented in Table 3. PP concen-
Fig. 4 Overland and subsurface drain flow patterns per event and plot. (a); (b) Total subsurface drain flow; (c) Run-off
coefficient for overland flow (ratio of total overland flow and total precipitation per event); (d) Run-off coefficient for
drain flow (ratio of total subsurface drain flow and total precipitation per event).
trations were all below detection limits, while TDP
concentrations were similar at Plots 2, 3 and 4
(overall range of 0.0080.020mg l 1) and below
detection limits at Plot 1. There were no spatial
concentration trends within the plots. Ammonium
concentrations were similar across plots (overall
range of 0.0540.071mg l1). Average NO3-N
Table 3
Groundwater nutrient concentrations (mg L 1) of PP, TDP, NH4N and NO3-N for selected piezometers sampled on 5 March 2009.
Note: bdl refers to concentrations below detection limits.
concentrations were lower and displayed more
variations in Plots 1 and 2 than in Plots 3 and 4
(average of 4.7mg l1 and 8.7mg l1, respectively).
Total P and TDN variations
Flow-weighted mean concentrations of TP and
TDN for all plots and events are presented in Table
4, and the corresponding total loads (in g ha 1) in
Fig. 5af. For the events before fertilisation (Events
1 and 2), flow-weighted mean concentrations of TP
and TDN in overland flow increased from Plot 1 to
Plot 3 and 4 (up to 1.6 times more TP and TDN).
Plot 2 had the highest concentrations for Event 1,
and intermediary concentrations between those of
Plot 1 and 3 for Event 2. Similarly, total loads of TP
and TDN in overland flow increased from Plot 1 to
Plot 4, but to a greater extent than flow-weighted
mean concentrations (up to 3.3 times more TP and
2.9 times more TDN for Plot 4 than for Plot 1, Fig.
5ad). For the event after fertilisation (Event 3),
Plot 2 had the highest flow-weighted mean
concentrations of TP and TDN. Otherwise, there
were no clear spatial trends in flow-weighted mean
concentrations across plots for this event. Both TP
and TDN loads were slightly smaller for Plot 2 than
for Plot 1 (Fig. 5ef), but still greater for Plots 3 and
Note: bdl refers to concentrations below detection limits and n.a. to samples not analyzed.
Flow-weighted mean nutrient concentrations (mg l-1) for all plots (1-, 2-, 3- and 4-) in overland flow (OF) and subsurface drain flow (DF)
for the three events (Event 1/Event 2/Event 3).
Table 4
Fig. 5 Total loads of P per plot in overland flow (OF) and drain flow (DF) for Event 1 (a), Event 2 (c) and Event 3 (e) and
the relative contribution of particulate phosphorus (PP), dissolved unreactive phosphorus (DUP) and dissolved reactive
phosphorus (DRP). Total loads of N per plot in overland flow (OF) and drain flow (DF) for Event 1 (b), Event 2 (d) and
Event 3 (f) and the relative contribution of dissolved organic nitrogen (DON) and dissolved inorganic nitrogen (DIN).
4 (1.5 more TP and 1.4 more TDN for Plot 4 than
for Plot 2).
In overland flow, Event 3 had the highest
flow-weighted mean concentrations of TP and the
highest loads of TP and TDN (up to 183.2g ha1
and 144.4g ha 1, respectively, Fig. 5ef). Similarly,
Event 2 had the lowest flow-weighted mean
concentrations of TP and the lowest loads of TP
and TDN (down to 2.0g ha 1 and 31.2g ha 1,
respectively, Fig. 5cd). Increases in total loads of
TP in overland flow for Event 3 (16.130.4 times
more loads for Event 3 than for Event 1) were
much higher than for TDN (1.33.1 times more
loads for Event 3 than for Event 1).
In subsurface drains, flow-weighted mean
concentrations of TP and TDN were more variable
between plots than in overland flow. Total dissolved
N loads increased from Plot 2 to Plot 4 for Event 1
(Fig. 5b), and from Plot 1 to Plot 4 for Event 2
(Fig. 5d). Total P loads behaved similarly for Event
2 between Plots 1 and 4 (Fig. 5c), but they
decreased from Plot 1 to Plot 3 for Event 1 (Fig. 5a).
In contrast to overland flow patterns, ranges of
flow-weighted mean concentrations and total loads
of TP and TDN in subsurface drains between
events were very comparable (total loads of 0.5
4.7g ha 1 and 6.261.9g ha1 for TP and TDN,
respectively, across all plots and events). For the
same plots, flow-weighted mean concentrations of
TP and TDN were generally smaller for Event 2,
while they were more similar for Events 1 and 3.
There were few variations in loads of TP and TDN
between events at the same plots, except for Plot 1,
where they were maximum for Event 2 (6.4 and
9.7 times more P and N at Event 2 than Event 1,
respectively) and minimum for Event 1.
P and N speciation and fractionation patterns
For the events before fertilisation, DRP was the
most abundant P fraction in overland flow for Plots
1 and 2 for Event 1 (49.9 and 53.1% of TP loads,
respectively, Fig. 5a) and for Plot 2 for Event 2
(39.2% of the TP loads, Fig. 5c), and in much
greater proportions in all plots for Event 3 (from
78.8% to 83.3% of TP loads, Fig. 5e). In contrast,
Plots 3 and 4 had DUP as the dominant P fraction
in overland flow for Events 1 and 2 (up to 41.8%
and 55.9% of TP loads for Events 1 and 2,
respectively, Fig. 5a and c). In contrast, PP was
the most abundant fraction in subsurface drain flow
for Plots 1 and 2 (up to 80.6% of TP loads) for
Events 1 and 2. This was also the case for Plot 4 in
Event 1 (Fig. 5a); otherwise Plots 3 and 4 had DUP
as the dominant P fraction in subsurface drains (up
to 89.2% of total P).
Dissolved organic N was the most abundant
fraction of dissolved N in both overland and
subsurface drain flow (up to 99.6% of TDN for
Plot 1 in Event 2, Fig. 5d), except for Plot 6 in
Event 2. The relative abundance of DIN was
nevertheless generally greater in subsurface drain
flow. For Events 1 and 2, this trend was more
marked for Plots 3 and 4 (overall range of 25.8
58.2% of TDN as DIN in subsurface drain flow,
and only 1.33.5% in overland flow, Fig. 5b and d)
than for Plots 1 and 2 (overall range of 6.626.2%
of TDN as DIN in subsurface drain flow, and 0.4
3.3% in overland flow). For Event 3, subsurface
drain flow at Plots 1 and 4 had a relative abundance
of DIN of 38.5% and 32.5% of TDN as DIN,
respectively (Fig. 5f).
The relative proportions of NH4 and NO3 in
DIN are presented in Fig. 6ac. In overland flow,
NH4 was the only N species detected in samples
for Event 1 for all plots, for Event 2 for Plots 2 and
3, and for Event 3 for Plot 2. Nitrate was also the
less abundant fraction of DIN in overland flow for
Plots 1 and 3 in Event 3, while it was more
abundant than NH4 for only two occasions (Plot 1
in Event 2 and Plot 4 in Event 3). In contrast, NO3
appeared to be the dominant fraction in all samples
of subsurface drain flow, except for Plot 2 in Event
1 and Plot 3 in Event 3 (43.3% and 31.7% of total
DIN as NO3 ; Fig. 6a and c). In general, the relative
abundance of NO3 was greater for Plots 3 and 4
than for Plots 1 and 2.
Fig. 6 Total loads of DIN expressed as N per plot in
overland flow (OF) and subsurface drain flow (DF) for
Event 1 (a), Event 2 (b) and Event 3 (c) and the relative
contribution of ammonium (NH4 ) and nitrate (NO3 ):
The results herein investigate water and nutrient
patterns in overland flow and subsurface drainage
systems in marginal land for a relatively limited
number of plots and rainfall events. The subsurface
drainage system installed on the current site has an
internal in-field groundwater drainage system combined with deep drains to control the water table
height. An external main drainage system then
transports water off-site to a monitored wellmaintained outflow. Caution should be exercised
in interpreting the results here when considering
the vast differences notable among likely marginal
grassland sites (e.g. slope, soil type and permeability,
water table depth, drainage design*deep versus
shallow, mole versus gravel mole, gravel only or
perforated pipes, collector pipe and outlet differ-
ences), agronomic management (e.g. grass off takes,
grazing, different rates and types of fertiliser applied)
or seasonal or short-term hydrometeorological
patterns. A soil test pit should always be dug in
representative areas of a proposed drainage site, left
to settle and then investigated. Knowledge gained
within the soil test pit will point to specific drainage
characteristics (e.g. type and thickness of topsoil,
type and thickness of subsoil, water table position as
indicated by influx of water in permeable layers,
colouration of soil, texture using hand techniques
and structure).
This section evaluates the hypothesis that spatial
variations of flow patterns between plots for the
same event are smaller than temporal variations for
each plot between events.
Overland Flow
Total flow and run-off coefficients values followed
a consistent ordering in overland flow across plots
for all events (Plot 2 B Plot 1 B Plot 3 B Plot 4,
Fig. 4a and c). This pattern links to spatial
differences in physical controls on run-off generation. In particular, the overall increase in run-off
coefficients from Plot 2 to Plot 4 (up to 2.5 times
for Event 2) can be in part related to a decrease in
surface area of up to 47% from Plots 1 and 2 to Plots
3 and 4 (Table 1). This scale dependency of run-off
coefficients has been observed in numerous studies,
as reviewed by Wainwright and Parsons (2002),
Cerdan et al. (2004) or Norbiato et al. (2009). Joel
et al. (2002) found that over eight rainfall events and
experimental plots with a surface area of 50m2 had
surface run-off coefficients of 40% less than plots
with a surface area of 0.25m2. When looking at a
wider range of scales over a five-year period in
predominantly arable land in Normandy (France),
Cerdan et al. (2004) found that 450m2 plots had
mean run-off coefficients 10 and 30 times greater
than larger catchments of 90ha and 1100ha,
respectively. In the present study, differences in
size*and slope length*of the different plots were
smaller than in the above studies. This suggests that
the effect of plot size can only explain a part of the
increase in run-off coefficients from Plots 1 and 2 to
Plots 3 and 4.
Run-off coefficients also tend to increase with
increasing slope (Scherrer and Naef 2003; Alaoui et
al. 2011). Even if Plots 3 and 4 were of similar size
(4080 m2 and 4070m2, respectively, Table 1), the
slightly greater slope in Plot 4 than in Plot 3 (5.4%
and 4.2%, respectively) may be responsible for the
increase in overland flow run-off coefficient. Runoff coefficients also tend to increase with decreasing
soil permeability. The influence of permeability was
shown at the catchment scale in northern Italy by
Norbiato et al. (2009) and in a study of preferential
flow in forest and grassland sites in Switzerland by
Alaoui et al. (2011). In the present study, soil
texture based on soil sampling to depths of 0.1m
and 0.3m was very similar between plots (Table 1),
but geophysical surveys, which include subsoils,
showed some differences (Fig. 1). Plots 3 and 4 had
sandy, gravely clay and less silt clay horizons than
Plots 1 and 2. These patterns may have influenced
the difference in run-off coefficients between these
two groups of plots, but they were probably not
sufficient to counterbalance the effect of other
parameters, such as plot size. Nevertheless, when
comparing Plots 1 and 2, the greater proportion of
silt-clay horizons in Plot 2 may explain the higher
overland run-off coefficients observed in Plot 2
than in Plot 1.
In addition to these differences in plot size and
sediment characteristics, a shallower water table in
Plots 3 and 4 than in Plots 1 and 2 (Fig. 2c) also
possibly implies that a greater amount of rainfall was
required in these latter plots to reach saturation of
the soils, further enhancing the effect of plot size on
run-off generation. As pointed out by Doody et al.
(2010), infiltration excess overland flow can dominate over saturation excess overland flow in poorly
drained soils in Irish grasslands, in particular in areas
of high soil water repellence. In the present study,
the respective importance of both processes was
difficult to assess, as no field measurements were
available to compare the volumetric soil moisture to
the soil field capacity. As all plots had a very similar
soil texture, it is therefore likely that they had very
similar infiltration capacity. Nevertheless, saturation
excess overland flow would probably occur more
often where the water table is shallower, i.e. in
Plots 3 and 4 (water table depth often shallower
than 0.5m for the period of study), as well as
towards the bottom of the slopes.
Overland flow run-off coefficients (Fig. 4c)
were at a maximum for Event 2 for all plots except
Plot 1, and were at a minimum for Event 1. Event
and pre-event*or antecedent*hydrologic conditions need to be accounted for in the discussion of
these patterns. An increase in total rainfall or rainfall
intensity, as well as wetter antecedent conditions,
have been shown to increase surface run-off
coefficients (Norbiato et al. 2009; Macrae et al.
2010; Vidon and Cuadra 2010, 2011). Accordingly,
an increase in rainfall intensity and total rainfall
between Events 1 and 3, as well as wetter pre-event
conditions, as indicated by higher pre-event cumulative precipitation and a shallower water table
in the majority of wells, can explain the increase in
run-off coefficients between Events 1 and 3. In
contrast, the high increase in run-off coefficients
from Event 1 to Event 2 is not related to an increase
in event precipitation, but rather to much wetter
antecedent conditions for Event 2 than for other
Subsurface drain flow
Subsurface drains generated less flow than surface
flow systems (Fig. 4b). They also lacked a consistent
ordering of total flow and run-off coefficients
observed across plots in overland flow. There
were nevertheless clear differences in flow behaviour between plots for each event. Vidon and
Cuadra (2010) also observed large variations
(often 50%) of flow generation between two
nearby tile drains of the same design installed within
a similar soil type. In the present study, the design
of the drainage system was identical for all plots.
Therefore, differences in drain flow patterns could
not be related to factors related to drainage design
criterion (Kladivko et al. 2004), but rather to the
inherent soil and subsoil heterogeneity of the plots,
which impact the hydrological connectivity between the surface and the subsurface drains.
Instead, variations in drain flow patterns across
plots for different events highlight some similarities
with overland flow behaviour. For Event 2, wetter
pre-event hydrological conditions, in particular,
appeared to result in the greatest run-off coefficients
(Fig. 4d), with the greatest increase for Plot 4 and
the lowest for Plot 2. This pattern was probably
related to spatial variations in water table depth
across plots, with groundwater inputs to the
subsurface drains being more important in wetter
periods in areas of shallower water table (Plot 4)
than in areas of deeper water table (Plots 1 and 2).
Similarly, the small increase in subsurface run-off
coefficient between Events 1 and 3 for Plot 4 may
be related to increased inputs in both pre-event and
event water, as indicated by both wetter pre-event
conditions and higher precipitation for the event
(total precipitation and rainfall intensity, Fig. 2a). In
contrast to what the hypothesis suggested, spatial
differences in overland and subsurface drain flow
patterns can be greater between plots than between
events for the same plots. Overland flow patterns
were nevertheless clearly different between Plots 1
and 2, and Plots 3 and 4; indeed, if these two pairs
of plots are considered separately, their flow
patterns confirm our hypothesis.
This section evaluates the hypothesis that TDN
and TP load variability is inherited from overland
and subsurface flow patterns and anthropogenic
Overland flow
In overland flow, variations of loads of TP and
TDN across plots appeared to follow the same
ordering than that of total flow and run-off
coefficients for Event 3 (Plot 2 B Plot 1 B Plot
3 B Plot 4, Figs. 4a and 5e and f), while for the
other events, values were smaller for Plot 1 than for
Plot 2. Furthermore, increases in loads of TP and
TDN between plots were similar to the increase in
total flow generation. For example, in Event 2, 2.1
times more flow was generated for Plot 3 than for
Plot 1, resulting in a 3.3 and 2.3 times increase in
loads of TP and TDN, respectively. For the same
plots during Event 3, 1.2 times more flow resulted
in a similar increase in loads of TP and TDN. Kurz
et al. (2005) showed in a similar setting that P losses
would increase in overland flow with increasing soil
test P concentration in soils. This confirmed the
findings of other studies (Heckrath et al. 1995;
Sharpley 1995; Smith et al. 1995; Hesketh and
Brookes 2000; Hart et al. 2004; Watson et al. 2007).
Similarly, high N losses in surface run-off often
occur as incidental losses under standard or excessive fertiliser applications (Cuttle and Scholefield
1995; Scholefield and Stone 1995). The present
study considered soils with very similar Morgan’s P
concentrations (arithmetic mean of 2.83.9mg
l1, low P-index, Table 2) compared to a range
of 417mg l1 in Kurz et al. (2005), as well as
identical fertiliser applications across plots. The lack
of strong variability in P and N availability in soils,
or through fertiliser application across plots, explains the general absence of large differences in TP
and TDN flow-weighted mean concentrations in
overland flow. The increase in flow-weighted mean
TP concentrations from Plot 1 to Plot 4, possibly
related to the contribution of water with higher TP
concentrations at Plots 3 and 4, contributes to the
overall increase in TP loads across plots. Nevertheless, the absence of such patterns for TDN, and
the good correlations between flow and total load
variations suggest that spatial variations in nutrient
losses in overland flow are primarily controlled by
differences in flow generation across plots.
Variations in TP and TDN loads between
Event 1 and 2 in Plot 3 were proportional to those
of flow generation, i.e. 1.2 times more flow for this
plot between these two events resulted in 1.4
greater P but similar N losses (Figs. 4a and 6ad).
Nevertheless, the higher TP and TDN flowweighted mean concentrations for Event 1 than
for Event 2 for Plot 2 (Table 4) resulted in 2.5 times
more TP loads for Event 1 than for Event 2, and up
to 1.7 times more TDN loads, for similar volumes
of water (Figs. 4a and 5ad). The strong increase in
TP losses for Event 3 relates to the application of
fertiliser on 20 and 21 March 2009 (i.e. 36 days
before the start of the event). This pattern relates to
a change from small critical P losses in a low
P-index context to high incidental losses resulting
from the occurrence of rainfall events after the
spreading of fertilisers (Haygarth et al. 1999).
Increases in TP of 16.130.4 times greater than for
Event 1 are within the range shown by other
studies (see Hart et al. 2004 for a review). For
example, TP losses for native grassland watersheds
in Oklahoma (USA) increased 1025 times after
application rates of 75kg P ha 1 of ammonium
phosphate fertiliser (Olness et al. 1980; Hart et al.
2004). In contrast to this, Kurz et al. (2005)
reported no obvious increase in DRP levels in
overland flow 44 days after the application of P
fertiliser in mid-March; they attributed this result to
a ‘time lag’ effect, as rainfall only occurred 44 days
after the fertiliser application. Ideally, advice on the
timing of fertiliser spreading should account for
variations in rainfall patterns occurring over similar
periods; nevertheless, present weather forecast
capabilities do not allow to do so. In the present
study, N fertilisers were applied two to three days
after P fertiliser. The small increase in TDN losses
in overland flow at Event 3 reflects an increase in
flow generation for this event (up to 2.8 times
greater flow, for up to 3.1 times greater TDN
losses). This pattern suggests that the time lag
between fertiliser application and Event 3 was
enough to mobilise excess N, either by biological
processing or through losses along surface and
subsurface flow paths.
Subsurface drain flow
As in overland flow, differences in loads of TP and
TDN between plots in subsurface drain flow often
followed the flow generation sequence for the same
event, whereas differences between events were
more variable (Figs. 4b and 5). Furthermore, Event
3 was not characterised by a large increase in TP
loads as in overland flow (Fig. 5e and f). Indeed, for
this event, loads of TP and TDN in subsurface drain
flow were similar to those observed for Event 1.
This pattern suggests that soilwater interactions, as
well as losses of nutrients in overland flow, were
sufficient to significantly buffer the effect of P
fertilisation on incidental losses, or that transit times
of P towards the subsurface drains are longer than
the period between the application of fertilisers and
Event 3.
Overland flow versus subsurface drain flow
Loads of TP and TDN in subsurface drain flow
were, in general, significantly smaller than those in
overland flow (2.3123.1 times higher TP loads,
and 2.65.0 times higher TDN loads in overland
flow), except for Plot 1-Event 1 (1.1 and 1.6 times
less TP and TDN loads, respectively, in overland
flow than in subsurface drain flow, Fig. 5).
Haygarth et al. (1998) related higher mean concentrations of TP in the shallowest horizons of the
soil to a greater soil test P. Indeed, P is often
considered to be retained in the shallow subsurface.
In the present study, the smaller loads of TP and
TDN in the subsurface drainage system could be
attributed to a combination of such processes, and
to the fact that smaller amounts of water were
generated by the subsurface drainage system. For
example, in Event 1, ratios of loads of TP between
overland and subsurface drainage flow were larger
than ratios of overland versus subsurface drainage
flow for all Plots except Plot 1 (up to 17.5 times less
P in subsurface drainage flow for 6.5 times less flow
for Plot 3), while there was an overall decrease in
TP flow-weighted mean concentrations between
overland and subsurface drainage flow. This suggests that the reduction in TP loads in the subsurface drainage system comparatively to the surface
system is potentially a result of (1) P retention in the
shallow soil, (2) dilution with water from subsurface
flow paths less concentrated in TP and (3) smaller
amount of flow in the subsurface drains. In contrast,
for the same event, ratios of loads of TDN between
overland and subsurface drainage flow were slightly
smaller than ratios of overland and subsurface
drainage flow, except for Plot 2, while TDN
flow-weighted mean concentrations where often
higher in the subsurface drainage system. This
specific pattern suggests losses of N from the
subsurface flow paths to the subsurface drains.
This section tests the hypothesis that the occurrence
and proportions of different species and fractions of
P and N are controlled by the contribution of
different proportions of water originating from a
rainfall event (event water) or stored in the subsurface (pre-event water).
P fractions
The predominance of dissolved forms of P in
overland flow possibly reflects particle retention
by the vegetation and limited erosion in the absence
of livestock (Haygarth and Jarvis 1997; Heathwaite
and Dils 2000; Hart et al. 2004). McDowell and
Sharpley (2002) observed through rainfall experiments that PP increased with increasing distance
along the slope in un-manured grass plots. In the
present study, differences in plot size*and slope
length*did not seem to impact on the relative
proportion of PP in overland flow. The predominance of DRP in overland flow for Plots 2 and 1Event 1 and for Plot 2-Event 2 (Fig. 5a and c)
reflects the result of previous studies (Haygarth and
Jarvis 1997; Heathwaite and Dils 2000; Hart et al.
2004). The higher contribution of pre-event water
for Plots 3 and 4 is probably responsible for the fact
that DUP was the major fraction of P released at
these locations for the first two events. Indeed,
processing of P by plants and soil biota, as well as
higher adsorption of DRP in soils, cause increases
in organic forms of P in pre-event water (Haygarth
et al. 1998; Reynolds and Davies 2001; Gburek
et al. 2005). DRP was nevertheless the most
abundant P fraction in overland flow for all plots
for Event 3 (Fig. 5e). This pattern probably relates
to the application of mineral P fertilisers 36 days
before the event (Hart et al. 2004), which effectively overrides differences in the respective contribution of pre-event and event water across plots
or events. As in overland flow, the predominance of
DUP in subsurface drainage flow at Plots 3 and 4 is
probably linked to the predominance of pre-event
water. In contrast, in Plots 1 and 2, where the water
table is deeper, the predominance of PP can be
indicative of the development of preferential flow
along macropores, in areas of finer soil texture than
those found in Plots 3 and 4 (Heathwaite and Dils
2000; Kramers et al. 2009, 2012).
Nitrogen species
As in few previous studies, DON was generally the
predominant form of N in overland and subsurface
drain flow for all events. Streeter et al. (2003) also
found that DON amounted to over 90% of TN in
soil water and surface water (lake water, as well as
lake inflow and outflow) in upland semi-managed
grassland in Cambria (UK). Similarly, Willett et al.
(2004) found that DON represented from 40% to
over 85% of the total N pool in streams and lakes in
Wales (UK), in areas predominantly covered by
grazed grasslands and forests. A similar predominance of DON over inorganic forms of N was
observed in soil water under pasture (Ghani et al.
2010) or un-grazed grassland (Dijkstra et al. 2007;
van Kessel et al. 2009). In the present study, this
pattern probably relates to the use of Urea as N
fertiliser in Spring, to the uptake of DIN inputs
through fertilisation by grass species as well as to
high rates of organic matter decomposition in the
soil (Stark and Richards 2008a; van Kessel et al.
2009). Several studies and reviews show the need to
better assess the importance of DON losses to
groundwater and surface water systems (Seitzinger
and Sanders 1997; Willett et al. 2004; Pellerin et al.
2006; van Kessel et al. 2009). These works especially
highlight that the bioavailability of DON in aquatic
ecosystems*and its contribution to eutrophication*and the overall function of DON in
the N cycle should be more accounted for.
The shift from NH4 dominated water in
overland flow to NO3 dominated water in subsurface drain flow (Fig. 6), and the greater loads of DIN
in the subsurface drain flow further indicate the
impact of soil microbial activity (i.e. nitrification;
Stark and Richards 2008a) on the chemical transformation of N in the subsurface. Here again, a
shallower water table for Plots 3 and 4 probably
relates to higher inputs of NO3 in the subsurface
drainage system than for Plots 1 and 2. Higher
concentrations of NO3-N than NH4-N in ground14
water, as well as higher NO3-N concentrations at
Plots 3 and 4 than at Plots 1 and
2, confirm this
process. In contrast, higher NH4 concentrations in
Plots 1 and 2 possibly relate to quick transfer of NH4
in macropores (Kramers et al. 2009); the absence of
an increase in P in the subsurface drains for Event 3
nevertheless suggest that this pathway is of small
importance. Alternatively, limited nitrification in
areas of higher than optimal soil water content
(Grundmann et al. 1995) could explain this pattern.
This study highlights the necessity to adopt a
common holistic and interdisciplinary framework,
which seeks to identify the controlling factors for
water and solute losses in both surface and subsurface environments in Irish marginal lands. Due to
the mixed nature of nutrient losses (i.e. both P and
N losses) in surface and subsurface drainage, any
end-of-pipe solution to ameliorate discharges must
consider both nutrient types. In addition, buffer
strip areas positioned at the bottom of slopes can
decrease such losses, providing the subsurface
drainage system does not extend into these areas
and the outflow still exists further down-gradient.
Plot size
In this study, the size of the plots*and the
correlated slope length*appears to relate to the
volume of water generated by unit of land area (i.e.
in mm) and total loads of P and N (in g ha 1) in
overland flow. As pointed out above, it was difficult
to quantify the importance of this control with
respect to others such as water table depth. It is
nevertheless likely that in this kind of setting,
significantly increasing field size will result in a
decrease of nutrient losses in overland flow. In
contrast, the decrease in flow volume and nutrient
loads with increasing field size were not compensated by correlated increases in subsurface drain
flow. This suggests that other pathways such as
evapotranspiration, losses to groundwater, or retention in the soil, are enough to compensate for the
difference. In Ireland, the mean size of permanent
pastures not classified as commonage is 5.5ha
(standard deviation of 12.2ha). A median size of
grassland fields of 3ha was determined by excluding
extreme outliers (CEC 2001). In areas where the
natural attenuation capacity of nutrients in subsurface flow paths is enough to accommodate increasing nutrient loads, increasing field size could be
considered as a measure to limit nutrient losses to a
connected waterbody.
Water table depth
Generally, fields with similar soil characteristics will
generate more overland flow where the water table
is shallow when compared with areas where more
rainfall is needed to reach full saturation (Doody
et al. 2010). In the present study, this mechanism, in
conjunction with the increase in plot size, was
probably partially responsible for the increase in the
volume of water and in the total loads of P and N
generated in overland flow from Plots 1 and 2
(deeper water table) to Plots 3 and 4 (shallower
water table). Subsurface drain flow also increased
more at Plots 3 and 4, further enhancing nutrient
losses. In addition, for events preceding the application of fertiliser, a shallower water table depth
across plots related to: (1) an increase in the
proportions of DUP over DRP in overland flow,
and those of DUP over PP in subsurface drain flow;
(2) an increase in the proportions of DIN relatively
to DON in subsurface drainflow; and (3) a decrease
in the proportions of NH4 relatively to NO3 in
subsurface drain flow. Dissolved inorganic forms of
P and N (i.e. DRP and DIN) are said to be more
bioavailable than organic (i.e. DON and the
majority of DUP) or particulate fractions (i.e. PP)
(Seitzinger and Sanders 1997; Reynolds and Davies
2001; Willett et al. 2004). Similarly, NH3 is highly
toxic to aquatic ecosystems (Camargo and Alonso
2006), whereas
in the current water legislation in
Ireland, NO3 is mostly considered to be a limiting
nutrient in coastal waters and a contaminant in
drinking water. Implementing subsurface drainage
may enhance crop growth and nutrient uptake and
thereby decrease nutrient loads. Nevertheless, in
many circumstances, artificially lowering the water
table could result in decreasing total loads of N and
P lost from surface pathways, but increasing the
nutrient bioavailability in quick flow (e.g. increasing the proportions of inorganic forms of N)
through the subsurface drainage system. In order
to address this issue, technologies such as permeable
reactive barriers or constructed wetlands (Brix et al.
2001), which aim at remediating mixed contaminant sources could be implemented.
Similar studies should be undertaken to evaluate the impact on nutrient losses of installing mole
or gravel mole drains to enhance the infiltration
capacity of soils (Galvin 1983). In the 1970s and
1980s, the priority was to drain land without
an environmental framework. As drainage implementation is now being re-visited to provide
environmentally sustainable solutions for Irish farming, these patterns of nutrient losses and bioavailability need to be accounted for.
This study investigated the controls on flow
generation and P and N losses and fractionation/
speciation in surface and subsurface drainage for
three rainfall events in four un-grazed grassland
plots in Ireland. Spatial differences in run-off
coefficients and in the total amount of water by
unit area (in mm) generated by the overland flow
systems mainly linked to (1) the size of the plots (an
increase in size linked with a decrease in flow) and
(2) water table depth (shallower water table linked
with an increase in flow). Temporally, both event
and pre-event hydrometeorological conditions
were the main controls. In contrast, controls on
spatial differences in flow generation in the subsurface drainage systems were more difficult to assess.
Overall, these controls imposed greater spatial
differences in overland and subsurface drainage
patterns between all plots than temporal variations
between events for the same plot. In turn, an
increase in overland and subsurface drain flow
induced higher TP and TDN total losses. Subsurface drain flow generated smaller loads of TDN and
TP than overland flow. Before the application of
fertiliser, the proportions of different P fractions and
N species reflected the influence of pre-event water
to overland and subsurface drain flow. Even if
DON was generally the dominant form in both
systems, the proportion of DIN was higher in the
subsurface drains, especially in areas of shallower
water table. Nitrate also dominated over NH4 in
the subsurface drain flow, but not in overland flow.
Similarly, DUP was the dominant P fraction in
subsurface drain flow where the water table was
shallow, while PP was the most important fraction
elsewhere. In overland flow, a shallower water table
implied a switch from DRP- to DUP-dominated
water. The application of fertiliser resulted in a
strong increase in TP concentrations in overland
flow, and a dominance of DRP in all plots. Both P
and N total losses and speciation/fractionation will
affect the nutrient bioavailability in aquatic ecosystems. This study highlights the importance of an
integrated assessment of the controls of flow and
solute patterns in both surface and subsurface flow
systems when aiming at identifying the impact of
grassland management on nutrient losses in water.
Further research is needed to test whether the
implementation of design criteria specific to local
soil and groundwater conditions can further reduce
P and N losses from grasslands.
This research was financially supported under the
National Development Plan, through the Research
Stimulus Fund, administered by the Department of
Agriculture, Food and Marine (RSF 07 525). We
also wish to thank Atul Haria, Sean Kenny, Alan
Cuddihy, John Murphy, Rioch Fox, Denis
Brennan, Maria Radford, Teresa Cowman,
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