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A semi-quantitative risk model for
dairy farms to pinpoint and break
source-pathway connections
between nutrient sources and
open drainage channel sections
D. G. Opoku
1
,
2
, M. G. Healy
2
, O. Fenton
3
, K. Daly
3
, T. Condon
1
and
P. Tuohy
1
*
1
Animal and Grassland Research and Innovation Centre, Teagasc Moorepark, Fermoy, Ireland,
2
Civil
Engineering and Ryan Institute, College of Science and Engineering, University of Galway, Galway,
Ireland,
3
Environmental Research Centre, Teagasc Johnstown Castle, Wexford, Ireland
Introduction: On intensive grassland dairy farms in high rainfall areas with poorly
drained soils, networks of open drainage channels linked to in-field drainage
systems are needed to enable farm operations. Nitrogen and phosphorus point
and diffuse sources may be connected to this open drainage channel network
along surface and subsurface pathways, with negative impacts upon delivery to
the downstream aquatic system.
Methods: This study developed a semi-quantitative risk assessment model by: (1)
selecting parameters (categorical or continuous) representing the nutrient
transfer continuum and (2) scoring (relative magnitude and impact) the risk of
nutrient source connectivity and delivery for every open drainage channel section
across seven dairy farms.
Results and Discussion: A Risk Index Classification System consisting of low,
medium, high, or very high-risk class was developed, with high or above requiring
a mitigation plan. Results showed that 23%, 68%, 9% and 0% of all open drainage
channels on study farms were identified as low, moderate, high and very high-
risk, respectively. A range from 2% to 25% per farm of the open drainage channels
was classified as high-risk that potentially needed mitigation, although none was
identified as very high-risk. Two-thirds of the high-risk open drainage channels
were connected to the farmyards, with potential for high nutrient loss from point
sources. A combined approach of source management and targeted breaking of
the pathway (e.g., in-channel filters, water diversion bars) may help minimise
nutrient losses from high risk open drainage channels on poorly draining soils.
KEYWORDS
water quality, agriculture, nitrogen, phosphorus, environment, mitigation
1 Introduction
Agricultural landscapes in areas of high annual precipitation and heavy textured soils
are characterised by high densities of open drainage channels, which provide outfalls for in-
field drainage systems (Shore et al., 2015;Tuohy et al., 2018). Open drainage channels,
comprising drainage ditches and smaller streams, are networked to collect and drain away
OPEN ACCESS
EDITED BY
PawełTomczyk,
Wroclaw University of Environmental and Life
Sciences, Poland
REVIEWED BY
Laura Christianson,
University of Illinois at Urbana-Champaign,
United States
Pankaj Tiwari,
University of Kalyani, India
*CORRESPONDENCE
P. Tuohy,
patrick.tuohy@teagasc.ie
RECEIVED 20 May 2024
ACCEPTED 09 September 2024
PUBLISHED 23 September 2024
CITATION
Opoku DG, Healy MG, Fenton O, Daly K,
Condon T and Tuohy P (2024) A semi-
quantitative risk model for dairy farms to
pinpoint and break source-pathway
connections between nutrient sources and
open drainage channel sections.
Front. Environ. Sci. 12:1435418.
doi: 10.3389/fenvs.2024.1435418
COPYRIGHT
© 2024 Opoku, Healy, Fenton, Daly, Condon
and Tuohy. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The use,
distribution or reproduction in other forums is
permitted, provided the original author(s) and
the copyright owner(s) are credited and that the
original publication in this journal is cited, in
accordance with accepted academic practice.
No use, distribution or reproduction is
permitted which does not comply with these
terms.
Frontiers in Environmental Science frontiersin.org01
TYPE Original Research
PUBLISHED 23 September 2024
DOI 10.3389/fenvs.2024.1435418
excess water from different parts of a farm to larger water courses
(Kröger et al., 2007). Within the open drainage channel network,
streams exist as intermittent or perennial natural channels, whereas
drainage ditches exist as man-made channels that may be
intermittent or perennial, depending on their landscape position
and their interplay with subsurface water and groundwater. These
open drainage channels perform many functions (Daly et al., 2017;
Ezzati et al., 2020) including storage and release of nutrients by
sediments, transportation and interception of farm surface and
subsurface runoff which may carry nutrients to the larger
water courses.
It is important to minimise the source of nutrients and intercept
instantaneous and legacy nutrients from farms in high rainfall areas
(Fenton et al., 2021;Peyton et al., 2016;Valbuena-Parralejo et al.,
2019). In these areas, open drainage channels form an integral part
of the source, mobilisation, pathway, and receptor (S-M-P-R)
component of the nutrient transfer continuum (Haygarth et al.,
2005) (defined as the framework that captures the nutrient-loss
influencing factors from source to receptor). Water drained in both
natural and man-made open drainage channels may be nutrient-rich
from different nutrient sources that are mobilised through point
(e.g., farmyard (Martínez-Suller et al., 2010;Vero et al., 2020), farm
roadway (Fenton et al., 2021;Rice et al., 2022) and diffuse (Daly
et al., 2017;Roberts et al., 2017)) sources. Where hydrological
connectivity exists with the surrounding environment, nutrients
from these sources travel through different pathways (Wall et al.,
2011) to enter open drainage channels. The nutrients are either
transformed or remain unchanged along the pathway to the open
drainage channel, before being transported to the adjoining
waterways (Clagnan et al., 2018). Aside from nutrient
transformation, these nutrients can be buffered and/or retained
to prevent connectivity losses as they go through the processes
and pathways (Deelstra et al., 2014). Understanding the nutrient
dynamics and loss risks occurring within an open drainage channel
system is critical to assessing, managing and mitigating nutrient
losses from farms (Collins et al., 2016;Herzon and Helenius, 2008).
Moloney et al. (2020) ranked connectivity risk for phosphorus
(P) loss along man-made open drainage channels and showed that
varying levels of connectivity to nutrient source, depending on their
geographical position, exist between man-made open drainage
channels and surface waters. The highest to lowest connectivity
for P loss was as follows: farmyard connection ditch, outlet (a ditch
that connects the drainage network to a surface water body), outflow
(a ditch that carries drainage water across the farm boundary
through neighbouring land), secondary, or disconnected ditch.
Opoku et al. (2024) further developed this concept by creating an
integrated (i.e., P and nitrogen (N)) ranked connectivity risk
incorporating nutrient loss from sources within open drainage
channels. That study showed that other factors, i.e., farm
management practices, landscape characteristics, and surface and
subsurface hydrological connectivity of directly connecting areas,
described the risk of P and N loss in categories of man-made open
drainage channels. These factors vary spatially and temporally
(Harrison et al., 2019;Mellander et al., 2017;Withers and Lord,
2002), even in a very small distance (Adams et al., 2022), and
therefore may vary in the nutrient loss risk they pose for individual
open drainage channels at different geographic locations on farm.
Characterising these factors for individual open drainage channels is
essential to assess the risk of connectivity for nutrient losses from an
open drainage channel network, but is not well studied. In previous
nutrient loss risk studies, open drainage channels were risk assessed
largely as a (transport) pathway factor for nutrient loss based on
either their presence, density, connectivity to high-risk fields or
sloping conditions (Buczko and Kuchenbuch, 2007;Magette et al.,
2007;Roberts et al., 2017;Schoumans and Chardon, 2003), thereby
limiting a holistic assessment (Granger et al., 2010). Furthermore, in
studies where these factors have been used in assessing farm nutrient
loss connectivity (Deelstra et al., 2014;Gramlich et al., 2018), their
influences on connectivity to open drainage channels under their
respective nutrient transfer continuum sections to enable complete
understanding of their nutrient loss risks (Haygarth et al., 2005;
Murphy et al., 2015) and improve regulations (Wall et al., 2011) have
not been evaluated. Such an evaluation could be achieved by
exploring a risk assessment of the factors under the nutrient
transfer continuum of open drainage channels and may allow
mitigation efforts to be optimised to prevent nutrient losses to
open drainage channels and transfer to adjoining water bodies.
Risk assessment provides an overall appraisal of the connectivity
components for each element (S-M-P-R) of the nutrient transfer
continuum to inform their combined implications and relationships
for nutrient loss to open drainage channels on farms (Jordan et al.,
2005). Risk can be assessed quantitatively (where data are sufficient;
Adkin et al., 2014), qualitatively (where data are insufficient; Nag
et al., 2020), and semi-quantitatively (a blend of the two, e.g., Rice
et al., 2022)). Subjective expert judgment may be used to
approximate risk values to inform decision-making (Redmill,
2002;Rice et al., 2022). Different assessment approaches to
identify and characterise landscape hotspots for nutrient losses
have been documented. These include direct nutrient
concentration measurements in open drainage channels (Ezzati
et al., 2020;Mattila and Ezzati, 2022), a combination of some
nutrient transfer continuum parameters (Alder et al., 2015;Hayes
et al., 2023;Fenton et al., 2022), or predictive models (Radcliffe et al.,
2015;Vadas et al., 2007;Vadas et al., 2015). A risk assessment to
identify open drainage channel sections associated with high-risk
nutrient runoff connectivity using all possible field management
data, and landscape and hydrological connectivity data across the
nutrient transfer continuum for heavy textured farms has not been
developed to date. Undertaking an appraisal incorporating these
elements will help identify and rank high-risk areas (also known as
critical source areas; McDowell et al., 2024) on the open drainage
channel network for heavy textured grassland dairy farms for
targeted mitigation.
The objective of this study was to develop a semi-quantitative
risk model for heavy textured grassland dairy farms that identifies
open drainage channel network sections that pose a risk of
contributing nutrients to the adjoining aquatic water courses and
which require mitigation. Instead of considering only nutrient
source connectivity to classify open drainage channel risks for
nutrient losses (as in Opoku et al. (2024)), the current study
builds on this theory and captures all relevant S-M-P-R factors
under the open drainage network nutrient transfer continuum to
rank the nutrient loss risk in the open drainage channel network on a
farm. To conduct this research, data were collected during field and
desk-based studies across seven heavy textured grassland farms in
Ireland. These farms are considered representative of heavy
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textured, poorly draining soils in Ireland, all receive high rainfall and
were subjected to high-resolution data collection on a vast range of
static and dynamic variables related to farm management.
2 Materials and methods
2.1 Nutrient transfer continuum framework
A semi-quantitative risk assessment model was developed based
on seven intensive grassland heavy textured dairy farms. Using
expert opinion and the literature, various parameters that best
describe the nutrient transfer continuum between a source and
an open drainage channel network (Dollinger et al., 2015;Kleinman
et al., 2011;Needelman et al., 2007) were collated and categorised
into S-M-P-R components as in Table 1.
2.1.1 Justification to S-M-P-R parameters
2.1.1.1 Source
In a nutrient loss risk assessment, identifying potential sources
and their characteristics is critical (Carton et al., 2008;McDowell
et al., 2024). Farmyards are largely associated with potential nutrient
sources, and connection to them imposes high-risk of direct or
indirect discharges of point source nutrients into the open drainage
TABLE 1 Nutrient transfer continuum element, parameter description, units, type, relative magnitude score, relative impact score, and denotation.
Nutrient transfer
continuum
element
Parameter
Description
Parameter unit Parameter
type
Relative
magnitude (M)
score
a
Denotation Relative
impact (I)
score
b
Source (Point) Connection to
farmyard
Categorical 0
3
No
Yes (e.g., pipe discharge,
seepage from leaking
tanks)
10
Source (Diffuse) Soil P mg/L Categorical 1
3
Adequate (<8.0 m/L)
Excessive (≥8.0 mg/L)
5
Source (Diffuse) N Fertiliser (kg) applied kg N ha
-1
Continuous Weighted to 0–38
Source (Diffuse) P Fertiliser (kg) applied kg P ha
-1
Continuous Weighted to 0–38
Source (Diffuse) Nutrient deposition
associated with grazing
(e.g., urine, dung pats)
Grazed or non-grazed
field × grazing
frequency
Continuous Weighted to 0–3
(Based on grazing field
(1 = not grazed, 3 =
grazed) ×grazing
frequency)
6
Source (Diffuse) Fertiliser application
count
#per field Continuous Weighted to 0–33
Mobilisation Rainfall mm Continuous 1
2
3
Low (<1,000 mm)
Moderate
(1,000–1,300 mm)
High (>1,300 mm)
10
Pathway Farm roadway runoff Categorical 0
1
2
3
No
c
Yes –flat slope
Yes - moderate slope
Yes –steep slope
4
Pathway Farmyard surface
runoff
Categorical 0
1
2
3
No
c
Yes –flat slope
Yes - moderate slope
Yes –steep slope
3
Pathway Field surface runoff Categorical 0
1
2
3
No
c
Yes –flat slope
Yes - moderate slope
Yes –steep slope
6
Pathway Subsurface connection
from infield drains
Categorical 0
3
No
Yes (e.g., low flow
discharge from pipes)
4
Pathway Groundwater
connection to ditch
Categorical 0
3
No
Yes (e.g., springs,
upwelling and seepage)
3
Receptor Connection to
watercourse
Categorical 0
3
No
Yes
7
a
Relative Magnitude score (M) = the relative magnitude of contributing nutrients to an open drainage channel network.
b
Relative Impact score (I) = subjective evaluation of relative relevance (on a 1–10 scale) for nutrient contribution to an open drainage channel network.
c
A barrier, e.g., buffer prevents connectivity of this runoff according to EPA (2020) and USDA (2001) with the surface water (man-made or natural) body.
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channel network (Moloney et al., 2020;Opoku et al., 2024;Vero
et al., 2020). Soil P status of fields directly connected to open
drainage channels offers a potential source contribution of soil
nutrients that can be readily lost, and dictates the amount of P
that can be applied in a mineral or organic soil (Moloney et al.,
2020), and is therefore essential as a source parameter. The organic
matter proportion in mineral and organic soils determines the
adsorption or repulsion of dissolved nutrients unto soil particles
(Roberts et al., 2017;Tejada and Gonzalez, 2008) and therefore
influences the soil P status. Soil P Indices of 1, 2 and 3 are defined as
low risk, while index 4 is defined as high-risk, with all organic soils
categorised as index 4 by default (Daly, 2005;Wall and Plunkett,
2016). The amount of P and N fertiliser (kg) applied is one of the
major nutrient sources that influences surface and subsurface
nutrient losses in open drainage channels (Hart et al., 2004;
Ibrahim et al., 2013;Richards et al., 2015;Watson and Foy,
2001). The rate of fertiliser application increases soluble reactive
P (SRP) and total P (TP) concentrations in overland flow and
drainage water (Watson et al., 2007). On these connecting fields,
fertiliser application count is another source parameter that
contributes nutrient loss to open drainage channels and may
increase nutrient losses especially under wet soil conditions. The
grazing status of a field connecting to open drainage channel
specifies the risk of another major nutrient source that
determines probability of livestock wastes (faeces and urine)
being deposited near an open drainage channel (Bilotta et al.,
2007;Gary et al., 1983;Hubbard et al., 2004) and damage to
soils (that may be high nutrient rich) by trafficking and poaching
to runoff into open drainage channels (Cassidy et al., 2017;Doody
et al., 2014;Pietola et al., 2005). Its impact varies with grazing
frequency (the number of times a grazing field is accessed by animals
for grazing), with frequently grazed fields more susceptible to
increase nutrient losses (Cassidy et al., 2017;Doody et al., 2014;
Hubbard et al., 2004).
2.1.1.2 Mobilisation
Rainfall is the prime mobilising parameter that controls the
transfer of nutrients within and around the open drainage channel
(Pérez-Gutiérrez et al., 2020;Vadas et al., 2011;Yao et al., 2021).
2.1.1.3 Pathway
Farm roadways that are connected to open drainage channels
under the nutrient transfer continuum acts as pathway by which
runoff, carrying nutrients, is transferred into the open drain (Maher
et al., 2023;Rice et al., 2022). Along the farm roadway network,
nutrients may be contributed from the road surface (Davison et al.,
2008;Edwards and Withers, 2008;Fenton et al., 2022). The farmyard
is another pathway, which comprises hard standing areas that collect
rainfall that becomes runoff to the adjacent open drainage channels
(Edwards et al., 2008;Vero et al., 2020). The field surface influences
runoff to connecting open drainage channels. Field surface is
dependent of the soil drainage class (well, moderate, imperfect,
and poorly-draining soils) and this dictates the runoff pathway
between surface and subsurface pathways (Houlbrooke and
Monaghan, 2009). There is high P loss risk from overland flow
in poorly drained soils, moderate P loss risk from imperfectly
drained soils, low P loss risk from both moderate and well-
drained soils (Magette et al., 2007). The subsurface in-field drain
pathway influences soil drainage capacity and subsequently the
surface and subsurface pathways (Houlbrooke and Monaghan,
2009). Subsurface in-field drains enhance infiltration and other
processes in soils (Opoku et al., 2024). Groundwater upwelling or
seeping pathways introduces nitrate (NO
3
-N) and P into open
drainage channels, but depends on many factors such as
landscape position and soil type (Opoku et al., 2024).
Groundwater composition may be high in nitrate concentrations,
especially if the soil processes are modified by drainage (Edwards
and Withers, 2008).
2.1.1.4 Receptor
The receptor is associated with the final direct impact on a
watercourse (Wall et al., 2011). Watercourse in this regard is defined
as any natural river, stream, or lake (but not a man-made drainage
channel) (Department of Agriculture Food and the Marine, 2018)
identifiable on an Ordnance Survey Ireland 6-inch map (www.osi.
ie). In this study, all natural open drainage channels were assumed to
have a final connection to a watercourse, with or without any
proximity observed during the ground survey.
2.2 Scoring continuous and categorical
parameters
The parameters were assigned individual risk scores that were
scored arithmetically in a magnitude-impact matrix (Teunis and
Schijven, 2019). For each open drainage channel, the risk score for
every parameter was calculated by multiplying the score for
magnitude (M) for contributing nutrients to an open drainage
channel by the score for its relative impact (I) (Table 1) (after
Shariff and Zaini, 2013).
Within the risk assessment, data for some parameters were
measured quantitatively as continuous data (e.g., N fertiliser (kg)
rate applied; Table 1), while others were assessed qualitatively as
categorical data during field observation (e.g., connection to a
farmyard; Table 1). As such, the M value for each parameter
differed depending on the parameter type.
For continuous parameters, the M value was weighted between
0 and 3 using the formula (Equation 1):
Xi−Xmin
()
×3Xmax −Xmin
() (1)
where X
i
is the on-farm observed data value; X
min
and X
max
are the
minimum and maximum values observed across all farms.
For categorical parameters, the value was based on literature
and/or expert judgement. Either “0”or “1”was scored as the
“lowest”and “3”as the “highest”values (Table 1). For each open
drainage channel, a total risk score was calculated by summing up all
the risk scores for each continuous and/or categorical nutrient
transfer continuum parameter for that open drainage channel. A
total risk score represents the degree of risk (i.e., the scale of
likelihood or propensity at which an open drainage channel
contributes nutrients to a watercourse) associated with the blend
of complex parameters (Table 1) for nutrient loss across all the open
drainage channels on a given farm. Although the risk assessment
takes into account the influence of the contributing area to an open
drainage channel, the approach of weighting the contributions over
the area rather than adding their impacts ensured an unbiased
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Opoku et al. 10.3389/fenvs.2024.1435418
assessment where a larger area of fields surrounding the stretch of an
open drainage channel could have led to high-risk. The risk
assessment is simple to use, relying on easily accessible farm
data, and can be used to assess the relative risk agricultural open
drainage channels pose to water quality, without quantifying the
nutrient loss.
2.3 Fieldwork to collect nutrient transfer
continuum parameter data
Seven farms, dominated by heavy textured soils of a wide variety
of bio-physical settings, were selected. These farms represented
varying open drainage channel network density and connectivity
risk compositions. During winter (November 2021 to March 2022),
afield survey was conducted in which all open drainage channel
networks were mapped as per Opoku et al. (2024) and Moloney et al.
(2020). Open drainage channel network features such as connection
to the farmyard, field slope, the proximity to water bodies, and
connectivity pathways for nutrients into the open drainage channel
network from in-field drains, farm roadways, groundwater springs,
seepage and upwelling throughout the open drainage channel
network, were noted on each farm. All the information
characterising the open drainage channel network was recorded
using an electronic device with ESRI ArcGIS Field Maps mobile
software (version 21.4.0) (ESRI, 2024) during the field survey. This
information was transferred to ‘geographic information system’
(GIS) mapping software, ArcMap GIS software (version 10.5).
Data on other parameters for the nutrient transfer continuum
elements was obtained from previous studies (Corbett et al.,
2022a;Corbett et al., 2022b;Tuohy et al., 2021) and ongoing
data collection by participating farmers and field agents. The data
were downloaded and collated with data from the field survey, and
the parameters in Table 1 were assigned an M score for every open
drainage channel network across the farms.
In applying nutrient loss risk magnitude to areas that have never
been calibrated, errors may prevail due to the unknowns in parameter
settings and adjustments, and reliance on experts’opinions to set model
parameters without calibration (Sharpley et al., 2017). However, the
adoption of systems that are assessed and approved (as suggested by
Bhandari et al. (2017);Nelson et al. (2017))enhancedtherobust
calibration of the parameters for the risk assessment.
2.4 Formation of risk classification system
Total risk score values for every open drainage channel for all seven
farms were split into four categories of equal intervals to produce four
potential risk classes (i.e., low risk, moderate risk, high-risk, and very
high-risk). The range was determined by the possible highest and lowest
score that could occur as per the risk assessment scoring system
developed. The risk classes were developed by Equation 2:
TRShigh–TRSlow
4Ie(2)
where TRS
high
and TRS
low
are the highest and lowest total risk score
values recorded across the seven farms, and I
.e.,
is the interval
between the four risk classes. These were colour-coded as green,
yellow, orange, and red, respectively, on farm maps. Such maps
provide information on the open drainage channels that are
potential critical hotspots for nutrient losses on heavy-textured
dairy farms. Risk classes in high and very high-risk ranges are
identified as hotspots that may require mitigation measures.
2.5 Synoptic water sampling across
dairy farms
Water quality parameters change over time, depending on the
local climatic conditions and farming practices (Huebsch et al.,
2013). At 105 sampling points throughout the drainage network
across all farms, a total of 210 water samples (a pair of filtered and
unfiltered at each sampling point) were collected during each season
(sampling event) for 4 seasons (Spring (March) 2022 to Winter
(January) 2023). The sampling was carried out across all 4 seasons to
capture hydrological fluctuations and conditions, including surface
and subsurface connectivity as per Opoku et al. (2024). As this study
aimed to assess the risk of the open drainage channels, the water N
and P chemistry only validated the potential nutrient losses from the
open drainage channel network surroundings and did not aim to
elucidate the load or impact of this connection. Except for
disconnected ditches (which were mostly dry), all man-made
open drainage channels (farmyard connection, outlet, outflow,
and secondary ditches; Moloney et al., 2020) and natural open
drainage channels were sampled. At each water sample location, two
50 mL samples (filtered on-site using 0.45 μmfilter paper and
unfiltered) were collected for dissolved and total P analyses,
respectively. All water samples were kept in an ice box during
sampling and transportation, and then tested within 1 day of
sample collection.
Filtered water samples were analysed for dissolved reactive
phosphorus (DRP) and total dissolved phosphorus (TDP) using a
Gallery discrete analyser (Gallery reference manual, 2016) and a
Hach Ganimede P analyser, respectively. Total dissolved phosphorus
(TDP) was measured by acid persulphate oxidation, under high
temperature and pressure. The unfiltered water samples were
analysed for nitrite (NO
2
-N), NH
4
-N, total oxidised nitrogen (TON),
and total reactive phosphorus (TRP) using a Gallery analyser. Total
phosphorus was analysed using the Ganimede P analyser. Phosphorus
was measured colourimetrically by the ascorbic acid reduction method
(Askew and Smith, 2005), where the 12-molybdophosphoric acid
complex is formed by the reaction of orthophosphate ion with
ammonium molybdate and antimony potassium tartrate (catalyst)
and reduced ascorbic acid. All samples, reagent blanks, and check
standards were analysed following the Standard Methods (APHA,
2005).Allqualitycontrol(QC)samples/check standards are made
from certified stock standards from a different source than
calibration standards. Quality control samples were analysed at the
beginning and end of every batch, and every 10 samples within a batch,
and if the QC fell outside limits, samples were repeated back to the last
correct QC. Blanks were included in every batch and approximately 10%
of samples were repeated. Tolerances range up to a maximum of ±7.5%
of nominal value. All instruments used were calibrated in line with
manufacturers’recommendations. Nitrate-N was calculated by
subtracting NO
2
-N from TON, particulate phosphorus (PP) was the
difference between TP and TDP, and dissolved unreactive phosphorus
(DUP) was the difference between TDP and DRP.
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3 Results and discussion
3.1 Open drainage channel characteristics
The total length and the number of open drainage channels in
the farms are shown in Table 2. The length of an open drainage
channel characterised the field area of contribution influencing the
connectivity and potential risk of nutrient loss to an open drainage
channel. Opoku et al. (2024) reported that multiple connectivity
pathways may exist on a single open drainage channel. Although the
relationship between the presence of connectivity pathways in open
drainage channels and the length of the open drainage channels was
not assessed in that study, longer open drainage channel lengths may
have high connectivity, resulting in a potentially higher risk of
nutrient loss. However, other parameters such as soil chemistry
(Daly et al., 2017;Ezzati et al., 2020), slope, design (Hodaj et al.,
2017), and vegetation (Soana et al., 2017) may also influence
nutrient loss.
3.2 Risk classification system
Table 3 presents the risk classification system ranges based on
the minimum and maximum possible total risk score from the risk
assessment scoring system. These risk classification ranges were the
basis on which risk class output maps for open drainage channel
networks on each farm were developed (Figure 1).
Although the possible lowest and highest total risk score are
14.0 and 201.0 according to the risk assessment scoring system
(Table 3), the actual lowest and highest total risk scores recorded for
the open drainage channels for the farms studied were 35.9 (Farm 4)
and 144.4 (Farm 4), respectively. This indicates the highest total risk
score across the farms reached only about 72% of the potential
maximum total risk score. Of the 171 open drainage channels on all
seven farms, 23%, 68%, 9%, and 0% were ranked as low, moderate,
high, and very high-risk classes, respectively (Figure 2). Data from
individual farms were similar to the overall trend (Figure 2), except
for Farm 6, where the majority (57%) of the open drainage channels
ranked as low-risk.
Across the high-risk open drainage channels, the total risk score
varied, with 144.4 being the highest recorded (a farmyard
connection ditch) on Farm 4 and 109.9 being the lowest (a
farmyard connection ditch) on Farm 7. The 9% high-risk open
drainage channels across the study farms were mostly on farmyard
connection and outlet ditches (Table 4). This result is similar to
Opoku et al. (2024) and Moloney et al. (2020), who found that
farmyard connection ditches were potentially the riskiest.
Agricultural pressures on waterbodies in Ireland are associated
with excess nutrients, mainly present as NO
3
-N or DRP (EPA,
2023a). Phosphorus dominates in poorly drained soils, such as those
included in this study, while N loss is more likely to vary depending
on other specific site conditions (EPA, 2023a). In Ireland, the EPA
considers good water in rivers to have NO
3
-N concentrations of less
than 1.8 mg L
-1
and DRP concentrations of less than 0.035 mg P L
-1
(EPA, 2023b). While open drainage channels assessed in these study
farms are different water bodies from rivers as defined on national
ordnance survey maps (6-inch maps) (www.osi.ie), comparisons of
NO
3
-N and DRP concentrations on the open drainage channels with
the water quality standards for rivers act as a guide to show if a water
sample is high or low.
The annual mean DRP concentrations in the open drainage
channels, which ranged from 0.09 mg L
-1
in moderate-risk class to
0.40 mg L
-1
in high-risk class (Figure 3), were higher than the surface
water standard of 0.035 mg L
-1
. The annual mean NO
3
-N
concentrations on the open drainage channels were lower across
the risk classes, with ranges of 0.59 mg L
-1
in low-risk class to
1.18 mg L
-1
in moderate-risk class (Figure 3) relative to the standard
of 1.8 mg NO
3
-N L
-1
. This is consistent with the poorly draining
conceptual model of the EPA in Ireland, as P losses dominate
nutrients relative to N losses. While this may be beyond the
TABLE 2 The characteristics (length (m) and number) of open drainage channels per farm.
Farm # Number of open
drainage channels per
farm
Average
length
Length of all open drainage channels per farm (m)
Total
length
Natural open drainage
channel average length
Man-made open drainage
channel average length
1 25 291.50 7,290 n/a 203
2 9 271.38 3,799 382 188
3 40 509.23 25,971 1898 170
4 16 397.44 14,308 716 142
5 19 372.71 14,163 1,030 197
6 49 134.95 10,526 322 122
7 13 204.27 4,494 860 139
TABLE 3 Risk classification system (risk class and score ranges) for risk
assessment model for open drainage channels on heavy textured dairy
farms.
Risk class Risk score classification
ranges
Low 14.0 60.7
Moderate 60.8 107.5
High 107.6 154.3
Very high 154.4 201.0
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scope of the present study, 32% of sampling locations had high NO
3
-
N concentrations, indicating the N connectivity pathways that may
be introducing NO
3
-N into these open drainage channels (Opoku
et al., 2024). Average P and N concentrations per risk class increased
as the risk of the open drainage channels increased, except for
average P concentrations for the moderate-risk class (Figure 3). This
could be due to the anthropogenic and natural characteristics that
create hydrochemical variation in the farm landscapes that
contribute nutrients to the open drainage channels. With this
caveat, this showed that the water quality seasonal grab samples
validated the total risk score.
3.3 Assessment of the nutrient transfer
continuum elements on the open
drainage channels
The contribution of the source to the average total risk score of
open drainage channels per farm ranged from 44.2% (Farm 2) to
63.5% (Farm 5) (Figure 4). Similarly, the contribution of the source
to the total risk score of each of the high-risk open drainage channels
ranged from 40.3%–70.2% (Figure 5).
The high proportion for source total risk score indicates that the
multiple sources of nutrients, either from connection to farmyard,
FIGURE 1
A map of a heavy textured grassland dairy farm (Farm #1 from Table 2) showing the risk classes of the open drainage channel network.
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Opoku et al. 10.3389/fenvs.2024.1435418
legacy soil P, fertiliser application, and grazing input parameters,
primarily influenced the risk of nutrient losses (Cassidy et al., 2017;
Moloney et al., 2020) to these open drainage channels. While most
(62.5%) of the high-risk open drainage channels connect farmyards,
the high-risk open drainage channel with the highest source
contribution to a total risk score recorded (70.2%)
(i.e., secondary ditch on Figure 5) had no farmyard connection.
This could be attributed to the open drainage channel’s connectivity
with high soil P-status fields, which received high fertiliser
application for the duration of this study. This, together with
surface and subsurface sources, may have led to the high total
risk score on the other 37.5% of the whole high-risk open
drainage channels with no connection to farmyards.
Along a connected pathway to the open drainage channel, the
mobilisation of nutrients from the source was integral in most of the
open drainage channels. The percentage of mobilisation
contribution to the average total risk score of the open drainage
channels per farm ranged from 10.2% to 31.5% (Figure 4). Rainfall is
the primary factor by which mobilisation occurs for nutrient losses
(Wang et al., 2020). Rainfall characteristics, including the intensity,
duration and frequency, may influence the hydrological conditions
that are critical to the surface and subsurface nutrient movement
(Pérez-Gutiérrez et al., 2020). This necessitates the need to break the
pathway to prevent the mobilised nutrient from the source to
the receptor.
Nutrients enter the open drainage channels through multiple
(surface, shallow subsurface and groundwater) pathways. The
pathway contribution to the average total risk score per farm
ranged from 10.5% to 18.4% (Figure 4). Heavy textured farms
have multiple subsurface and surface connectivity pathways
through which nutrients are lost (Clagnan et al., 2019;Granger
et al., 2010;Opoku et al., 2024), and these may have contributed to
FIGURE 2
Percentages of risk classes for open drainage channels across all farms and within farms (inset).
TABLE 4 Number of high-risk channels (indicated by a ‘X’) by open drainage channel category.
Farm # Natural open
drainage channel
Farmyard
connection ditch
Outlet
ditch
Outflow
ditch
Secondary
ditch
Disconnected
ditch
1X
2
3XXXXX
4X XXX
5 XXX
6X
7XX
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the high-risk open drainage channels. Eighteen-point-six percent
and 18.6% of the high-risk open drainage channels received risk
scores from roadway and farmyard runoff surface connectivity
pathways to the total risk score, respectively, while 87.5% and
31.3% of the high-risk open drainage channels received risk
scores from in-field drains and groundwater subsurface
connectivity pathways, respectively. Although the pathway
percentage contribution to the total risk score of the high-risk
open drainage channels ranged from 10.1%–22.6%, the highest
pathway contribution to total risk score for an open drainage
channel was 44.9% which was a moderate-risk open drainage
channel on Farm 6.
The connection to the receptor was not present on all high-risk
open drainage channels. However, contributions from 14.5% to
18.6% of the total risk score of high-risk open drainage channels
with connection to receptor for the study farms (Figure 5). This
FIGURE 3
(A) Nitrogen and (B) phosphorus mean plus standard error concentrations from seasonal water sampling from within open drainage channels as per
the risk classes across the case study farms.
FIGURE 4
Percentages of averaged risk scores per farm across nutrient transfer continuum elements.
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informs the importance of considering the delivery of the final
nutrient loss through the open drainage channels and may inform
the mitigation type.
3.4 Mitigation of the high-risk open
drainage channels
In Ireland, the EU Nitrates Directive is implemented through the
Nitrates Action Plan (NAP), which appliesto all farms in the country.
This programme of measures outlines best farming practices to
achieve good water quality outcomes for different farm enterprises.
The EPA in Ireland identifies “breaking the pathway”on poorly
draining soils, such as those in the present study, as an effective way to
break the connectivity of surface or near-surface runoff between
sources and waters. Opoku et al. (2024) classified the open
drainage channel network into different ditch categories. Building
on this work, the present study identifies open drainage channel
sections within these large networks to be of higher risk and which
may need mitigation. A combination of targeted measures is therefore
necessary to improve water quality. This may include (1) source
management (2) breaking the pathway (stopping runoff or near-
runoff being delivered to waters), and (3) installation of in-channel
filters (to slow the flow and attenuate a proportion of nutrients in
dissolved and particulate forms from discharging through that open
drainage channel section). On poorly draining soils this combined
treatment train (Bourke et al., 2022) may prevent high nutrient-
content water discharging from high-risk open drainage channel
sections to the broader aquatic environment. Scrutiny of individual
high-risk total risk score for different open drainage channel sections
enables an advisor and farmer to identify specific sources, pathways,
and in-channel actions as required. These may differ due to site-
specific factors and cannot therefore be generic. Farmers are more
inclined to accept less costly measures (van den Berg et al., 2023), and
therefore these should be considered during the selection of mitigation
measures (McDowell et al., 2024; King et al., 2015).
Opoku et al. (2024) and Fenton et al. (2021) detailed potential
mitigation measures and costs available in terms of “break the
pathway”mitigation options and costs. A few examples include:
re-directing runoff away from internal roadways and the farmyard
to collection or buffer areas with low-cost diversion bars or water
bars (Fenton et al., 2021); installation of riparian (spatially targeted
and linear) buffers along natural streams (Stutter et al., 2021)to
control nutrient losses from the upslope field and connected internal
farm roadways (Palmer, 2012;Yuan et al., 2009); targeted
engineered mitigation measures including low-grade weirs (Faust
et al., 2018), bunded drains, filter cells (Teagasc, 2022); and
management of in-channel sediments through maintenance or
characterisation of soil/sub-soil layer chemistry (Shore et al.,
2015), which is both a sink and source of nutrients (Daly et al., 2017).
FIGURE 5
Risk score percentages of nutrient transfer continuum elements for farms with high-risk open drainage channels, excluding Farm 2 which had no
high-risk open drainage channels.
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4 Conclusion
Assessments of nutrient loss from open drainage channels on
poorly draining (heavy textured) soils are largely associated with
predictions of surface runoff from critical hotspots. The risk
assessment developed in this study combines potential water
quality impacts from surface, subsurface, and groundwater
characteristics of connecting fields to produce a colour-coded
model of different potential water quality risk levels by which
open drainage channels can be risk assessed. This risk assessment
enables the production of risk maps that identify potential high- or
very-high risk open drainage channels on dairy farms with heavy
textured soils and assesses the nutrient transfer continuum elements
to inform mitigation. Unlike previous open drainage channel risk
assessment studies of Moloney et al. (2020) and Opoku et al. (2024),
this study critically assesses all the source-mobilisation-pathway-
receptor multi-parameters of the open drainage channel nutrient
transfer continuum framework, provides in-depth information
regarding high-risk open drainage channels to elucidate which
parameters require attention during mitigation. The findings of
this study apply to dairy farms on heavy textured soils in high
rainfall areas, and may (or may not) differ in other geographic areas
with different soils, climates and agricultural practices. However, it
should be noted that the same methodology can be applied
anywhere to develop a semi-quantitative risk assessment that will
inform mitigation management. Future work incorporating varying
risks encountered over time across wider farm characteristics will
improve the risk scoring system to produce a more robust model
that can be applied more generally on farms.
Data availability statement
The original contributions presented in the study are included in
the article/supplementary material, further inquiries can be directed
to the corresponding author.
Author contributions
DO: Conceptualization, Data curation, Formal Analysis,
Investigation, Methodology, Validation, Visualization,
Writing–original draft, Writing–review and editing. MH:
Conceptualization, Funding acquisition, Investigation,
Methodology, Supervision, Validation, Visualization,
Writing–review and editing. OF: Conceptualization, Funding
acquisition, Investigation, Methodology, Supervision,
Visualization, Writing–review and editing. KD:
Conceptualization, Investigation, Methodology, Validation,
Visualization, Writing–review and editing. TC: Funding
acquisition, Methodology, Project administration, Writing–review
and editing. PT: Conceptualization, Funding acquisition,
Investigation, Methodology, Project administration, Resources,
Supervision, Validation, Visualization, Writing–review and editing.
Funding
The author(s) declare that financial support was received for the
research, authorship, and/or publication of this article. The authors
are grateful to Teagasc for the award of a Walsh Scholarship to the
first author [grant number: RMIS-1381] to conduct this research.
Acknowledgments
The authors are grateful to Teagasc for the award of a Walsh
Scholarship to the first author [grant number: RMIS-1381] to
conduct this research, and to Simon Leach, Asaf Shnel and Denis
Brennan for GIS, fieldwork and laboratory assistance provided.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and
do not necessarily represent those of their affiliated organizations, or
those of the publisher, the editors and the reviewers. Any product that
may be evaluated in this article, or claim that may be made by its
manufacturer, is not guaranteed or endorsed by the publisher.
References
Adams, R., Doody, D. G., Anderson, A., Fenton, O., Tuohy, P., and Vadas, P. (2022).
Evaluating scenarios to reduce phosphorus transport in surface waters from slurry
applications in temperate grasslands. Hydrological Sci. J. 67 (8), 1216–1227. doi:10.1080/
02626667.2022.2072221
Adkin, A., Jones, D. L., Eckford, R. L., Edwards-Jones, G., and Williams, A. P. (2014).
A quantitative risk assessment for the safety of carcase storage systems for scrapie
infected farms. J. Appl. Microbiol. 117 (4), 940–948. doi:10.1111/jam.12596
Alder,S.,Prasuhn,V.,Liniger,H.,Herweg,K.,Hurni,H.,Candinas,A.,etal.
(2015). A high-resolution map of direct and indirect connectivity of erosion risk
areas to surface waters in Switzerland—a risk assessment tool for planning and
policy-making. Land Use Policy 48, 236–249. doi:10.1016/j.landusepol.2015.
06.001
APHA (2005). Standard methods for the examination of water and wastewater.
Washington, DC: American Public Health Association.
Askew, F. E., and Smith, R. K. (2005). “Inorganic non metallic constituents;
Phosphorus; Method 4500-P F. Automated ascorbic acid reduction method,”in
Standard methods for the examination of waters and waste water. Editor A. Bryman
21st edn (Washington, DC: American Public Health Association), 4–155.
Bhandari, A. B., Nelson, N. O., Sweeney, D. W., Baffaut, C., Lory, J. A., Senaviratne, A.,
et al. (2017). Calibration of the APEX model to simulate management practice effects on
runoff, sediment, and phosphorus loss. J. Environ. Qual. 46 (6), 1332–1340. doi:10.2134/
jeq2016.07.0272
Bilotta, G., Brazier, R., and Haygarth, P. (2007). The impacts of grazing animals on the
quality of soils, vegetation, and surface waters in intensively managed grasslands. Adv.
Agron. 94, 237–280. doi:10.1016/S0065-2113(06)94006-1
Bourke, M., Wilkinson, M. E., and Srdjevic, Z. (2022). Nature-based solutio ns for flow
reduction in catchment headwaters. Spatial Flood Risk Manag. Implement. Catchment-
Based Retent. Resil. Private Land Front,13–32. doi:10.4337/9781800379534.00009
Frontiers in Environmental Science frontiersin.org11
Opoku et al. 10.3389/fenvs.2024.1435418
Buczko, U., and Kuchenbuch, R. O. (2007). Review Article: Phosphorus indices as
risk-assessment tools in the U.S.A. and Europe - A review. J. Plant Nutr. Soil Sci. 170 (4),
445–460. doi:10.1002/jpln.200725134
Carton, O. T., Tunney, H., Daly, K., Ryan, M., Kurz, I., Doody, D., et al. (2008).
Eutrophication from Agricultural Sources.
Cassidy, R., Doody, D. G., and Watson, C. J. (2017). Impact of legacy soil phosphorus
on losses in drainage and overland flow from grazed grassland soils. Sci. Total Environ.
575, 474–484. doi:10.1016/j.scitotenv.2016.07.063
Clagnan, E., Thornton, S. F., Rolfe, S. A., Tuohy, P., Peyton, D., Wells, N. S., et al.
(2018). Influence of artificial drainage system design on the nitrogen attenuation
potential of gley soils: Evidence from hydrochemical and isotope studies under
field-scale conditions. J. Environ. Manag. 206, 1028–1038. doi:10.1016/j.jenvman.
2017.11.069
Clagnan, E., Thornton, S. F., Rolfe, S. A., Wells, N. S., Knoeller, K., Murphy, J., et al.
(2019). An integrated assessment of nitrogen source, transformation and fate within an
intensive dairy system to inform management change. PLoS ONE 14 (7), 1–22. doi:10.
1371/journal.pone.0219479
Collins, S. D., Shukla, S., and Shrestha, N. K. (2016). Drainage ditches have sufficient
adsorption capacity but inadequate residence time for phosphorus retention in the
Everglades. Ecol. Eng. 92, 218–228. doi:10.1016/j.ecoleng.2016.04.003
Corbett, D., Lynch, B., Wall, D. P., and Tuohy, P. (2022a). The response of finely
textured and organic soils to lime and phosphorus application: Results from an
incubation experiment. Soil Use Manag. 39, 368–384. doi:10.1111/sum.12825
Corbett, D., Wall, D. P., Lynch, M. B., and Tuohy, P. (2022b). The influence of
phosphorus application and varying soil pH on soil and herbage properties across a
range of grassland soils with impeded drainage. J. Agric. Sci. 160, 516–527. doi:10.1017/
s0021859622000363
Daly, K. (2005). Evaluating Morgan ’s Phosphorus Test as an Environmental
Indicator. Available at: http://www.teagasc.ie/research/reports/environment/4976/
eopr4976.pdf.1, 1–19.
Daly, K., Tuohy, P., Peyton, D., Wall, D. P., and Fenton, O. (2017). Field soil and ditch
sediment phosphorus dynamics from two artificially drained fields on poorly drained
soils. Agric. Water Manag. 192, 115–125. doi:10.1016/j.agwat.2017.07.005
Davison, P. S., Withers, P. J. A., Lord, E. I., Betson, M. J., and Strömqvist, J. (2008).
PSYCHIC - A process-based model of phosphorus and sediment mobilisation and
delivery within agricultural catchments. Part 1: Model description and
parameterisation. J. Hydrology 350 (3–4), 290–302. doi:10.1016/j.jhydrol.2007.10.036
Deelstra, J., Iital, A., Povilaitis, A., Kyllmar, K., Greipsland, I., Blicher-Mathiesen, G.,
et al. (2014). Reprint of “Hydrological pathways and nitrogen runoff in agricultural
dominated catchments in Nordic and Baltic countries.”.Agric. Ecosyst. Environ. 198,
65–73. doi:10.1016/j.agee.2014.06.032
Department of Agriculture Food and the Marine (2018). Woodland for Water:
Creating new native woodlands to protect and enhance Ireland’s waters. Available at:
www.agriculture.gov.ie/forestservice.
Dollinger, J., Dagès, C., Bailly, J. S., Lagacherie, P., and Voltz, M. (2015). Managing
ditches for agroecological engineering of landscape. A review. Agron. Sustain. Dev. 35
(3), 999–1020. doi:10.1007/s13593-015-0301-6
Doody, D. G., Ferris, C. P., and Watson, C. J. (2014). Nutrient losses from two
contrasting dairy cow grazing systems. Biol. Environ. Proc. R. Ir. Acad. 114B (2), 61.
doi:10.3318/bioe.2014.10
Edwards, A. C., Kay, D., McDonald, A. T., Francis, C., Watkins, J., Wilkinson, J. R.,
et al. (2008). Farmyards, an overlooked source for highly contaminated runoff.
J. Environ. Manag., 87(4), 551–559. doi:10.1016/j.jenvman.2006.06.027
Edwards, A. C., and Withers, P. J. A. (2008). Transport and delivery of suspended
solids, nitrogen and phosphorus from various sources to freshwaters in the UK.
J. Hydrology 350 (3–4), 144–153. doi:10.1016/j.jhydrol.2007.10.053
EPA. (2020). Council Directive of 12 December 1991 concerning the protection
of waters against pollution caused by nitrates from agricultural sources (91/676/
EEC) Article 10 Report for Ireland for the Period 2016-2019: Vol. 375/1 (Issue
December).
EPA (2023a). Ireland’s national water quality monitoring programme 2022–2027.
Ireland: Environmental Protection Agency. Available at: http://www.ctic.org/media/
Detailed NWQMC Agenda.pdf.
EPA (2023b). “Water Quality in 2022,”in Water quality in 2022 an indicators report.
Available at: https://www.epa.ie/publications/monitoring–assessment/freshwater–
marine/water-quality-in-2020.php.
ESRI (2024). ArcGIS field maps mobile. Software. Available at: https://www.esri.com/
en-us/arcgis/products/arcgis-field-maps.
Ezzati, G., Fenton, O., Healy, M. G., Christianson, L., Feyereisen, G. W., Thornton, S.,
et al. (2020). Impact of P inputs on source-sink P dynamics of sediment along an
agricultural ditch network. J. Environ. Manag. 257 (March), 109988. doi:10.1016/j.
jenvman.2019.109988
Faust, D. R., Kröger, R., Moore, M. T., and Rush, S. A. (2018). Management Practices
Used in Agricultural Drainage Ditches to Reduce Gulf of Mexico Hypoxia. Bull.
Environ. Contam. Toxicol. 100 (1), 32–40. doi:10.1007/s00128-017-2231-2
Fenton, O., Rice, P., Murnane, J. G., Tuohy, P., and Daly, K. (2022). Dairy farm
roadway surface materials as a P-source within the nutrient transfer continuum
framework. Front. Environ. Sci. 10 (October), 1–13. doi:10.3389/fenvs.2022.878166
Fenton, O., Tuohy, P., Daly, K., Moloney, T., Rice, P., and Murnane, J. G. (2021). A
Review of On-farm Roadway Runoff Characterisation and Potential Management
Options for Ireland. Water, Air, Soil Pollut. 232 (Issue 3), 89. doi:10.1007/s11270-
021-05027-0
Gary, H. L., Johnson, S. R., and Ponce, S. L. (1983). Cattle grazing impact on surface
water quality in a Colorado Front Range stream. J. Soil & Water Conservation 38 (2),
124–128.
Gramlich, A., Stoll, S., Stamm, C., Walter, T., and Prasuhn, V. (2018). Effects of
artificial land drainage on hydrology, nutrient and pesticide fluxes from agricultural
fields –A review. Agric. Ecosyst. Environ. 266 (August), 84–99. doi:10.1016/j.agee.2018.
04.005
Granger, S. J., Bol, R., Anthony, S., Owens, P. N., White, S. M., and Haygarth, P. M.
(2010). “Towards a holistic classification of diffuse agricultural water pollution from
intensively managed grasslands on heavy soils,”.Advances in agronomy. 1st ed., Vol. 105
(Elsevier Inc), 83–115. doi:10.1016/S0065-2113(10)05003-0
Harrison, S., McAree, C., Mulville, W., and Sullivan, T. (2019). The problem of
agricultural ‘diffuse’pollution: Getting to the point. Sci. Total Environ. 677, 700–717.
doi:10.1016/j.scitotenv.2019.04.169
Hart, M. R., Quin, B. F., and Nguyen, M. L. (2004). Phosphorus Runoff from
Agricultural Land and Direct Fertilizer Effects: A Review. J. Environ. Qual. 33 (6),
1954–1972. doi:10.2134/jeq2004.1954
Hayes, E., Higgins, S., Geris, J., Nicholl, G., and Mullan, D. (2023). Weighted risk
assessment of critical source areas for soil phosphorus losses through surface runoff
mechanisms. Catena 225, 107027. doi:10.1016/j.catena.2023.107027
Haygarth, P. M., Condron, L. M., Heathwaite, A. L., Turner, B. L., and Harris, G. P.
(2005). The phosphorus transfer continuum: Linking source to impact with an
interdisciplinary and multi-scaled approach. Sci. Total Environ. 344 (1-3 SPEC.
ISS.), 5–14. doi:10.1016/j.scitotenv.2005.02.001
Herzon, I., and Helenius, J. (2008). Agricultural drainage ditches, their biological
importance and functioning. Biol. Conserv. 141 (5), 1171–1183. doi:10.1016/j.biocon.
2008.03.005
Hodaj, A., Bowling, L. C., Frankenberger, J. R., and Chaubey, I. (2017). Impact of a
two-stage ditch on channel water quality. Agric. Water Manag. 192, 126–137. doi:10.
1016/j.agwat.2017.07.006
Houlbrooke, D. J., and Monaghan, R. M. (2009) The influence of soil drainage
characteristics on contaminant leakage risk associated with the land application of farm
dairy effluent Prepared for Environment Southland, 32. October.
Hubbard, R. K., Newton, G. L., and Hill, G. M. (2004). Water Quality and the Grazing
Animal. J. Anim. Sci. 82 E-Suppl, E255–E263. doi:10.2527/2004.8213_supplE255x
Huebsch, M., Horan, B., Blum, P., Richards, K. G., Grant, J., and Fenton, O. (2013).
Impact of agronomic practices of an intensive dairy farm on nitrogen concentrations in
a karst aquifer in Ireland. Agric. Ecosyst. Environ. 179, 187–199. doi:10.1016/j.agee.2013.
08.021
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. Biol. Environ. 113 B (2), 1–18.
doi:10.3318/BIOE.2013.13
Jordan, P., Menary, W., Daly, K., Kiely, G., Morgan, G., Byrne, P., et al. (2005).
Patterns and processes of phosphorus transfer from Irish grassland soils to rivers -
Integration of laboratory and catchment studies. J. Hydrology 304 (1–4), 20–34. doi:10.
1016/j.jhydrol.2004.07.021
Kleinman, P. J. A., Sharpley, A. N., McDowell, R. W., Flaten, D. N., Buda, A. R., Tao,
L., et al. (2011). Managing agricultural phosphorus for water quality protection:
Principles for progress. Plant Soil 349 (1–2), 169–182. doi:10.1007/s11104-011-0832-9
Kröger, R., Holland, M. M., Moore, M. T., and Cooper, C. M. (2007). Hydrological
Variability and Agricultural Drainage Ditch Inorganic Nitrogen Reduction Capacity.
J. Environ. Qual. 36 (6), 1646–1652. doi:10.2134/jeq2006.0506
Magette, W., Hallissey, R., Hughes, K., and Cosgrave, E. (2007). Eutrophication from
Agricultural Sources: Field- and Catchment-Scale Risk Assessment. Environ. Prot.
Agency. Available at: https://www.epa.ie/publications/research/water/ERTDI-Report-
79—Web1.pdf.
Maher, P. J., Murphy, M. D., Egan, M., and Tuohy, P. (2023). An evaluation of
parameters that affect dairy herd movement on Irish pasture-based farms. J. Agric. Sci.,
1–10. doi:10.1017/S0021859623000497
Martínez-Suller, L., Provolo, G., Carton, O. T., Brennan, D., Kirwan, L., and Richards,
K. G. (2010). The composition of dirty water on dairy farms in Ireland. Ir. J. Agric. Food
Res. 49 (1), 67–80.
Mattila, T. J., and Ezzati, G. (2022). A common agricultural soil test can identify legacy
P hotspots in a drainage ditch network. J. Environ. Manag. 302 (Pt A), 113876. doi:10.
1016/j.jenvman.2021.113876
McDowell, R., Kleinman, P. J. A., Haygarth, P., McGrath, J. M., Smith, D., Heathwaite,
L., et al. (2024). A review of the development and implementation of the critical source
Frontiers in Environmental Science frontiersin.org12
Opoku et al. 10.3389/fenvs.2024.1435418
area concept: A reflection of Andrew Sharpley’s role in improving water quality.
J. Environ. Qual.,1–20. doi:10.1002/jeq2.20551
Mellander, P., Jordan, P., Mcdonald, N., and Vero, S. (2017). Nutrient mobilisation
and transfer pathways.
Moloney, T., Fenton, O., and Daly, K. (2020). Ranking connectivity risk for
phosphorus loss along agricultural drainage ditches. Sci. Total Environ. 703, 134556.
doi:10.1016/j.scitotenv.2019.134556
Murphy, P. N. C., Mellander, P. E., Melland, A. R., Buckley, C., Shore, M., Shortle, G.,
et al. (2015). Variable response to phosphorus mitigation measures across the nutrient
transfer continuum in a dairy grassland catchment. Agric. Ecosyst. Environ. 207,
192–202. doi:10.1016/j.agee.2015.04.008
Nag,R.,Whyte,P.,Markey,B.K.,O’Flaherty,V.,Bolton,D.,Fenton,O.,etal.(2020).
Ranking hazards pertaining to human health concerns from land application of anaerobic
digestate. Sci. Total Environ. 710, 136297. doi:10.1016/j.scitotenv.2019.136297
Needelman, B. A., Kleinman, P. J. A., Strock, J. S., and Allen, A. L. (2007). Improved
management of agricultural drainage ditches for water quality protection: an overview.
J. soil water conservation 62 (4), 171–178.
Nelson,N.O.,Baffaut,C.,Lory,J.A.,AnomaaSenaviratne,G.M.M.M.,Bhandari,A.B.,
Udawatta, R. P., et al. (2017). Multisite Evaluation of APEX for Water Quality: II. Regional
Parameterization. J. Environ. Qual. 46 (6), 1349–1356. doi:10.2134/jeq2016.07.0254
Opoku, D. G., Healy, M. G., Fenton, O., Daly, K., Condon, T., and Tuohy, P. (2024).
An integrated connectivity risk ranking for phosphorus and nitrogen along agricultural
open ditches to inform targeted and specific mitigation management. Front. Environ.
Sci., 12, 1–16. doi:10.3389/fenvs.2024.1337857
Palmer, M. (2012). Agricultural fine sediment: sources, pathways and mitigation: a
thesis submitted for the degree of doctor of philosophy at school of civil engineering and
geosciences,. UK: [University of Newcastle upon Tyne]. Available at: https://theses.ncl.
ac.uk/jspui/bitstream/10443/1518/1/Palmer12.pdf.
Pérez-Gutiérrez, J. D., Paz, J. O., Tagert, M. L. M., and Sepehrifar, M. (2020). Impact
of rainfall characteristics on the NO3 –N concentration in a tailwater recovery ditch.
Agric. Water Manag. 233 (3), 106079. doi:10.1016/j.agwat.2020.106079
Peyton, D. P., Healy, M. G., Fleming, G. T. A., Grant, J., Wall, D., Morrison, L., et al.
(2016). Nutrient, metal and microbial loss in surface runoff following treated sludge and
dairy cattle slurry application to an Irish grassland soil. Sci. Total Environ. 541, 218–229.
doi:10.1016/j.scitotenv.2015.09.053
Pietola, L., Horn, R., and Yli-Halla, M. (2005). Effects of trampling by cattle on the
hydraulic and mechanical properties of soil. Soil Tillage Res. 82 (1), 99–108. doi:10.1016/
j.still.2004.08.004
Radcliffe, D. E., Reid, D. K., Blombäck, K., Bolster, C. H., Collick, A. S., Easton, Z. M.,
et al. (2015). Applicability of Models to Predict Phosphorus Losses in Drained Fields: A
Review. J. Environ. Qual. 44 (2), 614–628. doi:10.2134/jeq2014.05.0220
Redmill, F. (2002). Risk analysis - a subjective process. Eng. Manag. J. 12 (2), 91–96.
doi:10.1049/em:20020206
Rice, P., Daly, K., Tuohy, P., Murnane, J. G., Nag, R., and Fenton, O. (2022).
Evaluating connectivity risk of farm roadway runoff with waters - Development and
sensitivity analysis of a semi quantitative risk model. Sci. Total Environ. 851 (August),
158114. doi:10.1016/j.scitotenv.2022.158114
Richards,K.G.,Jahangir,M.M.R.,Drennan,M.,Lenehan,J.J.,Connolly,J.,Brophy,C.,
et al. (2015). Effect of an agri-environmental measure on nit rate leaching from a beef farming
system in Ireland. Agric. Ecosyst. Environ. 202 (April), 17–24. doi:10.1016/j.agee.2014.12.020
Roberts, W. M., Gonzalez-Jimenez, J. L., Doody, D. G., Jordan, P., and Daly, K. (2017).
Assessing the risk of phosphorus transfer to high ecological status rivers: Integration of
nutrient management with soil geochemical and hydrological conditions. Sci. Total
Environ. 589, 25–35. doi:10.1016/j.scitotenv.2017.02.201
Schoumans, O. F., and Chardon, W. J. (2003). Risk assessment methodologies for
predicting phosphorus losses. J. Plant Nutr. Soil Sci. 166 (4), 403–408. doi:10.1002/jpln.
200321222
Shariff, A. M., and Zaini, D. (2013). Inherent risk assessment methodology in
preliminary design stage: A case study for toxic release. J. Loss Prev. Process
Industries, 26(4), 605–613. doi:10.1016/j.jlp.2012.12.003
Sharpley, A., Kleinman, P., Baffaut, C., Beegle, D., Bolster, C., Collick, A., et al. (2017).
Evaluation of Phosphorus Site Assessment Tools: Lessons from the USA. J. Environ.
Qual. 46 (6), 1250–1256. doi:10.2134/jeq2016.11.0427
Shore, M., Jordan, P., Mellander, P. E., Kelly-Quinn, M., and Melland, A. R. (2015).
An agricultural drainage channel classification system for phosphorus management.
Agric. Ecosyst. Environ. 199, 207–215. doi:10.1016/j.agee.2014.09.003
Soana, E., Balestrini, R., Vincenzi, F., Bartoli, M., and Castaldelli, G. (2017).
Mitigation of nitrogen pollution in vegetated ditches fed by nitrate-rich spring
waters. Agric. Ecosyst. Environ. 243 (November 2016), 74–82. doi:10.1016/j.agee.
2017.04.004
Stutter, M., Barros Costa, F., and O Huallachain, D. (2021). Riparian buffer zone
quantitative effectiveness review database. doi:10.17632/t64dbpv63x.3
Teagasc (2022). “GROUNDWATER DRAINAGE SYSTEMS,”in Teagasc manual on
drainage - a best practice manual for Ireland’s farmers. Editors P. Tuohy, O. Fenton, and
M. Moore (Carlow, Ireland: Teagasc), 79–88.
Tejada, M., and Gonzalez, J. L. (2008). Influence of two organic amendments on the
soil physical properties, soil losses, sediments and runoff water quality. Geoderma 145
(3–4), 325–334. doi:10.1016/j.geoderma.2008.03.020
Teunis, P., and Schijven, J. F. (2019). Generic Guidance to Quantitative Microbial Risk
Assessment for Food And Water.
Tuohy, P., O’Loughlin, J., Peyton, D., and Fenton, O. (2018). The performance and
behavior of land drainage systems and their impact on field scale hydrology in an
increasingly volatile climate. Agric. Water Manag. 210 (August), 96–107. doi:10.1016/j.
agwat.2018.07.033
Tuohy, P., O’Sullivan, L., and Fenton, O. (2021). Field scale estimates of soil carbon
stocks on ten heavy textured farms across Ireland. J. Environ. Manag. 281 (December
2020), 111903. doi:10.1016/j.jenvman.2020.111903
Vadas, P. A., Busch, D. L., Powell, J. M., and Brink, G. E. (2015). Monitoring runoff
from cattle-grazed pastures for a phosphorus loss quantification tool. Agric. Ecosyst.
Environ. 199, 124–131. doi:10.1016/j.agee.2014.08.026
Vadas, P. A., Gburek, W. J., Sharpley, A. N., Kleinman, P. J. A., Moore, P. A., Cabrera,
M. L., et al. (2007). A Model for Phosphorus Transformation and Runoff Loss for
Surface-Applied Manures. J. Environ. Qual. 36 (1), 324–332. doi:10.2134/jeq2006.0213
Vadas, P. A., Jokela, W. E., Franklin, D. H., and Endale, D. M. (2011). The effect of
rain and runoff when assessing timing of manure application and dissolved phosphorus
loss in runoff. J. Am. Water Resour. Assoc. 47 (4), 877–886. doi:10.1111/j.1752-1688.
2011.00561.x
Valbuena-Parralejo, N., Fenton, O., Tuohy, P., Williams, M., Lanigan, G. J., and
Humphreys, J. (2019). Phosphorus and nitrogen losses from temperate permanent
grassland on clay-loam soil after the installation of artificial mole and gravel mole
drainage. Sci. Total Environ. 659, 1428–1436. doi:10.1016/j.scitotenv.2018.12.173
van den Berg, L. M., Dingkuhn, E. L., Meehan, N., and O’Sullivan, L. (2023).
Investigating bottlenecks hampering the adoption of water quality-enhancing
practices for sustainable land management in Ireland. J. Environ. Manag. 345
(January), 118741. doi:10.1016/j.jenvman.2023.118741
Vero, S. E., Sherry, E., and Doody, D. (2020). Evidence and perception of phosphorus
loss risk factors in farmyards. Environ. Sci. Policy 114, 542–548. doi:10.1016/j.envsci.
2020.09.025
Wall, D., Jordan, P., Melland, A. R., Mellander, P.-E., Buckley, C., Reaney, S. M., et al.
(2011). Using the nutrient transfer continuum concept to evaluate the European Union
Nitrates Directive National Action Programme. Environ. Sci. & Policy, 14(6), 664–674.
doi:10.1016/j.envsci.2011.05.003
Wall, D., and Plunkett, M. (2016). Nutrient Advice for Productive Agricutural Crops.
Wang, Z.-J., Li, S.-L., Yue, F.-J., Qin, C.-Q., Buckerfield, S., and Zeng, J. (2020).
Rainfall driven nitrate transport in agricultural karst surface river system: Insight from
high resolution hydrochemistry and nitrate isotopes. Agric. Ecosyst. & Environ., 291,
106787. doi:10.1016/j.agee.2019.106787
Watson, C. J., and Foy, R. H. (2001). Environmental impacts of nitrogen and
phosphorus cycling in grassland systems. Outlook Agric. 30 (2), 117–127. doi:10.
5367/000000001101293562
Watson, C. J., Smith, R. V., and Matthews, D. I. (2007). Increase in Phosphorus Losses
from Grassland in Response to Olsen-P Accumulation. J. Environ. Qual. 36 (5),
1452–1460. doi:10.2134/jeq2006.0207
Withers, P. J. A., and Lord, E. I. (2002). Agricultural nutrient inputs to rivers and
groundwaters in the UK: Policy, environmental management and research needs. Sci.
Total Environ. 282–283, 9–24. doi:10.1016/S0048-9697(01)00935-4
Yao, Y., Dai, Q., Gao, R., Gan, Y., and Yi, X. (2021). Effects of rainfall intensity on
runoff and nutrient loss of gently sloping farmland in a karst area of SW China. PLoS
ONE 16 (3 March), e0246505–e0246518. doi:10.1371/journal.pone.0246505
Yuan, Y., Bingner, R. L., and Locke, M. A. (2009). A Review of effectiveness of
vegetative buffers on sediment trapping in agricultural areas. Ecohydrology 130
(February), 321–336. doi:10.1002/eco.82
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