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Joint Water Evidence Programme
Neap-N Nitrate Leaching for 1970 and 2014
Final report WT1550
Produced: December 2015
Funded by the Joint Water Evidence Programme. The Joint Water Evidence Programme comprises Defra and Environment Agency with partners including Natural England and Forestry Commission.
This is a report of research carried out by ADAS, on behalf of the Department for
Environment, Food and Rural Affairs
Research contractor: ADAS
Authors: David Lee, Richard Gooday, Steven Anthony and Isabel Whiteley
Publishing organisation
Department for Environment, Food and Rural Affairs Nobel House, 17 Smith Square London SW1P 3JR
© Crown copyright 2016
Copyright in the typographical arrangement and design rests with the Crown. This
publication (excluding the logo) may be reproduced free of charge in any format or
medium provided that it is reproduced accurately and not used in a misleading context.
The material must be acknowledged as Crown copyright with the title and source of the
publication specified. The views expressed in this document are not necessarily those of
Defra. Its officers, servants or agents accept no liability whatsoever for any loss or
damage arising from the interpretation or use of the information, or reliance on views
contained herein.
1 Introduction .............................................................................................................................. 1
2 Methodology ............................................................................................................................ 1
2.1 The Neap-N Model ........................................................................................................................1
2.2 Updating of the Neap-N Coefficients.............................................................................................1
2.2.1 Cropping ................................................................................................................................2
2.2.2 Pigs and Poultry .....................................................................................................................2
2.2.3 Grazing Livestock ...................................................................................................................2
2.2.4 Resulting Coefficients ............................................................................................................3
2.3 Generation of Landcover and Livestock dataset ...........................................................................4
3 Results ...................................................................................................................................... 4
3.1 Crop and Livestock Datasets ..........................................................................................................4
3.2 Nitrate Leaching ............................................................................................................................4
3.2.1 1970 .......................................................................................................................................5
3.2.2 2014 .......................................................................................................................................7
4 Validation of 2014 results .......................................................................................................... 9
4.1 Outline ...........................................................................................................................................9
4.2 Preparation of dataset for verification of NEAP-N agricultural nitrate loads ...............................9
4.3 Selection of Harmonised Monitoring Scheme sites for analysis ................................................. 10
4.4 Comparison of PARCOM measured nitrate loads with predicted nitrate loads ......................... 11
4.5 Comparison of HMS flow weighted mean measured nitrate concentrations with predicted flow
weighted mean nitrate concentrations .................................................................................................. 12
4.6 Calibration between HMS 95th percentile nitrate concentration and predicted flow-weighted
mean nitrate concentration ................................................................................................................... 13
4.7 Comparison of EA measured 95th percentile concentrations with predicted 95th percentile
nitrate concentrations ............................................................................................................................ 14
4.8 Prediction of WFD catchment nitrate 95th percentile concentrations ........................................ 16
4.9 Discussion of validation .............................................................................................................. 17
5 Discussion ............................................................................................................................... 19
5.1 Comparison of 1970 and 2014 Results ....................................................................................... 19
5.2 Mitigation Impacts ..................................................................................................................... 21
6 Conclusion .............................................................................................................................. 21
7 References .............................................................................................................................. 22
© ADAS 1
This project has delivered national estimates of long-term climate average nitrate leached (pollutant
load and concentrations) from agricultural land. These estimates have been produced for the years 1970
and 2014, to support the designation of Nitrate Vulnerable Zones by the Environment Agency.
The estimates were achieved through use of the NEAP-N (Lord and Anthony, 2000) nitrate leaching
model. The model was parameterised by preparing national data layers of agricultural land use and
livestock numbers for 1970 and 2014, scaling Neap-N model coefficients to represent long-term changes
in nitrogen fertiliser use and livestock performance and running the model for these inputs. The project
has produced national scale databases of the livestock, landcover and cropping for 1970 and 2014 at
1km2 resolution, alongside a national database of the agricultural N losses for the 1970 and 2014
scenarios.
The NEAPN model (Anthony et al., 1996; Lord and Anthony, 2000; Silgram et al., 2001) was developed
under Defra Water Quality funding as a policy tool to allow estimation of nitrate loss from agricultural
land, applicable to any catchment in England and Wales. In essence NEAPN was devised as an export
coefficient model, with adjustments for climate and soil type. Nitrate loss potential coefficients are
assigned to each crop type and livestock category. The livestock coefficients represent the short and
long-term increase in nitrate leaching risk associated with the keeping of stock and the spreading of
manures. For grassland, nitrate leaching loss is represented mainly through the coefficients for grazing
livestock, on the grounds that due to the wide variation in stocking densities, losses are much more
closely correlated with stock numbers than with area of grassland. NEAPN includes a water balance
model and a leaching algorithm, which calculates the proportion of the potential loss that is actually
leached. The NEAPN model operates at 1 km2 resolution, with the input data being the agricultural
census (for each of the cropping and livestock categories),the dominant soil type (sourced from the
Cranfield University NatMap soils dataset), mean annual rainfall (sourced from the UKCP09 1961-90
baseline climate dataset) and potential evapotranspiration for the different crop types. Output of the
model is total annual nitrate-N loss from the soil profile for agricultural land, and associated water flux.
No calculation of groundwater delays or in-river processes is included. The version of NEAPN used in this
project has been modified to better represent the impacts of atmospheric deposition (Lord et al., 2007)
The original NEAPN crop coefficients were designed to represent nitrate leached under different UK
arable crops fertilised in accordance with DEFRA guidelines, derived from Lord (1992), with revisions
based on the results of subsequent research (Lord et al., 1995; Shepherd and Lord, 1996; Webb et al.,
1997; Lord and Mitchell, 1998, Anthony et al., 1996) and the results of measurements on commercial
farms within Nitrate Vulnerable Zones. The original livestock coefficients were derived from research
under-pinning the N-CYCLE model (Scholefield et al., 1991), and subsequently modified by Lord et al
(2007), primarily to account for the typical timing of manure applications using the MANNER model
(Chambers et al., 1999). The original NEAPN coefficients are thus considered to be representative of
agricultural practice and yields circa 2000, and need to be modified to account for differences in farm
practice and yields in 1970 and 2014. When calculating these revised coefficients, the average value for
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any data item was taken over a 5 year period centred on the year of interest (and thus only 3 years for
2014) in order to account for annual fluctuations.
The NEAPN coefficients for crops can be considered as the N at risk of leaching over the winter, and are
thus comparable to soil mineral nitrate (SMN) values in the autumn. The NitCat model (Lord, 1992) uses
a nitrogen balance approach to determining this N at risk of leaching. The nitrogen balance in NitCat is a
function of crop yield, crop N content, fertiliser applied, manure applied and background mineralisation.
Nitrogen losses from manure are accounted for as part of the livestock coefficients and so could be
ignored here. Crop N contents were assumed to be constant over time due to insufficient suitable data,
although Garwood et al (1995) show wheat grain N values ranging between 19.4 and 24.5 kg N t-1
between 1969 and 1994, but with no discernible trend1. The N balance was thus calculated using
fertiliser rates and crop yields only – the effective contribution to the N balance from mineralisation was
assumed to be accounted for in a scalar applied to the N balance to make the results of the calculation
for 2000 equal to the original NEAPN coefficient, and this scalar was assumed to be constant for all
years. Fertiliser rates for each crop type were taken from British Survey of Fertiliser Practice. Crop yields
were taken from Defra statistics for Agriculture in the UK2, supplemented by data for the United
Kingdom taken from the production data available from the Food and Agriculture Organisation (FAO) of
the United Nations3.
The excreta (and thus manure) produced by livestock is generally proportional to body weight, so for
pigs and poultry types (other than laying hens), the original NEAPN coefficients were simply scaled by
changes in body weight. The formula used for the scaling factor, F, was
75.0/ dCF
where C is carcass weight, d is the dressed proportion and the factor of 0.75 converts to metabolic live
weight. Dressed proportions were 0.7 for pigs and 0.75 for poultry. Scaling factors were derived for
1970, 2000 and 2014, and the changes to the coefficients derived for 1970 and 2014 from the ratio of
their scaling factors to the 2000 value. To account for potential annual fluctuations in carcass weights,
the average value over a 5 year period centred on the year of interest (and thus only 3 years for 2014)
was used. Carcass weights were taken from Defra statistics.
For laying hens, changes to the coefficients were based upon egg production per bird taken from Defra
statistics.
The NEAPN coefficients for grazing livestock represent the losses associated with excreta and manure,
and also losses due to the fertiliser used to grow the grass they consume. Therefore it was felt that
changes to the coefficients needed to account for both the changes in livestock yields over time and also
the intensity of production (i.e. the additional fertiliser required to maintain 2 cows on 1 ha of grassland
would result in more than twice the leaching than if that 1 ha of grassland supported only 1 cow of the
same size).
1 Garwood et al (1995) was calculating nutrient balances for England and Wales between 1969 and 1994 and used constant N contents for all crop types except wheat and barley. 2 https://www.gov.uk/government/statistical-data-sets/agriculture-in-the-united-kingdom 3 http://faostat3.fao.org/download/Q/QC/E
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The first stage in this calculation was to determine the number of livestock units (LSU) for all grazing
livestock types. MAFF (1980) states the milk output of a one LSU dairy cow, and how the LSU changes as
milk production changes, which allowed for the calculation of the total number of LSUs for dairy cows
for 1970, 2000 and 2014 using national livestock totals and milk production figures. It also states the LSU
equivalents for a range of animals at different weights, which allowed for a relationship to be derived
between livestock weight and LSUs. Using this relationship, national livestock totals and livestock
weights derived from Defra statistics, it was possible to determine the total LSU for other categories of
grazing livestock. One LSU is defined as requiring 48,000 MJ of metabolisable energy (MAFF, 1980), so it
was possible to determine the total energy required by all grazing livestock. Using national average
fertiliser rates to grassland for the appropriate years (taken from the British Survey of Fertiliser Practice)
and the total area of grassland, it was possible to set up the NCycle model (Scholefield et al, 1991) so
that it produced the required dry matter of grass to provide the necessary amount of metabolisable
energy per hectare of grassland. For this scenario NCycle predicted a loss of nitrate per hectare. An
effective loss per unit of each livestock for each livestock category was then calculated from the energy
requirement, the energy produced per hectare and the leaching per hectare. The ratios of these
leaching values for each livestock category between 1970, 2014 and 2000 was used to scale the original
NEAPN coefficients, deemed representative of 2000, to produce values appropriate for 1970 and 2014.
Table 2.1 below shows how the coefficients have varied between 1970, 2000 and 2014 for some of the
major livestock and crop categories. For wheat, both fertiliser use and yields were lower in 1970, with
much lower potential N loss coefficients, whereas for potatoes, yields were lower in 1970, but fertiliser
rates were higher than today so the risks of N loss are greater. For non-grazing livestock, bodyweights
and production have increased over time, resulting in higher coefficients. For grazed livestock,
coefficients are highest for 2000 as this is where livestock numbers and fertiliser rates to grassland are
highest, coupled with a smaller grassland area and thus a more intensive level of production.
Table 2.1 - Changes in selected coefficients
Category 1970 2000 2014
Winter Wheat 30 45 46
Potatoes 151 120 111
Adult Dairy Cows 25.5 31.3 28.2
Adult Beef Cows 12.3 14.1 12.7
Sheep 1.7 1.7 1.5
Fattening Pigs (>110 kg) 3.68 4.8 5.21
Laying Hens 0.12 0.13 0.14
Note that there are a number of factors that have not been taken in to account when determining the
new coefficients for 1970 and 2014, either due to data availability or due to the constraints of the
coefficient based approach of the NEAPN model. Such changes include crop N contents, timing of
fertiliser applications, timing and method of manure applications, sowing and harvest dates, grazing
management and crop residue management.
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The Neap-N model requires livestock and cropping data input at the 1km2 resolution. The 2014 land
cover and livestock dataset was generated using the 2014 June Survey returns provided by Defra and
Welsh Government. The methodology used to generate a 1km2 dataset from the June Survey returns is
detailed in Comber at al. (2008). This methodology has been used in previous projects to generate
appropriate datasets from survey returns from other years.
Comber at al. (2008) provides full methodological detail of the Dasymetric mapping approach, but in
brief:
Non-agricultural areas were identified using a fixed dataset derived from the CEH Land Cover
Map (1990) and supplementary Ordnance Survey Strategi datasets for urban areas, woodland
and linear features.
An iterative pycnopylatactic approach was used to distribute Parish level counts of livestock and
areas of cropping across the agricultural land present on the 1km2 cells in each parish.
Validation was performed to ensure no significant differences between the total areas and
populations for the derived 1km2 scale data and the nationally reported Defra totals.
Crop and Livestock datasets covering England and Wales have been provided for 1970 and 2014. These
spatially disaggregate the livestock and cropping data to a 1km2 scale. The two datasets have different
livestock and cropping categories, reflecting differences in the data collected in the two years. In
addition, reduced detail in the cropping data collection in Wales mean that there are not values in Wales
for all of the categories that are collected in England.
Nitrate Leaching values have been modelled for each 1km2 in England and Wales for 1970 and 2014.
They have been reported as both total losses, and also split into the following components:
Atmospheric deposition to arable land
Spreading of housed animal manure to arable land
General cropping practices, including fertiliser applications, to arable land
Atmospheric nitrogen deposition to grassland
Spreading of housed animal manure to grassland
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General grassland practices, including fertiliser applications, excreta returns and spreading of
grazed animal manure, to grassland
Atmospheric nitrogen deposition to rough pasture
Excreta deposition to rough pasture
Losses from farm woodland.
Figure 3.1 shows the predicted nitrate leaching from agricultural land for 1970 livestock, cropping and
coefficients. There are peaks in northern East Anglia, the North East above Hull and in some areas of the
Welsh Marches. The lowest values are in the upland areas of Wales and Northern England.
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Figure 3.2 shows the predicted nitrate leaching from agricultural land for 2014 livestock, cropping and
coefficients. The pattern appears similar to 1970, with peaks in northern East Anglia, the North East
above Hull and in some areas of the Welsh Marches. The lowest values are again in the upland areas of
Wales and Northern England.
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The outputs from the NEAP-N (Lord and Anthony, 2000) model (parameterised with 2014 livestock and
cropping data) were combined with modelled nitrate loads from non-agricultural sources to predict
nitrate loads and concentrations in each catchment.
The predicted nitrate loads and concentrations were verified against PARCOM nitrate loads and
concentrations covering the period 2008-2012 (Harmonised Monitoring Scheme (Environment Agency,
2013) and UK Hydrometric Register (Marsh & Hannaford, 2008) data).
The regular monitoring at HMS sites and the large catchment areas for these sites make HMS
monitoring data an excellent independent set of measurements against which to compare predicted
loads and concentrations.
A regression model was calibrated using PARCOM data to convert predicted mean flow-weighted
concentrations to predicted 95th percentile nitrate concentrations. The updated tool was verified using a
larger dataset of measured 95th percentile TIN concentration data covering the period 2004-2009,
provided by the Environment Agency.
The total national modelled agricultural N load for the area of comparison was 240 kt, and average N
losses per ha were generally in the range of 5.4kg/ha to 35.6kg/ha.
The combined framework produced unbiased predictions of nitrate loads and concentrations.
For verification of the NEAP-N predicted agricultural nitrate loads, the following modelled non-
agricultural nitrate loads were used to allow prediction of total nitrate loads in each catchment:
- Modelled nitrate loads from sewage treatment works, diffuse urban sources, septic tanks, storm
tanks, combined sewer overflows, bank erosion as developed in Defra project WQ0223 (Zhang
et al., 2014).
- Modelled nitrate loads from re-charge from historical agricultural nitrate loading to
groundwater, using modelled groundwater nitrate concentrations (Wang et al, in prep).
- Modelled nitrate loads from re-charge from urban nitrate loading to groundwater (Anthony,
2005; Lerner, 2000).
Defra project WQ0223 identified catchments with significant historical loading from agriculture to
groundwater nitrate concentrations (Wang et al, in prep). In catchments which had a modelled
groundwater concentration (n=1413), the proportion of the modern agricultural nitrate load leached to
groundwater (and therefore not contributing to modern nitrate loads in rivers) was modelled as the
Baseflow Index multiplied by the NEAP-N Agricultural N load (in kg) for each WFD waterbody catchment.
In catchments without a modelled groundwater concentration (n=3072), none of the modern
agricultural N load was modelled as being leached to groundwater.
The NEAP-N model outputs as adjusted for leaching to groundwater and N loads from non-agricultural
sources were totalled and accumulated along the flow path to give a cumulative N load (in kg) for each
WFD waterbody catchment.
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The average annual flow was calculated for each catchment using the NEAP-N model to estimate runoff
from agricultural land and the flow from rainfall direct to open water. Runoff from urban areas was
estimated using the Wallingford Procedure (Mitchell et al., 2001).
The effects of in-river retention of N on the total N load were modelled for each catchment, using
Behrendt & Opitz’s (1999) approach and the calculated average annual flows.
The cumulative N load, adjusted for in-river retention, was divided by the cumulative WFD catchment
area to give a predicted N load (in kg per ha) for each catchment and divided by the cumulative
modelled flow to give a predicted N concentration (in mg per l) for each catchment.
Harmonised Monitoring Scheme (HMS) sites were matched with UK Hydrometric Register gauging
stations. The coordinates of each gauging station from the UK Hydrometric Register were used to assign
the sites to WFD waterbody catchments.
Only sites with an HMS sample count >40 were used in the analysis. HMS site 1010, the River Wyre at St
Michaels, was excluded from the analysis because of a strong seasonal bias in the sampling (>40% of
samples taken in November and December and only 7.4% of samples taken in March to June).
Not all gauging stations are located close to the outflow point of the WFD waterbody catchment that
they fall within. The WFD waterbody catchment area was compared with the gauging station catchment
area from the UK Hydrometric Register and sites where the difference between the two areas exceeded
20% of the gauging station catchment area were excluded from the analysis. Sixty-six out of 88 sites
passed the selection criteria. The difference between the areas was <10% of the gauging station
catchment area for 46 out of the 66 sites.
Table 4.1 - Summary of characteristics of the 66 sites used in the analysis
Characteristic Mean Std. dev Minimum Maximum
Mean annual rainfall (mm) 1225 487 582 3049
Modelled WFD catchment area (km2) 1050 1986 50 9966
Agricultural area as % of modelled area 89.9 7.2 72.4 98.6
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Figure 4.1- Map showing location of the 66 HMS sites used in the analysis
HMS measured concentrations and flows were combined with long term average flows and catchment
areas for each site from the UK Hydrometric Register to calculate the annual average measured nitrate
loads in kg/ha at each site.
The annual average measured nitrate loads were compared against predicted nitrate loads. Regression
analysis showed that there was no significant intercept term and that predicted loads on average slightly
overestimated measured loads. Certain mitigation methods currently practiced on some farms are not
explicitly represented in the NEAP-N model – for example improved manure management and fertiliser
timing, and use of buffer strips. National modelling using Farmscoper predicts that current practice of
mitigation methods accounts on average for an 8.9% reduction in nitrate loads.
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Figure 4.2- Graph comparing annual average measured nitrate loads against predicted nitrate loads. Measured load = 0.8834 (±0.0247) x Predicted load, RMSE = 4.226 kg/ha/yr. Red lines show 95% prediction intervals.
HMS measured concentrations and flows were used to calculate an annual flow weighted average
observed concentration for each site. The flow weighted average observed concentrations were
compared against predicted flow weighted mean nitrate concentrations.
Regression analysis showed that there was no significant intercept term and that predicted
concentrations on average were a slight overestimate compared with measured concentrations.
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Figure 4.3 - Graph comparing flow weighted average measured nitrate concentrations against predicted flow weighted average nitrate concentrations. Observed concentration = 0.8687 (±0.0265) x Predicted concentration,
RMSE = 1.069 mg/l. Red lines show 95% prediction
The 95th percentile of HMS observed nitrate concentrations over the period 2008-2012 was calculated
for each site. A regression analysis calculated the average conversion factor between predicted flow-
weighted mean nitrate concentrations and observed 95th percentile nitrate concentrations as 1.278
(±0.034) x predicted flow-weighted mean nitrate concentrations. The RMSE was 1.38 mg/l.
The largest prediction errors occurred in catchments where the agricultural nitrate load accounted for
less than 80% of the total nitrate load. When the regression analysis is restricted to catchments where
the agricultural nitrate load accounts for more than 80% of the total load, the RMSE drops to 0.76mg/l.
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Figure 4.4 - Graph comparing HMS 95th percentile nitrate concentrations against predicted flow weighted mean nitrate concentrations. 95th percentile concentration = 1.278 (±0.034) x Mean concentration, RMSE = 1.375 mg/l.
Red lines show 95% prediction intervals.
The conversion factor of 1.27816 x Mean flow-weighted concentration, calculated from the regression
between HMS measurements and predicted mean concentrations, was used to convert predicted mean
flow-weighted concentrations into predicted 95th percentile concentrations.
The predicted 95th percentile concentrations were compared with measured 95th percentile TIN
concentration data covering the period 2008-2012, which were provided by the Environment Agency
(EA) and are independent of the HMS measurements used as a training dataset to calibrate predicted
flow-weighted mean nitrate concentrations with 95th percentile nitrate concentrations.
The EA measurements were filtered to select monitoring points that are within the main river channel,
within 2km of the corresponding WFD catchment outflow, and where the corresponding WFD
catchment outflow is more than 1km downstream of any sewage treatment works within the same WFD
catchment. There is a level of uncertainty, represented by confidence intervals provided with the data,
associated with the EA measured 95th percentile concentrations which are calculated as Weibull
estimates. Only measurements for which the dataset contained both upper and lower confidence
intervals were used. Following these criteria, 301 EA measured 95th percentile concentrations were
selected for use in the comparison with predicted 95th percentile concentrations.
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Figure 4.5- Map showing the 301 EA monitoring points used in the comparison.
Figure 4.6 - Graph comparing EA measured 95th percentile nitrate concentrations against predicted flow 95th percentile nitrate concentrations. Measured 95th percentile concentration = 0.9272 (±0.0301) x Predicted 95th
percentile concentration + 1.153 (±0.232), R2
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Figure 4.8 - Map showing probability that nitrate 95th percentile concentration exceeds 11.3 mg/l.
There is a strong linear relationship between predicted nitrate loads and PARCOM measured nitrate
loads, with very few outliers. Similarly, there is a strong linear relationship between predicted mean
flow-weighted concentrations and HMS mean flow-weighted concentrations, with few outliers,
demonstrating that the estimated nitrate loads and concentrations consistently predict the relative
magnitude of observed nitrate loads and concentrations across England and Wales.
Predicted nitrate loads and mean flow-weighted concentrations both on average slightly overestimated
PARCOM measured nitrate loads and HMS mean flow-weighted concentrations. This may be explained
by current mitigation practice not represented in the Neap-N model.
The predicted 95th percentile nitrate concentrations, calibrated from predicted mean flow-weighted
concentrations using HMS measurements as a training dataset, compared well with an independent set
of measured 95th percentile TIN concentrations provided by the Environment Agency, demonstrating the
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strong predictive ability of the modelled nitrate loads and concentrations across all parts of England and
Wales.
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Table 5.1 shows the totals and apportionment of N losses for England and Wales for the two time periods and Figure 5.1 maps the changes at the water
management catchment scale.
Table 5.1 - Comparison of totals between 1970 and 2014
1970 Total (kT)
% of Total
2014 Total (kT)
% of Total
% Change
All Losses 288 256 -11.2
All Losses from ANY Contribution from Arable Land 171 60 155 61 -9.3
All Losses - ANY Contribution from Grassland 102 35 86 34 -15.5
All Losses from Grazed Animal N on Rough Pasture 8 3 8 3 -3.4
All Losses from Atmospheric N on Rough Pasture 1 0 1 0 -12.4
All Losses from Atmospheric N on Woodland and Forest 3 1 3 1 -3.1
All Losses from Atmospheric N on Open Water 2 1 2 1 -0.1
[
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Figure 5.1- Mapped changes in N load between 1970 and 2014 at the water management catchment scale
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The table shows an 11% decrease in total nitrate leaching from agricultural land between the two dates.
The greatest reduction is seen in the losses from grassland (15.5%), with a lesser value from arable
(9.3%).
The smallest changes are the reductions from atmospheric N on woodland and open water, which are
not impacted by changes in agricultural practice, and there is no change in modelled deposition rates for
the two time periods.
Despite some differences in the level of reduction between the two dates, the overall apportionment
has stayed consistent, with approximately 65% of the losses coming from arable land and 35% from
grassland in both 1970 and 2014.
It is inevitable that there will be a large and varied degree of change between the years at the 1km2
scale as the livestock and cropping reporting locations change. Summarising the 1km2 cell values to the
water management catchment level gives a better overall view of the regional patterns of change
(Figure 5.1) level. The map shows large areas of England and Wales with reductions in nitrate leaching,
and a number of regions where the values have stayed consistent. There are only four catchments
where the nitrate leaching is estimated to have increased over the time period, one of the main drivers
for these changes appears to be pig production. Both the Hull and East Riding WMC (red area on the
East of the map) and the Waver WMC (red catchment in the North West) are now major areas for pig
production, and both have shown a large increase in pigs over the time period (total pigs increased
430% for the Waver, 57% for Hull and East Riding from a much greater starting level). In addition, the
loss coefficients for pigs have also increased over this time period (all have increased by between 14 and
41%). This combination of large increases in pig numbers in these catchments coupled with the increase
in pig loss coefficients (due to typical pigs in 2014 being larger than 1970) has led to increases in nitrate
leaching in these areas.
The Neap-N model can only reflect the impact of mitigation that is itself reflected in a change in
livestock numbers or cropping areas reported in the June survey, or through the fertiliser rates that have
been used to calculate year-specific crop coefficients. Therefore it will reflect mitigation in the form of
changes in stocking densities or cropping types, but will not reflect in field measures such as buffer
strips.
Previous ADAS work using the Farmscoper model (Gooday et al. 2014) has shown that the magnitude of
impact of current mitigation additional to that represented in Neap-N on nitrate leaching is estimated to
be 8.9% (England only), which is within the likely error of the predicted value for any cell, given the
uncertainty in the exact location of landuse, the use of a single soil type and the application of national
coefficients to represent farm practice. The impact of this current mitigation will also vary spatially
depending on measure take up, local farming types and other conditions.
This project has delivered England and Wales livestock and cropping datasets and nitrate leaching losses
for 1970 and 2014, both at 1km2 resolution. Comparison of the two years shows an approximately 11%
reduction in nitrate leaching. Mapping of the change shows that at the water management catchment
scale, only four catchments showed an increase greater than 5%. The 2014 nitrate leaching values have
© ADAS 22
been validated against monitored data and show a strong relationship between predicted loads and
measured PARCOM values.
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