Nitrogen and phosphorus losses from grassland …...2019/01/02 · Sulphur-coated urea (SCU)...
Transcript of Nitrogen and phosphorus losses from grassland …...2019/01/02 · Sulphur-coated urea (SCU)...
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Nitrogen and phosphorus losses from grassland soils and potential
abatement strategies
Catherine WatsonFertilizer Association of Southern Africa - 30th July 2015
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• Overview of N & P cycle and losses• Good management strategies• Improving N fertiliser efficiency
- Slow release-controlled release products
- Urease inhibitors
- Nitrification inhibitors
• Phosphorus losses & mitigation• Conclusions
Outline of presentation
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Animal
Soil/Plant System
INPUTS OUTPUTS
AtmosphereFertiliser
Concentrates MilkMeat
Losses to air
Excreta
Losses to water
Grass/silage
NO3, NH4, organic NSRP, SOP, PP
NH3N2O/N2
Grassland agriculture is part of an open system
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Results in eutrophication• Increase in algal and weed biomass• Oxygen depletion of water• Change in algal and plankton species• Added costs of water purification• Change in fish populations
Why are losses to water important?
Cost to N.I. £36 - 61m/yr
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CRITICAL LOAD EXCEEDANCES UK agricultural ammonia emissions 2012
237.7 kt NH3-N£468m/yr
Contributes to acid rain and leads to deposition of N in sensitive ecosystems
Why are ammonia losses important?
Animal housing
32%
Storage13%
Land-spreading
23%
Outdoor17%
Fertilisers16%
(Source: DEFRA, 2013)
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Effects of acid rain on Bleaklow Moor, Derbyshire
(http://www.bbc.co.uk/news/uk-england-17930662)
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N2O is a potent GHG gas with a global warming potential nearly 300 times that of CO2
• In Ireland agriculture is responsible for over 30% of total GHG emissions (mainly as CH4 and N2O)
• EU Directive to reduce GHG emissions by 20% by 2020 and UK Climate Change Act to reduce GHG emissions by 50% by 2050
38.3 kt N2O/yr
97.5 kt N2O/yr
£ 738m/yr
N2O emissions from UK farmed livestockManure
8,8%Machinery
1,6%
Crops9,2%
Fertilisers80,4%
(Source: NAEI, 2014)
Why are nitrous oxide losses important?
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Match N & P supply to crop demand• Fertiliser management (type, rate & timing of application)
• Crop & soil management (improved varieties, use of legumes, good soil drainage, good soil structure, soil & plant testing, control pests and diseases etc.)
• Livestock management (increase production per animal, diet manipulation to reduce N & P excretion)
• Manure management (allow for N & P content of manure, consider storage and timing & method of application)
• Nutrient balance with other essential nutrients (e.g. K, S, trace elements)
Good Management Strategies
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Underuse of sulphur (S) • Dramatic drop in fertiliser and
atmospheric S inputs since 1960’s -negative balances
• Currently, more than 20% of silage and grazed swards are testing as sulphur deficient at 1st cut and 1stgrazing
-30
-20
-10
0
10
20
30
1940 1950 1960 1970 1980 1990 2000year
S b
ala
nc
e k
g S
ha-
1
Cumulative deficit: 256,000 tons S
Cumulative surplus: 200,000 tons S
Underuse of potash (K2O) • More than 20% of 1st and 2nd cut silage
swards may be K deficient and under-performing
Sub-optimal sulphur & potash will : Reduce DM production & Reduce fertiliser N efficiency
AFBI research has developed DRIS analysis to identify nutrient
imbalances in grass
Identifying nutrient imbalances
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Slow or controlled release fertilisers
Delays the availability of a nutrient for plant uptake or extends its availability to the plant longer than ‘rapidly available nutrient fertilisers’
•Slow release – nutrient release pattern is fully dependant on soil and climatic conditions and cannot be predicted
•Controlled release – release pattern, quantity and time can be predicted within certain limits
Improving the efficiency of fertilisers
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Type Description ExamplesOrganic-N low solubility compounds
Condensation products of urea-aldehydes (slow-release)
Urea-formaldehyde (UF)Isobutylidene-diurea (IBDU)Cyclo-diurea/ Crotonylidene diurea(CDU)
Physical barrier -coated/encapsulated
Organic polymer coatings (thermoplastic or resins)Inorganic coatingsMatrices can be hydrophobic (e.g. polyolefines, rubber etc) or hydrophilic (hydrogels)
Polymer coated sulphur-coated urea (PSCU)Polymer coated urea (PCU)Sulphur-coated urea (SCU)Polyolefin coated urea (e.g. Meister®) and coated NPK(+) compounds (e.g. Nutricote®)
Inorganic low-solubility compounds
Slow release Eg. Metal ammonium phosphates (struvites), partially acidulated phosphate rock
Slow and Controlled Release Fertilisers
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Use• Limited use < 0.20 – 0.47% of total world fertiliser
consumption (Trenkel, 2010)• High cost compared to conventional fertilisers has limited
their use to niche non-agricultural markets• They are cost-effective for high-value crops• Recent increase in use due to increased production
capacity for SCU in China, and development of new PCU fertilisers (e.g. Environmentally Smart Nitrogen by Agrium) for agricultural crops in USA (profitable in field crops like maize, rice, wheat & potatoes)
Advantages Disadvantages• N release rate matches crop
demand• Increases nitrogen use efficiency• Reduces N loss to the environment• Reduces number of
applications/rates/ labour saving
• Synchronizing nutrient release to plant need
• High cost per unit N compared to conventional fertilisers
• ‘Burst’, damaged granules• Residues of synthetic material in soil
Slow and Controlled Release Fertilisers
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Well
ModerateUrea Ammonium
(NH4+)Nitrate (NO3-)
NH3
Urea Hydrolysis Nitrification
N2O, N2
Leaching
Urease Inhibitor(inhibit hydrolytic action of ureaseenzyme on urea)
Nitrification Inhibitor(inhibit the biological oxidation of NH4+-N to NO3—N)
DenitrificationVolatilisation
Uptake
CAN CAN
Extends the time the N component of the fertiliser remains in the soil in the urea or ammoniacal form
Soil
Stabilised N fertilisers
Adapted from D Wall
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• Non toxic
• Stable during production, storage and use
• Effective at low concentrations
• Inexpensive
• Compatible with urea or ammoniacal N
Many compounds have been tested but few meet these requirements and are commercially available
Requirements for successful inhibitors
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Advantages Disadvantages• Most concentrated N fertiliser
available (46% N)• Offers transportation advantages
over other sources• Less expensive to manufacture
• Loss of N by ammonia volatilisation• Yield response is often lower than that to
AN/CAN• Can adversely affect seed germination
and seedling growth
United Kingdom (0.86mt N)
Nitrogen consumption (%) of straight N products
Urea fertiliser
South Africa (0.28mt N)Global (137.7mt N)
(IFA data 2012)
17%
64%56%
26%
63%10%
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% inhibition in total NH3-N loss
nBTPT is the most effective ureaseinhibitor – reduces NH3 loss from urea & increases yield
Extensive studies on:Rate of nBTPTFormulationStabilityEffect of soil propertiesRepeated applicationsShort-term plant
physiological effects
Daily NH3 emissions
2NH4+ + HCO3-CO(NH2)2 + H+ + 2H2OureaseX
Tradename is AGROTAIN®
Agrotain treated urea is now marketed in over 70 countries worldwide
Strategy to reduce ammonia loss from urea
% NH3-N loss
S.E. 1.9
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0,0
5,0
10,0
15,0
20,0
25,0
30,0
35,0
40,0
45,0
Prec
ipita
tion
(mm
)
2014 Daily Precipitation (mm)
Soil moisture, rainfall, temperature, soil type, carbon source, rate & form of N
Daily N2O emissions
0
100
200
300
400
500
0 24 48 72 96 120 144
Nitr
ous
oxid
e fl
ux
(mm
olm
-2h-
1 )
Time (hours)
ControlDay 0Day -1Day -2Day -3Day -4LSD
Effect of timing of nitrate fertiliser application after slurry on N2O fluxes
Delaying nitrate fertiliser application for 4 days after slurry is applied can lower N2O emissions
Understanding factors controlling N2O emissions
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Challenge: Manipulate soil N transformations to produce N2 gas(N2O N2)
UreaCAN
02468
101214161820
0 80 160 240 320 400
Cum
ulat
ive
N2O
Em
issi
on(k
g N
2O-N
ha-
1y-
1 )
CAN (kg N ha-1 y-1)
02468
101214161820
0 80 160 240 320 400Cu
mul
ativ
e N
2O E
mis
sion
(kg
N2O
-N h
a-1
y-1 )
Urea (kg N ha-1 y-1)
EF 3.99% EF 0.52%R2 = 0.992 R2 = 0.935
Effect of rate and form of N on N2O emissions
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0
20
40
60
80
100
Soil
NO
3-N (m
g/kg
)
0100200300400500600700800900
N2O
-N (g
ha
d-1 ) CAN
0
5
10
15
20
25
30
Prec
ipita
tion
(mm
)
0102030405060708090
N2O
-N (g
ha
d-1) Urea
0
20
40
60
80
100
Soil
NO
3-N (m
g/kg
)
① ③ ②④ ③ ④⑤② ⑤①
0
5
10
15
20
25
30Pr
ecip
itatio
n (m
m)
2030405060708090
100So
il M
oist
ure
(% G
MC
)
Peak N2O emissions linked to soil nitrate
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Nitrobacter
Nitrosolobus
Nitrosomonas
xNO ON2 2N
Nitrification Inhibitors
Ammonia monooxygenase
Hydroxylamine oxidoreductase −− →→→ 3223 NONOOHNHNH Nitrobacter
Nitrosolobus
Nitrosomonas
xNO ON2 2N
Nitrification Inhibitors
Ammonia monooxygenase
Hydroxylamine oxidoreductase −− →→→ 3223 NONOOHNHNH
−− →→→ 3223 NONOOHNHNH X
Our expertise in 15N isotope techniques has shown that the dominant process generating N2O in Northern Ireland soils is denitrification
We have shown that grassland soils are fungal dominated
Key is to manage the soil nitrate pool
Form of NCAN vs Urea
Inhibitors urease and nitrification
Strategy to reduce N2O emissions
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Nitrapyrin/ N-serve
High(Corrosive)
Low Suitable with anhydrous ammonia with injection into soil
1-2 mg/kg
Rate Relative volatility
Solubility in water
Inhibitor Mode of application
DCD Low High Use in solid, liquid fertilisers & slurry
20 mg/kg(10 kg/ha)
DMPP Low Low Use in solid, liquid fertilisers & slurry
0.5–1.5 kg/ha
Commercially available nitrification inhibitors
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Half Life of DCD at 5, 15, and 25˚C (1st order kinetics)– average of 9 soils, data for 3 reps
High temperatures affect the persistence of DCD
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Greatest % inhibitionon arable soils: average TN = 0.13%
Grass soils: average TN = 0.49%
0
10
20
30
40
50
60
70
80
90
% in
hibi
tion
in n
itrat
e pr
oduc
tion
Arable Grass
Soil properties affect the efficacy of DCD
DCD is less effective in soils with high % clay and high organic matter content
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Direct N2O emission factors (%)
Strategy to reduce N2O emissions
0,0
0,5
1,0
1,5
2,0
2,5
3,0
3,5
4,0
CAN Urea Urea + Agrotain Urea + DCD Urea + Agrotain +DCD
N2O
-N E
mis
sion
Fac
tor (
%)
2011 2012 2013 2014
YearFertiliser Form 2011 2012 2013 2014 Average
CAN 0.46 3.50 3.82 1.69 2.37Urea 0.54 0.67 0.53 0.72 0.62
Urea + n-BTPT 0.47 0.29 0.40 0.41 0.39
Urea + n-BTPT + DCD 0.09 - 0.11 0.20 0.13Urea + DCD 0.26 - 0.25 0.35 0.29
Direct & indirect N2O EFs at Hillsborough
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Dry-matter yield (t ha-1)
4
6
8
10
12
14
16
2011 2012 2013 2014
Dry-
mat
ter y
ield
(t h
a-1 )
Control CAN Urea
Urea + Agrotain Urea + DCD Urea + Agrotain + DCD
Impact: Stabilised urea is now commercially available in the UK and Ireland as an alternative to CAN & is cheaper
Replacing CAN with urea + urease inhibitor is a potential mitigation strategy to reduce N2O emissions under Irish conditions, whilst maintaining grass production
Strategy to reduce N2O emissions
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NrecNlab
NH4+ads
NH4+ NO3-
MNrecMNlab ONrec
ONH4
DNO3
INO3INH4Nlab
RNH4a
INH4Nrec
ANH4
15N Tracing Model 5 soil N PoolsNlab Labile soil organic NNrec Recalcitrant soil organic NNH4+ AmmoniumNO3- NitrateNH4+ads Adsorbed ammonium
(Müller et al., 2007)
Impact: Providing insights into the effect of inhibitors on soil N transformations
Isotope ratio mass spectrometer
Use of 15N stable isotopes
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0
20
40
60
80
100
120To
tal N
Upt
ake
(kg
ha-1
)Total N uptake (kg ha-1)
50,7
56,9
49,0
56,5
30354045505560
Perc
enta
ge (%
)
Herbage 15N % recovery
15N field Micro-plot study
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Controlling phosphorus losses in Northern Ireland
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0 50 100 150
Neagh
Upper Erne
DergSheelin
Macnean
EnnellCorrib
Mask
Conn
Total Phosphorus (ug P l-1)
OECD eutrophic lakes limit
P concentrations of Irish lakes
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74% of monitored lakes classed as eutrophic or hypertrophic.– Lough Neagh is hypertrophic
– Lough Erne is eutrophic
Lough Neagh386 km2
Upper and Lower Lough Erne140 km2
Impact of excess nutrients on water quality
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Challenge: Reducing high P status soils
Impact of high soil P?
Courtesy of NIEA
32% at good status or better
17
-
Year1/1/05 1/7/05 1/1/06 1/7/06 1/1/07 1/7/07 1/1/08 1/7/08 1/1/09 1/7/09 1/1/10
Olse
n P
(mg/
l)
0
10
20
30
40
50
60
70
80
0 kg P/ha/yr40 kg P/ha/yr80 kg P/ha/yr
Research Impact• 13 years for Index 4 soil to decline to Index 2 at a P balance of -8
kg P/ha/yr, under grazing management• P balance of -8 kg P/ha/yr is not compatible with intensive dairy
farming
Index 2
Curtailing phosphorus fertiliser applications Leads to a decline in soil P status
kg P/ha/yr previously
applied
Annual rate of decline in Olsen P (mgP/L/year)
10 -0.7720 -1.3840 -1.8080 -4.40
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Experimental site at AFBI Hillsborough measures nutrient losses to water from six 0.2 ha grassland plots
Plots are hydrologically isolated and continuously monitored for a range of parameters:
– drain-flow– surface runoff– hourly rainfall at site
Annual decline = 99 µg P/L/year
Curtailing phosphorus fertiliser applications Leads to a decline in P concentrations in runoff
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• Manure from dairy cows fed with variable P diets
– produced high P (1.3%P) and low P (0.5%P) manures
• Rainfall simulation studies were undertaken to determine the impact of manure spreading on:
– TP concentrations in runoff
– Persistence of the P signal after manure application
• A rainfall simulator was used for a standard & reproducible rainfall event
– High intensity rain 40 mm/hour for 30 minutes
– Results in infiltration excess surface runoff
• Standard slurry application of 50 m3/ha
Reducing dietary P on total P losses in runoff following manure application
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Summer(Start 1 May)
0
5
10
15
2 9 32 54Days from manure application
TP in
runo
ff (m
g P
L-1 )
Slurry 1.3 % PSlurry 0.5 %PControl
Autumn(Start 29 October)
0
5
10
15
2 9 32 54Days from manure application
TP in
runo
ff (m
g P
L-1 )
Slurry 1.3 % PSlurry 0.5 %PControl
Spring(Start 17 March)
0
5
10
15
2 9 32 54Days from manure application
TP in
runo
ff (m
g P
L-1 )
Slurry 1.3 % PSlurry 0.5 %PControl
• Two days after slurry applications very high P concentrations were measured in runoff.
• Persistence of P signal was less in summer than in autumn – In autumn slurry effect evident > 9 days after application
• Avoiding runoff has benefits as great as or better than lowering manure P.
Reducing dietary P on total P losses in runoff following manure application
High P (1.3% P) vs low P (0.5% P) manure
O’Rourke et al. (2010) J. Environ Qual. 39: 2138-2146
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Total P inputs to wetland and exports from ponds 1-5
March 2006 - February 2007
7360
4534
14
168
0
50
100
150
200
INFLOW(100%)
POND 1(57%)
POND 2(64%)
POND 3(73%)
POND 4(80%)
POND 5(92%)
% values are wetland reduction of TP relative to iinput at inflow
Total
P (k
g P ye
ar-1 )
The Wetland designed and scaled to treat dirty water from 180 dairy cows containing:
– Parlour washings
– Winter runoff from unroofed grass silage pits
– Dirty water runoff from lightly contaminated livestock yards
Research has shown:
• Pollutant removals > 95% - Biochemical Oxygen Demand (BOD) > 99%.
• Virtually 100% treatment efficiency in summer.
– high plant evaporation ensures very little discharge from May to October
• Winter phosphorus retention (82% to 95%) – least in February.
Greenmount Constructed Wetland
Managing dirty water
Chart5
INFLOW (100%)
POND 1 (57%)
POND 2 (64%)
POND 3 (73%)
POND 4 (80%)
POND 5 (92%)
% values are wetland reduction of TP relative to iinput at inflow
Total P (kg P year-1)
Total P inputs to wetland and exports from ponds 1-5 March 2006 - February 2007
168.0304255517
72.7053730044
59.9814186497
45.3882479515
33.577386303
13.5649366704
Sheet1
Wetland
Wetland area1.25ha
Contributing area0.66ha
Ratio ratio0.528
Rainfall March 2006-February 2007961mm
% of long term average107% of long term average
TP
Inflow 100%POND 1POND 2POND 3POND 4POND 5flow from yard
Mar-061095011250705064005625967748.54520132Mar-06
Apr-06116956667424028503703311145.8Apr-06
May-0681201111366072700178582349.661001188May-06
Jun-06433601500725804774577789.548200132Jun-06
Jul-0653733186334273668594103367.540400066Jul-06
Aug-066965017285107281451452196281.199201386Aug-06
Sep-06289671063312107419846469338.30220132Sep-06
Oct-0636600151351145540802880158585.683600726Oct-06
Nov-063312015254996267822618974764.134200132Nov-06
Dec-061815092357595822863502112445.083801386Dec-06
Jan-073807890148591807044452601630.913404884Jan-07
Feb-0751201121578725667040122281457.530800198Feb-07
Mar-076255112238967959753070581459.947Mar-07
averageV notchPOND 1POND 2POND 3POND 4POND 5145.1994Apr-07
mean3363512615782643812782827231.5276May-07
INFLOW (100%)POND 1 (62%)POND 2 (77%)POND 3 (87%)POND 4 (92%)POND 5 (97.5%)1137.021Jun-07
33.635354166712.61522361117.82597222224.38102777782.78205138890.8274541667514.4234Jul-07
100.06277879298753.2642Aug-07
217.5156Sep-07
Oct-07
Nov-07
Dec-07
Pond water balances (cummulative)
m3m3m3m3m3m3
Flow from yard(total)Pond 1 balancePond 2 balancePond 3 balancePond 4 balancePond 5 balancepond 1pond 2pond 3pond 4pond 5
158.175000198Nov-05195.9480232654219.7559643078260.1369243798312.8004264737368.3242465727Nov-05Nov-05195.9480232654219.7559643078260.1369243798312.8004264737368.3242465727
634.642401386Dec-05845.3958178574978.23149015461203.53581065861497.37019531591807.163636008938687Dec-05845.3958178574978.23149015461203.53581065861497.37019531591807.1636360089
246.423800132Jan-06307.4995782367345.9950018528411.2875931452496.4400142889586.217327315938718Jan-06307.4995782367345.9950018528411.2875931452496.4400142889586.2173273159
269.820200396Feb-06315.5538283818344.3792553752393.270438968457.0326909038524.25806834438749Feb-06315.5538283818344.3792553752393.270438968457.0326909038524.258068344
748.54520132Mar-06933.69287755821050.38951981971248.32022047531506.45484258021778.609555981638777Mar-06933.69287755821050.38951981971248.32022047531506.45484258021778.6095559816
145.8Apr-06118.5178770477101.322240532172.156496618834.1195055984-5.983392282438808Apr-06118.5178770477101.322240532172.156496618834.11950559840
349.661001188May-06331.8246635456320.5826066352301.5148069284276.6472181441250.428993547338838May-06331.8246635456320.5826066352301.5148069284276.6472181441244.4456012649
89.548200132Jun-06-100.5998726295-220.4482124769-423.7245486139-688.8307703259-968.335732514238869Jun-0600000
367.540400066Jul-06246.6949268328170.527290028841.3383654143-127.1455237705-304.780295115538899Jul-06146.09505420330900
281.199201386Aug-06272.5180036339267.0463355629257.7657678101245.6623606991232.90158003938930Aug-06272.5180036339217.1254131149000
338.30220132Sep-06410.7875514611456.4743088998533.9642155094635.0239687129741.572590301238961Sep-06410.7875514611673.5997220146409.343800119964.71003531560
585.683600726Oct-06719.5584793876803.9384140451947.05632441831133.705932531330.493059293238991Oct-06719.5584793876803.9384140451947.05632441831133.705932531031.8512020036
764.134200132Nov-06991.04001654681134.05637744971376.62829700221692.9825087522026.518898136839022Nov-06991.04001654681134.05637744971376.62829700221692.9825087522026.5188981368
445.083801386Dec-06588.319281611678.5991054499831.7238951031.42414137161241.970727002939052Dec-06588.319281611678.5991054499831.7238951031.42414137161241.9707270029
630.913404884Jan-07830.1534794527955.73241286681168.72848367521446.51085935441739.38045671639083Jan-07830.1534794527955.73241286681168.72848367521446.51085935441739.380456716
457.530800198Feb-07575.7407523629650.2472478254776.6186888925941.42810995091115.188841418239114Feb-07575.7407523629650.2472478254776.6186888925941.42810995091115.1888414182
459.947Mar-07514.5307602369548.9343329474607.2866824211683.3878715265763.622352052839142Mar-07514.5307602369548.9343329474607.2866824211683.3878715265763.6223520528
145.1994Apr-07-26.0228915888-133.9425096726-316.9863848678-555.7061054349-807.391433828239173Apr-0700000
231.5276May-07132.330183479769.8070902163-36.2391457074-174.5411117246-320.354686119739203May-07106.30729189090000
1137.021Jun-071405.8987521221575.36958475131862.81127967012237.68315679352632.915487306939234Jun-071405.8987521221511.23416529491509.58574909491507.4359396341505.169367359
514.4234Jul-07588.4434633675635.0975344878714.2281144798817.4275792193926.232126708339264Jul-07
753.2642Aug-07905.08539306141000.77670182841163.07998171591374.75050923581597.917519081139295Aug-07
217.5156Sep-07183.0071942836161.2569073844124.36596140776.254019361425.528968642439326Sep-07
Oct-0739356Oct-07
Nov-0739387Nov-07
Dec-07Dec-07
INFLOW (100%)POND 1 (114%)POND 2 (122%)POND 3 (137%)POND 4 (156%)POND 5 (176%)
520459186368713281289178
100.0113.7122.4137.1156.2176.4
concs
InletPOND 1POND 2POND 3POND 4POND 5loadsPOND 1POND 2POND 3POND 4POND 5
Feb-0650073.33333333331481011566.66666666678276.66666666672685102Feb-0613.54.74.03.31.20.1
Mar-061095011250705064005625966.6666666667Mar-068.210.57.48.08.51.7
Apr-06116956666.6666666667424028503702.5310.5Apr-061.70.80.40.20.10.0
May-06812011113.33333333336606.666666666727001785.333333333381.6666666667May-062.83.72.10.80.50.0
Jun-064336015006.66666666672580476.6666666667457.333333333377.3333333333Jun-063.90.00.00.00.00.0
Jul-0653733.333333333318633.33333333334273.3333333333668594103Jul-0619.72.70.00.00.00.0
Aug-06696501728510727.51450.5451.75196.25Aug-0619.64.72.30.00.00.0
Sep-0628966.666666666710633.333333333312106.66666666674197.666666666746469.3333333333Sep-069.84.48.21.70.00.0
Oct-063660015135114554079.752879.5158Oct-0621.410.99.23.93.30.2
Nov-063312015254996267822618973.6Nov-0625.315.111.39.34.42.0
Dec-061815092357595822863502111.5Dec-068.15.45.26.86.52.6
Jan-07380789013.6859180704445.22600.6Jan-0724.07.58.29.46.44.5
Feb-0751201.2512156.758724.56669.7540122281Feb-0723.47.05.75.23.82.5
Mar-0762550.512237.596795974.753070581.25Mar-0728.86.35.33.62.10.4
Apr-0710232011994711974432200904Apr-0714.90.00.00.00.00.0
INFLOW (100%)POND 1 (57%)POND 2 (64%)POND 3 (73%)POND 4 (80%)POND 5 (92%)
40362415138393912525723338599291687360453414
100.090092.455889.731287.419868.25909.3100.056.764.373.080.091.9
Inlet
Feb-0650073.3333333333TPFlow
1095010950967Mar-0611778.6095559816
1169511695311Apr-0600
8120812082May-060244.4456012649
433604336077Jun-0600
53733.333333333353733103Jul-0600
6965069650196Aug-0600
28966.66666666672896769Sep-0600
3660036600158Oct-0601031.8512020036
3312033120974Nov-0612026.5188981368
18150181502112Dec-0621241.9707270029
38078380782601Jan-0731739.380456716
51201.25512012281Feb-0721115.1888414182
62550.562551581Mar-071763.6223520528
102320904Apr-0710
0
1505.169367359
Sheet1
% values are wetland reduction of TP relative to inflow
Total P (mg P L-1)
Mean concentrations (Mar 2006- Feb 2007) of total P in inflow to wetland and at point of outflow from each pond
volume 3
% values are wetland reduction of TP relative to inflow
Volumes (m3 year-1)
Inflows to wetland and flows from each pond for 12 months March 2006 - February 2007
summary (2)
&A
Page &P
TP
Flow
TP concentration (mg P L-1)
Outfow volume (m3 month-1)
Monthly changes in outflow TP concentration and flow from Pond 5
% values are wetland reduction of TP relative to iinput at inflow
Total P (kg P year-1)
Total P inputs to wetland and exports from each pond for 12 months March 2006 - February 2007
% values are wetland reduction of TP relative to inflow
Total P (mg P L-1)
Mean concentrations (Mar 2006- Feb 2007) of total P in inflow to wetland and at point of outflow from each pond
% values flow from pond relative to wetland inflow
Volumes (m3 year-1)
Inflows to wetland and flows from each pond for 12 months March 2006 - February 2007
evap correction for Penman Moncreiff1.2
mmmmmmmmmm
pTwet daysMonthrainfallevaporationrunoff potentailcumulative deficitWetlevel deficit
Nov-05720Nov-0525-8.0516.830.00
Dec-05423Dec-0598-4.3993.880.00
Jan-06716Jan-0636-8.7427.210.00
Feb-061716Feb-0640-20.0320.370.00
Mar-062722Mar-06115-32.5582.470.00
Apr-065923Apr-0659-71.15-12.15-12.150
May-067620May-0684-91.53-7.94-20.10-26
Jun-069110Jun-0624-109.18-84.70-104.80-81
Jul-0610211Jul-0668-122.12-53.83-158.62-180
Aug-066822Aug-0677-81.08-3.87-162.49-84
Sep-064522Sep-0686-53.8832.29-130.2034
Oct-062622Oct-0690-30.7159.63-70.57787.2
Nov-061218Nov-06116-14.62101.0730.50
Dec-06626Dec-0671-7.2463.800.00
Jan-07927Jan-07100-10.9588.750.00
Feb-071520Feb-0771-18.1852.650.00
Mar-073820Mar-0770-45.9824.310.00
Apr-07788Apr-0717-93.18-76.27-76.27
May-079019May-0764-107.87-44.19-120.45
Jun-076618Jun-07199-79.42119.77-0.69
Jul-077024Jul-07117-83.5832.970.00
Aug-075615Aug-07135-67.1167.630.00
Sep-0740.614356242219Sep-0733-48.74-15.37-15.37
Oct-07
Nov-07
Dec-07
931
9 Total200733.36612440.614356242233.366
m3/day
pondPond 1Pond 2Pond 3Pond 4Pond 5WetlandYard areaparlour wash
areas224514152400313033001249066002
2245366060609190124902500200.1601281025
-1000-80.064051241
Wetland water balancewinter yard evap0.5(mm/day with rain)-2000-160.128102482
summer yard evap2(mm/day with rain)-2500-200.1601281025
values/monthmmmmmmm3m3m3m3m3mmmm
days in monthrainfallwet daysyard evapYard runoffWetland net rainParlour inputWater balancedeficitswater balanceMeasuredWater balancePond level
30Nov-05252010982106036829Nov-05368Nov-05368
31Dec-05982311.55731173621807145Dec-051807Dec-051807
31Jan-06361681843406258647Jan-06586Jan-06586
28Feb-06401682142545652442Feb-06524Feb-06524
31Mar-0611522116871030621779142Mar-061779Mar-061779
30Apr-0659234686-15260-6-6-00Apr-06-60Apr-06-6
31May-06842040288-996224420-26May-06244-25.8246597278May-06244
30Jun-0624102030-105860-968-968-78-81Jun-06-968-80.7205764612Jun-06-968
31Jul-06681122306-67262-305-1273-102-180Jul-06-1273-180.0520416333Jul-06-1273
31Aug-06772244219-4862233-1040-83-84Aug-06-1040-84.1321056845Aug-06-1040
30Sep-0686224427840360742-299-2434425.95425.95Sep-06-29934.1032826261Sep-06-725
31Oct-069022115247456210328378978552.05Oct-06103278.3026421137Oct-06480
30Nov-061161897041262602027162Nov-062027Nov-062027
31Dec-0671261338379762124299Dec-061242Dec-061242
31Jan-071002713.55691108621739139Jan-071739Jan-071739
28Feb-0771201040265856111589Feb-071115Feb-071115
31Mar-077020103983046276461Mar-07764Mar-07764
30Apr-07178485-95360-807-807-65Apr-07-807Apr-07-807
31May-07641938170-55262-320-1128-90May-07-1128May-07-1128
30Jun-07199183610771496601505121Jun-071505Jun-071505
31Jul-0711724484524126292674Jul-07926Jul-07926
31Aug-071351530691845621598128Aug-071598Aug-071598
30Sep-0733199.5158-1926026262Sep-0726Sep-0726
Oct-07Oct-07
11613183215543595197012159Volume (Feb-Jan)5587-32828869hyrdaulic loading
0.9727442649end of month levelsAverage deficit mmmm/yearpond vlume
961
38817710.05817351433747
Pond water balances (cummulative)Pond level predictions not cummulative38868
m3m3m3m3m3m3mmmmmmmmmm38895
Flow from yard(total)Pond 1 balancePond 2 balancePond 3 balancePond 4 balancePond 5 balancePond 1Pond 2Pond 3Pond 4Pond 538925
158Nov-05196220260313368Nov-05876043342938953
635Dec-05845978120414971807Dec-0537726719916314538987
246Jan-06307346411496586Jan-061379568544739023
270Feb-06316344393457524Feb-0614194655042
749Mar-069341050124815061779Mar-06416287206164142Pond 1Pond 2Pond 3Pond 4Pond 5
146Apr-061191017234-6Apr-065328124-000000
350May-06332321302277250May-061488850302000-20-35-50
90Jun-06-101-220-424-689-968Jun-06-45-60-70-75-7800-100-140-100
368Jul-0624717141-127-305Jul-06110477-14-24-67-23-262-243-205
281Aug-06273267258246233Aug-06121734327198625-182-172
338Sep-06411456534635742Sep-0618312588695900011520
586Oct-0672080494711341330Oct-063212201561231070040150125
764Nov-069911134137716932027Nov-06441310227184162
445Dec-0658867983210311242Dec-0626218513711299
631Jan-07830956116914471739Jan-07370261193157139
458Feb-075766507779411115Feb-0725617812810289
460Mar-07515549607683764Mar-072291501007461
145Apr-07-26-134-317-556-807Apr-07-12-37-52-60-65
232May-0713270-36-175-320May-075919-6-19-26
1137Jun-0714061575186322382633Jun-07626430307243211
514Jul-07588635714817926Jul-072621741188974
753Aug-079051001116313751598Aug-07403273192150128
218Sep-071831611247626Sep-0782442182
Oct-07Oct-07
Nov-07Nov-07
Dec-07
Pond 1Pond 2Pond 3Pond 4Pond 5
Apr-0600
May-0600
Jun-06-450
Jul-060-67
Aug-0608
Sep-0600
Oct-0600
Apr-0600
May-0600
Jun-06-600
Jul-060-23
2007Aug-0606
129.25.410094Sep-0600
86.613.57157Oct-0600
81.330.765.0434Apr-0600
28.852.023.04-29May-060-20
71.479.357.12-22Jun-06-70-100
154.588.7123.635Jul-06-63-262
124.187.599.2812Aug-06025
98.170.178.488Sep-0600
58.443.546.723Oct-06040
22.4Apr-0600
6.7May-060-35
3.7Jun-06-75-140
5.4Jul-06-89-243
13.5Aug-06-62-182
Sep-0600
Oct-060-0
Apr-060-50
May-060-100
Jun-06-78-205
Jul-06-102-172
Aug-06-8320
Sep-060125
Oct-060
gregs low water inflows
4471
3983
4498
3612
3569
Forgot to add these figures I had from the outflow;
1st - 15th Nov 06- 449,566lt- 449.57m3/14 = 32.11m3/day.
I'm trying to get some more.
rainfall
evaporation
mm month-1
Monthly rainfall and and potential evaporation losses
&A
Page &P
Water balance
Pond level
Water balance (m3 month-1)
Pond level (mm)
Pond 1
Pond 2
Pond 3
Pond 4
Pond 5
rainfall
evaporation
mm month-1
Monthly rainfall and and potential evaporation losses
Water balance
Pond level
Water balance (m3 month-1)
Pond level (mm)
Water balance
Pond level
Water balance (m3 month-1)
Pond level (mm)
Monthly water balances for wetland and changes in pond level
Water conductivityFDC dirty water BOD results (mg/l)
µg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/lµg/l1aD1D2C1
CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5V notchPOND 1POND 2POND 3POND 4POND 5DateDairy walkwayDairy unit 1Dairy unit 2Cream unit 1V notchP1P2P3P4P5112
sample dateCONDCONDCONDCONDCONDCONDPHPHPHPHPHPHsample dateSRPSRPSRPSRPSRPSRPsample dateTSPTSPTSPTSPTSPTSPsample dateTPTPTPTPTPTPsample dateTONTONTONTONTONTONNO2NO2NO2NO2NO2NO2
5-Apr-051432638.749.045-Apr-05"1.1115-Apr-053.6295-Apr-056475-Apr-055-Apr-05
11-Sep-051112452851992017.838.438.638.478.0111-Sep-05151916222011-Sep-05252947462711-Sep-0575861055411-Sep-0511-Sep-05
3-Nov-053-Nov-053-Nov-053-Nov-053-Nov-053-Nov-053-Nov-05387.55.6
10-Nov-0510-Nov-0510-Nov-0510-Nov-0510-Nov-0510-Nov-0510-Nov-053,6005925,63097231026051.4127
23-Nov-0523-Nov-0523-Nov-0523-Nov-0523-Nov-0523-Nov-0523-Nov-051,1105,7706621,0401,180341.4
30-Nov-0530-Nov-0530-Nov-0530-Nov-0530-Nov-0530-Nov-0530-Nov-05381.7701.7
8-Dec-05194240327117520238376.646.586.946.856.838-Dec-05164367534733358-Dec-052404466610352638-Dec-052033771881158-Dec-058-Dec-057-Dec-05703954,5502,6201,610147220.834
15-Dec-0515-Dec-0515-Dec-0515-Dec-0515-Dec-0515-Dec-0515-Dec-05701,2703,6501,3052,560141622.5
4-Jan-064-Jan-064-Jan-064-Jan-064-Jan-064-Jan-064-Jan-063525,0002826901197.3
11-Jan-0611-Jan-0611-Jan-0611-Jan-0611-Jan-0611-Jan-0611-Jan-06789409774214124
18-Jan-0618-Jan-0618-Jan-0618-Jan-0618-Jan-0618-Jan-0618-Jan-065317193,4301,4401,18022541101031
25-Jan-0625-Jan-0625-Jan-0625-Jan-0625-Jan-0625-Jan-0625-Jan-061431831,6401,3802541323011751
1-Feb-061-Feb-061-Feb-061-Feb-061-Feb-061-Feb-061-Feb-067.9
8-Feb-069664155744113336.696.736.777.227.78-Feb-061064050805080340308-Feb-065560544096266201008-Feb-06632052001473017951558-Feb-060.840.10.060.110.08124731028-Feb-06
15-Feb-0610255383152502502556.917.26.846.737.027.4815-Feb-0616040207603600430061208715-Feb-0616920210404280138002816012315-Feb-06150001312023600270040605915-Feb-061.140.050.050.050.040.36170151612114015-Feb-06
22-Feb-066596183124373322847.027.87.367.717.878.2922-Feb-061157001280050005500545422-Feb-06114800137005600580019007522-Feb-06128900165005900740022009222-Feb-061.310.510.10.080.070.115131312101022-Feb-06
2-Mar-0614365732884593082467.736.816.576.866.918.412-Mar-06128001280042006400160013002-Mar-068000133004200680013009002-Mar-0690001490046007800470011002-Mar-061.40.30.060.070.060.051819171614132-Mar-061-Mar-06992135208981
8-Mar-068-Mar-068-Mar-068-Mar-068-Mar-068-Mar-068-Mar-065082251,4301,560451281488518
16-Mar-064082352242542881567.567.287.32"2.597.488.0716-Mar-065000550053006800530060016-Mar-06150005600600054003100100016-Mar-0615000760068007500500090016-Mar-064.660.330.170.120.170.11472929189416-Mar-06
22-Mar-062563951972481547.787.197.367.388.0222-Mar-06100036002900290020022-Mar-06600066003600340080022-Mar-061700090004400490090022-Mar-065.790.120.10.070.080.0316215151213622-Mar-0622-Mar-061325721561
29-Mar-063763293183343158.747.727.87.647.6229-Mar-061700650061005200420029-Mar-0620006500610053004400130029-Mar-06280078005900790029-Mar-063.20.20.070.090.088914108729-Mar-0629-Mar-0636479208073318326262654092
5-Apr-063504102442652461997.918.018.017.287.267.945-Apr-061100046004600500027006005-Apr-06500066005600750054006005-Apr-06900056005600620049009005-Apr-065.20.10.070.060.070.05161786545-Apr-06
12-Apr-062572461841841681486.917.517.427.297.268.2812-Apr-06106408040215011204401012-Apr-0610980776021801480100016012-Apr-0614260806015401300713016012-Apr-062.060.360.220.150.080.031111012761012-Apr-0612-Apr-06836155117200361064
19-Apr-0619-Apr-06800068002520130042013019-Apr-06898064005590"1149036012019-Apr-06126606340272013205809019-Apr-061.770.180.220.140.080.06165121157719-Apr-0619-Apr-061293449602717742
26-Apr-06274155117110997.687.747.927.888.2626-Apr-0650003860172024803526-Apr-0699405720264038207326-Apr-06108607100258022009226-Apr-060.050.160.110.10.07612912526-Apr-06
3-May-0628320485143109999.487.867.787.817.968.173-May-06592014780146020803-May-061006015740214030202040703-May-0612200105402420342028201103-May-061.40.20.240.200.180.022462431171893-May-063-May-0641854211977211152
10-May-064483042292582072047.567.027.067.156.837.9610-May-061132034201460208014603110-May-068440173204800240013604910-May-068440116005920320018804810-May-060.450.220.090.070.070.051331414712710-May-0610-May-0685949744257165584
17-May-0617-May-062880714034201740900917-May-0659358520948010802006217-May-063720112001148014806568717-May-0617-May-0617-May-0610185394032746.819.07.64.1
24-May-0624-May-0624-May-0624-May-0624-May-0624-May-0624-May-06192852126883.72.83.00.2
31-May-0631-May-0631-May-0631-May-0631-May-0631-May-0631-May-0626853117043313.78.512.41.0
7-Jun-067-Jun-067-Jun-067-Jun-067-Jun-067-Jun-067-Jun-0655476613550.730.620.117.37.05
15-Jun-067584882312842907.136.666.726.967.5315-Jun-061114018803904155315-Jun-061176023205224909715-Jun-0613920288054473710015-Jun-069.310.110.160.070.050.07101485715-Jun-0615-Jun-066668.04.4
22-Jun-063046744944943113046.167.17.427.67.67.822-Jun-06832025805742034322-Jun-06280001228028005792718222-Jun-06298801536034805574597722-Jun-060.830.140.170.020.0284382471322-Jun-0622-Jun-0676117635.63.9
29-Jun-069818374993082873096.936.646.786.837.197.7129-Jun-0639320132001240228752029-Jun-06492001318016802681135429-Jun-06568401574013803291765529-Jun-060.130.020.020.02157751510929-Jun-0629-Jun-0682211309.15.7
6-Jul-0614262545322942962657.038.376.746.797.027.626-Jul-0644500113003620261243296-Jul-0649400146604100329293646-Jul-06585001736041004565811026-Jul-066-Jul-06
19-Jul-0680911695613554192767.357.486.646.86.647.5219-Jul-0635100015780610021426211619-Jul-0638200015440662028935716619-Jul-06478001936052005406417919-Jul-0619-Jul-0619-Jul-0611112497
26-Jul-0666112956364343223046.88.478.138.328.298.3926-Jul-06496501418028404963308726-Jul-064725014140326056143813126-Jul-0654900191803520100856012826-Jul-0626-Jul-0626-Jul-06871951310.4
3-Aug-067319956084773483158.718.2488.298.148.483-Aug-064450073401875913397473-Aug-0663700892017809004533983-Aug-0673000864018009694493793-Aug-063-Aug-062-Aug-0667015776.25.1
10-Aug-0612337836864862923146.628.687.917.957.71810-Aug-0614500694018303273594310-Aug-0635500938068608643868110-Aug-0694500107607220108343913210-Aug-0610-Aug-0610-Aug-06550160715.37.9
16-Aug-0613107364874752813074.296.988.037.957.88.1516-Aug-062764013220788015701674516-Aug-065980014640838017922677516-Aug-06694001542020470184359011816-Aug-0616-Aug-0616-Aug-06282027038.25.0
24-Aug-0612706136114192302276.676.967.117.27.357.624-Aug-0632600160401242018753634024-Aug-0637200166001302020185106724-Aug-06417003432013420190732915624-Aug-0624-Aug-0623-Aug-0689016025.94.3
30-Aug-069516907796112312806.247.287.487.567.67.8930-Aug-0630-Aug-0630-Aug-0630-Aug-0630-Aug-0630-Aug-0657017105.53.5
6-Sep-0611046386206532262737.38.347.957.918.088.126-Sep-06222009000118602423245796-Sep-0629800101801260024654041006-Sep-063630010860134803234258796-Sep-066-Sep-066-Sep-061004152092.97
13-Sep-069536816567252662846.298.237.727.717.588.2113-Sep-0623709103601172022864563913-Sep-0629600107201224033655635113-Sep-0641700110801112044733646613-Sep-0613-Sep-0613-Sep-06127121343.53
20-Sep-067515526457052632897.927.987.757.747.78.2320-Sep-0628626384920-Sep-06530088201210033465305420-Sep-06890099601172048867706320-Sep-0620-Sep-06
27-Sep-067786565536224382536.267.897.667.767.798.0427-Sep-0627-Sep-0627-Sep-0627-Sep-0627-Sep-06
4-Oct-0610196446365955232877.466.76.756.957.057.434-Oct-0631732583244-Oct-0646400145801322034172752704-Oct-06489001374012740402432281134-Oct-064-Oct-06
11-Oct-0610147096155684343265.937.347.247.627.517.8211-Oct-06346025102311-Oct-06184001340011060360027656211-Oct-061870013720111004195282020411-Oct-0611-Oct-06
18-Oct-0618-Oct-063900248014218-Oct-063180013280113204320274018918-Oct-063930016300106604590295013518-Oct-0618-Oct-06
25-Oct-06106081960654234437996.7777.036.997.3525-Oct-062940186020625-Oct-062580014700106202840194026425-Oct-063950016780113203510252018025-Oct-0625-Oct-06
1-Nov-069189315714823043708.166.736.966.896.757.131-Nov-06301016902811-Nov-06396001740011240323017903471-Nov-06435001852010760379019304111-Nov-061-Nov-06
8-Nov-0610656555233804206.357.737.637.57.898-Nov-06514028403088-Nov-06305001875010650552030803748-Nov-0640200159009900604033803158-Nov-068-Nov-06
16-Nov-0616-Nov-06610080060016-Nov-064260015350101506000295080016-Nov-065890014700151506750335075016-Nov-0616-Nov-06
22-Nov-067357855015692733158.737.147.227.187.057.2322-Nov-067700216043722-Nov-06100001585063506300235066722-Nov-06990017000565082502170120022-Nov-0622-Nov-06
29-Nov-069008857356154804208.127.247.137.257.387.1229-Nov-067140196090229-Nov-069400915085508080212099229-Nov-061310010150835090802260219229-Nov-0629-Nov-06
6-Dec-063480306011486-Dec-0617700685041003608324012666-Dec-061800098506750453638001938
13-Dec-0610458156754023503898.147.127.247.057.387.4213-Dec-0635282780182513-Dec-06153007760802028602800191013-Dec-061830086208440119208900228513-Dec-0613-Dec-06
3-Jan-0774669162454639339877.827.788.197.557.883-Jan-077075389233733167.57493-Jan-0745566110217776727040929063-Jan-07532061134481657762543113803-Jan-073-Jan-07
10-Jan-07631713685"243353586.536.836.857.286.917.4310-Jan-076335299864010-Jan-073854911496106686906328383210-Jan-074679411145106347064501189910-Jan-0710-Jan-07
18-Jan-073666666515403063577.287.577.457.837.527.8918-Jan-075614267918-Jan-07106797288785557562752181518-Jan-07114178196900966782812258118-Jan-0718-Jan-07
24-Jan-076796386055964544207.738.718.548.548.518.5224-Jan-07698639392143.824-Jan-076310676873573933271024-Jan-07471556451752781574407418024-Jan-0724-Jan-07
31-Jan-076146115755623783857.46.766.927.087.357.2631-Jan-0773193639221931-Jan-07299727613721477113772236131-Jan-073181879327620106894565396331-Jan-0731-Jan-07
7-Feb-076007214626094094606.287.67.658.267.897.947-Feb-07368006294239818447-Feb-07120756785357806338240622767-Feb-0771353868360057841345333767-Feb-077-Feb-07
14-Feb-078347824355129384065.546.945.797.7914-Feb-0748561688146514-Feb-076864511638685852271785152914-Feb-078263012342627161843343229414-Feb-0714-Feb-07
21-Feb-076477176214643413425.856.937.017.367.317.3621-Feb-0742722995108921-Feb-079044814564972354753048109021-Feb-073307213962998858875788165421-Feb-0721-Feb-07
28-Feb-0728-Feb-0757823079115328-Feb-0711535782307911535782307928-Feb-0717750136401263467673464180028-Feb-0728-Feb-07
7-Mar-075036863984272803196.757.427.257.638.048.067-Mar-075389301412107-Mar-07452921245670065705306112827-Mar-07432021034973997739416814447-Mar-077-Mar-07
14-Mar-074706746174122983166.37.577.457.667.627.9214-Mar-073515164916114-Mar-075622310561104723878181918614-Mar-076433912082111515980226031414-Mar-0714-Mar-07
21-Mar-07432"175464"1563216.778.337.848.778.4921-Mar-072524.7530421-Mar-075918511234833832221-Mar-0743354124638127305536621-Mar-0721-Mar-07
28-Mar-0728-Mar-076961244915028-Mar-07747221565685848215113415128-Mar-079930714056120397125278220128-Mar-0728-Mar-07
4-Apr-074526074645402983166.727.967.247.557.627.574-Apr-07579414414254-Apr-07118869114184489627915435304-Apr-07158164126014966691218229724-Apr-074-Apr-07
18-Apr-074556616234072883217.027.827.337.457.527.8718-Apr-0718-Apr-073613210670102735716196352818-Apr-07464761138792727974257883618-Apr-0718-Apr-07
2-May-077555634864773143503.166.596.627.076.997.492-May-07485015007829231780677372950.8571
9-May-079535514874483623635.356.516.666.836.897.59-May-072302841513234300942252383321122880421854710508546255201712616
16-May-075975593293593353255.566.516.616.877.237.5116-May-072133903378826069332.5255310735269744610837.57382.534071894619
CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5V notchPOND 1POND 2POND 3POND 4POND 5DateDairy walkwayDairy unit 1Dairy unit 2Cream unit 1V notchP1P2P3P4P5112
sample dateCONDCONDCONDCONDCONDCONDPHPHPHPHPHPHsample dateSRPSRPSRPSRPSRPSRPsample dateTSPTSPTSPTSPTSPTSPsample dateTPTPTPTPTPTPsample dateTONTONTONTONTONTONNO2NO2NO2NO2NO2NO2
CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5CW REPORT DATA.V notchPOND 1POND 2POND 3POND 4POND 5V notchPOND 1POND 2POND 3POND 4POND 5DateDairy walkwayDairy unit 1Dairy unit 2Cream unit 1V notchP1P2P3P4P5112
sample dateCONDCONDCONDCONDCONDCONDPHPHPHPHPHPHsample dateSRPSRPSRPSRPSRPSRPsample dateTSPTSPTSPTSPTSPTSPsample dateTPTPTPTPTPTPsample dateTONTONTONTONTONTONNO2NO2NO2NO2NO2NO2
mean7536705144503273007.167.497.407.467.517.87mean346229703451735321847503mean3990811500732438542061667mean3664012794817046782847853mean3000001192116101010meanAverage7086963,6871,1369432388419158460
min25620485117109994.296.646.575.796.647.12min100034201240214759min11535600168026811349min28005600138032917648min000000677352minmedian366293,6501,1397281385414108434
max143612957797259384609.488.718.548.548.778.52max3510001604012420770053002219max3820001875013220821557823079max9930734320204701192089004180max9100002467531181840maxmax36002,8205,7702,6202,7031,18043365551710127
min36871,430282124605433018
1/7/007.47
AverageminmaxAverageminmaxAverageminmaxAverageminmaxAverageminmax% reductionAverageminmaxAverageminmaxAverageminmax
Vnotch7532561436Vnotch7.164.299.48Vnotch346221000351000Vnotch399081153382000Vnotch36640280099307Vnotch2.6270.0509.310Vnotch1196246Vnotch9437282703
P16702041295P17.496.648.71P19703342016040P111500560018750P11279456003432065.08P10.2110.0500.510P121775P12381381180
P251485779P27.406.578.54P24517124012420P27324168013220P2817013802047077.70P20.1250.0200.240P216731P28453.85432.5
P3450117725P37.465.798.54P335322147700P338542688215P346783291192087.23P30.0860.0200.200P310318P31914.165
P4327109938P47.516.648.77P41847755300P420611135782P42847176890092.23P40.0800.0200.180P410518P4159.9755
P530099460P57.877.128.52P550392219P5667493079P585348418097.67P50.0820.0200.360P510240P587.617.3
%%
CONDCONDCONDCONDCONDCOND
V notchPOND 1POND 2POND 3POND 4POND 5
Nov-050000000.000.000.000.000.000.00Nov-05000000Nov-05000000Nov-0500000016-Nov-05
Dec-0519424032711752023837.006.646.586.946.856.83Dec-0516436753473335Dec-05240446661035263Dec-05203037718811511-Dec-05
Jan-060000000.000.000.000.000.000.00Jan-06000000Jan-06000000Jan-0600000014-Jan-06
Feb-068835783474203312916.877.506.987.077.377.82Feb-06474601678045604960217157Feb-064576017370510797421022799Feb-065007314810115678277268510211-Feb-06
Mar-066193793063112901857.957.277.227.297.358.17Mar-0651258267480053253500700Mar-06775084675725527530501000Mar-06109501125070506400562596715-Mar-06
Apr-062943281941891751497.507.767.727.507.478.16Apr-0686606480328322851510194Apr-0687256920477338732645238Apr-0611695666742402850370331115-Apr-06
May-063662541572011581528.527.447.427.487.408.07May-066707844721131967118020May-0681451386054732167120060May-068120111136607270017858217-May-06
Jun-066437564943442943016.556.966.957.057.257.68Jun-063932010887190039723139Jun-063860012407226745629178Jun-06433601500725804774577718-Jun-06
Jul-069659065763613462827.068.117.177.307.327.84Jul-0614838313753418732427877Jul-06159550147474660393363120Jul-065373318633427366859410317-Jul-06
Aug-0610997636344942762896.517.637.717.797.728.02Aug-0629810108856001117132244Aug-06490501238575101394404155Aug-06696501728510728145145219616-Aug-06
Sep-068976326196762982756.948.117.777.787.798.15Sep-0622955968011790252444656Sep-0621567990712313305949968Sep-0628967106331210741984646916-Sep-06
Oct-0610317246195684343317.326.946.997.207.187.53Oct-060003368235899Oct-0630600139901155535442549146Oct-063660015135114554080288015814-Oct-06
Nov-069058676165473593817.847.047.267.247.177.34Nov-0600058181890506Nov-062642015300938858262458636Nov-06331201525499626782261897415-Nov-06
Dec-0610458156754023503898.147.127.247.057.387.42Dec-06000350429201487Dec-061650073056060323430201588Dec-06181509235759582286350211213-Dec-06
Jan-076076646285613733847.197.547.517.787.577.80Jan-07070753892592532851438Jan-073119287468056700035661725Jan-07380789014859180704445260117-Jan-07
Feb-076947405065285634035.897.167.337.147.667.65Feb-073680000530125401388Feb-077025199596360454832551994Feb-075120112157872566704012228117-Feb-07
Mar-074686804934202893196.617.777.517.658.148.16Mar-0700045972371456Mar-075885612477860059332005485Mar-07625511223896795975307058117-Mar-07
Apr-0710232011994711974432200904
Feb-jan7796394894233072847.377.457.337.387.417.83Feb-jan00031311674393Feb-jan3698811784690738302523493Feb-jan3363512615782643812782827Feb-jan
Averageminmax
Inlet9431242703
P1238601180
P2845433
P319465
P415355
P58317
-
Challenge: Maintain soil fertility and stocking rates
AFBI Research – quantifying P Balance
Reducing the P surplus of NI Agriculture
-
Target Concentration
Improvements in water quality in NI
Courtesy of NIEA, Northern Ireland
-
0
10
20
30
40
1995 2000 2005 2010
P in
put (
kg P
/ ha
)
P fertiliserP feedsFertiliser and feed inputs
Average farm P surpluses for NI: 1995-2013Phosphorus inputs to NI farmland
0
5
10
15
20
25
1995 2000 2005 2010
Farm
P s
urpl
us (k
g P/
ha)
A dramatic decline in P fertiliser usage since 2003 caused a significant decline in mean farm P surpluses on NI farms
A progressive increase in concentrate P usage, however, has recently begun to reverse this decline in farm P surplus
Currently, farm P surpluses on 50% of dairy farms (non-derogated) are between 10 and 40 kg P/ha/yr
Overuse of P in land based livestock production
Courtesy of John Bailey, AFBI
-
Lack of soil testing and manure application in fields close to farm yards As a result, on average 66% of land on intensive dairy farms is over-supplied
with P and on some 100% of fields have P indices > index 2
0 - Deficient1 - Low2 - Optimal3 - High4 -Very High5 – Gross Excess
1 & 23-3+ 45-5+
Low - OK
High
Very High
Gross Excess
Farmyard
Soil P index distribution on intensive dairy farms
Unbalanced distribution of P
Courtesy of John Bailey, AFBI
-
Directive 2000/60/ECTarget is to restore all surface water to good
ecological and chemical status by 2027
Water Framework Directive
-
Challenge: Need for Additional Measures & Setting Realistic Targets
Chemical Water Quality Biological Water Quality
Why is there no improvement in biological water quality?
Requirement for long term monitoring programmes of lakes and river networks
0102030405060708090
100
1990 1991 1992 1993 1994 1995 1996 1997 1998 2008
% o
f site
s
ASPT > 65 < ASPT < 64 < ASPT < 5ASPT < 4
0
20
40
60
80
100
1990 1991 1992 1993 1994 1995 1996 1997 1998 2009
% o
f site
s
Salmonid
Cyprinid
no fish
Courtesy of Chris Barry, AFBI
Ecological targets are NOT being met
Chart1
1990199019901990
1991199119911991
1992199219921992
1993199319931993
1994199419941994
1995199519951995
1996199619961996
1997199719971997
1998199819981998
2008200820082008
ASPT < 4
4 < ASPT < 5
5 < ASPT < 6
ASPT > 6
% of sites
8.3333333333
58.3333333333
33.3333333333
0
26.0869565217
43.4782608696
21.7391304348
8.6956521739
8
64
24
4
16
48
28
8
12
56
24
8
12
64
16
8
12
60
28
0
12
56
28
4
8
68
24
0
4.347826087
60.8695652174
30.4347826087
4.347826087
summary
ASPT
1990199119921993199419951996199719982009mean 1990-1998SD 1990-1998improvedecline
UB 95.796.476.426.656.836.175.945.576.006.086.210.42x
UB 105.606.055.836.196.215.965.146.144.945.505.780.47x
UB 244.755.325.525.255.434.845.365.845.065.505.260.34
UB 184.885.175.054.825.004.734.784.725.005.404.910.16
UB 165.575.325.625.525.396.115.335.265.255.395.490.27
UB 175.654.904.854.765.064.634.444.435.255.184.890.39
UB 214.854.334.244.654.674.474.384.294.455.084.480.20x
UB 75.314.954.845.034.244.884.855.144.685.054.880.30
UB 114.554.144.834.644.544.144.294.154.385.004.410.25x
UB 145.134.754.655.215.285.225.255.815.765.005.230.39x
UB 125.265.785.115.645.605.425.835.004.955.460.31x
UB 135.375.475.105.285.125.045.255.294.684.935.180.23x
UB 84.504.534.384.364.334.134.063.924.004.904.250.22x
UB 154.414.424.754.474.384.294.124.414.474.784.410.17
UB 224.584.004.133.934.254.254.394.004.084.754.180.21x
UB 44.063.564.214.254.193.863.734.084.084.524.000.24x
UB 64.834.004.524.334.074.255.004.384.474.504.430.33
UB 204.633.804.204.794.334.174.084.084.754.504.310.34
UB 14.143.783.913.854.004.004.164.064.184.474.010.14x
UB 23.935.294.134.084.204.294.274.294.294.474.310.39
UB 254.384.384.434.384.544.454.284.414.334.410.07
UB 34.334.004.153.903.703.853.694.074.214.253.990.22x
UB 54.004.473.873.863.914.153.753.853.924.003.970.22
UB 194.334.474.845.074.634.694.335.005.284.740.33
UB 234.894.434.334.294.334.184.294.294.380.22
BMWP Score
1990199119921993199419951996199719982009mean 1990-1998SD 1990-1998improvedecline
UB 2476101138147125921181118118711024.61
UB 911012312217315717910111710815213229.46
UB 1611710119114912417112812112615113628.58
UB 131021041481691281311261118914312324.85
UB 46532808567544153531135917.20x
UB 78510412115189117971138910610720.94
UB 83686929665626951681036919.44x
UB 108411513416114914972135849912032.98
UB 12100156138141140103105909912224.65x
UB 17964963818174806284887414.17x
UB 15755395677060707576867111.70x
UB 6584495785768805767816715.35
UB 183962968210571868590818019.78
UB 147757799995948493121808917.65
UB 1583443506052796971765714.28x
UB 25912762536360646060766822.51
UB 2255486659686879605376629.46
UB 11505887655958605457706110.61
UB 365445439375048615968519.80x
UB 21635272798467706049666611.60
UB 20373863676550535357545410.85
UB 5327658544354455047525112.09
UB 25707062575949777552659.70x
UB 192667927188756590957421.39
UB 234462526065717360619.51
Taxa
1990199119921993199419951996199719982009mean 1990-1998SD 1990-1998improvedecline
UB 2416192528231922191634214.06x
UB 1319192932252624211929244.71x
UB 1621193427232824232428254.41
UB 41691920161411131325153.57x
UB 919191926232917211825214.02x
UB 716212530212420221921224.00
UB 88192122151517131721164.27x
UB 12192727252519181820224.10
UB 612112118141616131518153.10
UB 1015192326242514221718214.45
UB 1517122015161417171718162.26
UB 11491113151319171717143.15
UB 215241513151415141417153.28
UB 1717101317161618141617152.49
UB 315111310101313151416131.94
UB 1415121719181816162116172.57
UB 2391412141517171416142.62
UB 188121917211518181815163.99
UB 1111141814131414131314141.86
UB 58171514111312131213132.54
UB 2113121717181516141113152.44
UB 208101514151213131212122.30
UB 25161614131311181712152.38
UB 1961519141916151818164.03
UB 22121216151616181513152.05
summary
0.41725958450.4172595845
0.46517663520.4651766352
0.33994570890.3399457089
0.15608908560.1560890856
0.26905472360.2690547236
0.39237809040.3923780904
0.20242322470.2024232247
0.30299103220.3029910322
0.24816227660.2481622766
0.38809048390.3880904839
0.30840761930.3084076193
0.23004241870.2300424187
0.22228678210.2222867821
0.16757353540.1675735354
0.2107691930.210769193
0.23718011240.2371801124
0.32691645880.3269164588
0.33930087140.3393008714
0.14174217520.1417421752
0.3883819040.388381904
0.07462259870.0746225987
0.22430903230.2243090323
0.21760502420.2176050242
0.33485517910.3348551791
0.21785913960.2178591396
2009
1990-1998 mean (+/- 1 SD)
ASPT
site ranking
24.609167216924.6091672169
29.456653653229.4566536532
28.583697762528.5836977625
24.851782855824.8517828558
17.200613684117.2006136841
20.940391591420.9403915914
19.442936449519.4429364495
32.984845004932.9848450049
24.651499519724.6514995197
14.169607537914.1696075379
11.702326454411.7023264544
15.349629021915.3496290219
19.780742599219.7807425992
17.654870275517.6548702755
14.282856857114.2828568571
22.511725339922.5117253399
9.45750730619.4575073061
10.611838253210.6118382532
9.79512350339.7951235033
11.595018087311.5950180873
10.851267207110.8512672071
12.093386622412.0933866224
9.7018039569.701803956
21.389249636221.3892496362
9.50845488429.5084548842
mean 1990-1998
2009
1990-1998 mean (+/- 1 SD)
BMWP
Sheet1
4.05517502024.0551750202
4.71109800844.7110980084
4.40958551844.4095855184
3.57460176493.5746017649
4.02423215594.0242321559
44
4.27200187274.2720018727
4.09703725714.0970372571
3.10017920633.1001792063
4.44722135474.4472213547
2.2607766612.260776661
3.15348132143.1534813214
3.28295260063.2829526006
2.48886408722.4888640872
1.93649167311.9364916731
2.57120810342.5712081034
2.61861468282.6186146828
3.99304951693.9930495169
1.85592145431.8559214543
2.53859103532.5385910353
2.43812313972.4381231397
2.29734145872.2973414587
2.37546987832.3754698783
4.03457281234.0345728123
2.04803428792.0480342879
mean 1990-1998
2009
1990-1998 mean (+/- 1 SD)
Taxa
UB 9
UB 10
UB 11
UB 12
UB 13
UB 8
UB 4
UB 1
UB 3
UB 16
UB 4
UB 8
UB 12
UB 1
UB 3
BMWP Score
UB 24
UB 13
UB 4
UB 9
UB 8
UB 18
UB 17
UB 21
UB 7
UB 11
UB 14
UB 13
UB 8
UB 15
UB 22
UB 4
UB 6
UB 20
UB 1
UB 2
UB 25
UB 3
UB 5
ASPT
ASPTBMWPTaxa
siteimprovedeclineimprovedeclineimprovedeclinesiteno changeshift to higher scoring taxamore higher scoring taxamore lower scoring taxashift to lower scoring taxaloss of similar scoring taxa
1xx11
222
3xx33
4xxx44
555
666
777
8xxx88
9xx99
10x1010
11xx1111
12xx1212
13xx1313
14x1414
15xx1515
161616
171717
181818
19not assessed19not assessed
202020
21x2121
22x2222
23not assessed23
24x24
25x2525
no changeshift to higher scoring taxamore higher scoring taxamore lower scoring taxashift to lower scoring taxaloss of similar scoring taxa
214910
5381312
611
715
16
17
18
20
21
22
ASPT
31990199119921993199419951996199719982009
3.5UB 95.796.476.426.656.836.175.945.576.006.08
4UB 105.606.055.836.196.215.965.146.144.945.50
4.5UB 244.755.325.525.255.434.845.365.845.065.50
5UB 184.885.175.054.825.004.734.784.725.005.40
5.5UB 165.575.325.625.525.396.115.335.265.255.39
5UB 175.654.904.854.765.064.634.444.435.255.18
6UB 214.854.334.244.654.674.474.384.294.455.08
6.5UB 75.314.954.845.034.244.884.855.144.685.05
UB 114.554.144.834.644.544.144.294.154.385.00
UB 145.134.754.655.215.285.225.255.815.765.00
UB 125.265.475.785.115.645.605.425.835.004.95
UB 135.374.535.105.285.125.045.255.294.684.93
UB 84.504.424.384.364.334.134.063.924.004.90
UB 154.414.004.754.474.384.294.124.414.474.78
UB 224.583.564.133.934.254.254.394.004.084.75
UB 44.064.004.214.254.193.863.734.084.084.52
UB 64.833.804.524.334.074.255.004.384.474.50
UB 204.633.784.204.794.334.174.084.084.754.50
UB 14.145.293.913.854.004.004.164.064.184.47
UB 23.934.384.134.084.204.294.274.294.294.47
UB 34.334.004.384.434.384.544.454.284.414.33
UB 54.004.474.153.903.703.853.694.074.214.25
UB 194.334.473.873.863.914.153.753.853.924.00
UB 234.894.845.074.634.694.335.005.28
4.434.334.294.334.184.294.29
sites24232525252525252523
average4.814.684.744.754.724.664.594.694.684.89
stdev0.55352182160.74464840920.67279199850.7097989960.76138798450.68999280130.61544111470.72455979120.55320748150.4852990469
Bin1990199119921993199419951996199719982008
30000000000
3.50000000000
42624333321
4.5669710101212116
58475463268
5.54526526347
64041121420
6.50211120101
More0001100000
sum hist24232525252525252523
sum sample24232525252525252523
%
1990199119921993199419951996199719982008
< 48268161212121284
4 - 4.525263628404048484426
4.5 - 53317282016241282435
5 - 5.5172282420824121630
5.5 - 61701644841680
6 - 6.50944480404
> 6.50004400000
100100100100100100100100100100
1990199119921993199419951996199719982008
ASPT < 48268161212121284
4 < ASPT < 558436448566460566861
5 < ASPT < 633222428241628282430
ASPT > 60948880404
100100100100100100100100100100
< 4
4 - 4.5
4.5 - 5
5 - 5.5
5.5 - 6
6 - 6.5
> 6.5
ASPT < 4
4 < ASPT < 5
5 < ASPT < 6
ASPT > 6
% of sites
Chart1
199019901990
199119911991
199219921992
199319931993
199419941994
199519951995
199619961996
199719971997
199819981998
200920092009
no fish
Cyprinid
Salmonid
% of sites
45.8333333333
33.3333333333
20.8333333333
26.0869565217
56.5217391304
17.3913043478
48
32
20
40
56
4
52
40
8
32
36
32
52
32
16
8
64
28
24
32
44
0
16.6666666667
83.3333333333
% summary
siteChemical Water Quality Class- SUMMER
1990199119921993199419951996199719982009ImproveDeterior
16666635443
2*5445535322
3*6566656651
4*5455655331
56666535553
65555535452
72234524331
8*5455556423
91112121211
101114226221
11*4356355322
12113322221
133333443232
143333332221
15*5423523421
16*3323322221
174365634232
185454464442
193334324352
20*5564655351
214343435353
22*5543555342
236556532
243333343222
252264523342
Number of sites24232525252525252524
Number of Samples11 (sum)9 (sum)10(sum)10(sum)10(sum)10(sum)10(sum)12(sum)10(sum)10(sum)
24
Number of sites1990199119921993199419951996199719982009
Salmonid545128471120
Cyprinid81381410981684
No fish116121013813260
% of sites1990199119921993199419951996199719982009
Salmonid20.833333333317.391304347820483216284483.3333333333
Cyprinid33.333333333356.52173913043256403632643216.6666666667
no fish45.833333333326.086956521748405232528240
24232525252525252524
siteChemical Water Quality Class- all year
199019911996199719982009
1664333
2453223
3566533
4454333
5664553
6555353
7223323
8455323
9111211
10114221
11344322
12212222
13333222
14332222
15453322
16332222
17343222
18454333
19334353
20554332
21344333
22554332
23433
24332222
25222222
Number of Samples25423
1990199119921996199719982009
Salmonid555101313
Cyprinid1381613811
no fish6112230
2424023252424
2424025252524
% summary
Salmonid
Cyprinid
No fish
Number of sites
improved sites vs Bio
50% = 12 sites
Salmonid
Cyprinid
no fish
% of sites
Sheet3
UB8
UB11
UB4
UB8
UB11
UB2
UB3
UB4
UB15
UB16
UB20
UB22
Salmonid
Cyprinid
no fish
site
summer1990-1998 mean
1990199119921993199419951996199719982009
454556553314.5555555556
854555564234.5555555556
1143563553224
whole year
199019911996199719982009
4454333
8455323
11344322
41990-1998 mean
BMWP58197272594046454511351
TAXA167192016121413133014
ASPT3.632.713.793.603.693.333.293.463.463.773.44
81990-1998 mean
BMWP3044778153414045508851
TAXA58151610889101510
ASPT6.005.505.135.065.305.135.005.005.005.875.24
111990-1998 mean
BMWP4742846256426551546756
TAXA9916121191411111211
ASPT5.224.675.255.175.094.674.644.644.915.584.92
BMWP
1990199119921993199419951996199719982009
458197272594046454511351
83044778153414045508851
114742846256426551546756
TAXA
1990199119921993199419951996199719982009
4167192016121413133014
858151610889101510
119916121191411111211
ASPT
1990199119921993199419951996199719982009
43.632.713.793.603.693.333.293.463.463.773.44
86.005.505.135.065.305.135.005.005.005.875.24
115.224.675.255.175.094.674.644.644.915.584.92
wq chembmwpaspttaxa
2009411133.7730
200983885.8715
2009112675.5812
mean 90s44.5555555556513.4414
mean 90s84.5555555556515.2410
mean 90s114564.9211
4
8
11
WQ-chem
4
8
11
ASPT
4
8
11
Taxa
4
8
11
BMWP
-
• Target high risk areas with:– Wetlands– Riparian zones– Willows– Vegetated ditches– Absorption resins– Zone land– Plough/Reseed
• Reduce the P surplus and improve manure distribution (incl. manure separation)
How can we move forward?Further options to reduce P losses
-
• Growth in demand for agricultural products • Increased dependence on concentrate feeds (mainly
cereals) in livestock systems• Increasing concerns regarding the environmental impacts
of intensive farming systems (e.g. GHGs & ammonia emissions, water quality, ecological impacts)
• Compliance with EU Directives (e.g. Nitrates Directive and WFD) and environmental targets
ConclusionsKey issues:
-
Sustainable Agricultural Production
Innovation is required
-
Thank you for listening
Acknowledgements:John Bailey, Rachael Carolan, Donnacha Doody, Suzanne Higgins, Ronnie Laughlin, Karen McGeough and all the Agri-Environment field and lab staff
Nitrogen and phosphorus losses from grassland soils and potential abatement strategies Slide Number 2Slide Number 3Results in eutrophicationCRITICAL LOAD EXCEEDANCESSlide Number 6N2O emissions from UK farmed livestockSlide Number 8Slide Number 9Slide Number 10Slide Number 11Slide Number 12Slide Number 13Slide Number 14Nitrogen consumption (%) of straight N productsSlide Number 16Slide Number 17Slide Number 18Slide Number 19Slide Number 20Slide Number 21Slide Number 22Slide Number 23Slide Number 24Slide Number 25Slide Number 26Slide Number 27Slide Number 28Slide Number 29Slide Number 30Slide Number 31Slide Number 32Slide Number 33Slide Number 34Slide Number 35Slide Number 36Slide Number 37Slide Number 38Slide Number 39Slide Number 40Slide Number 41Slide Number 42Slide Number 43Slide Number 44Slide Number 45Slide Number 46