Nitrogen and phosphorus losses from grassland …...2019/01/02 · Sulphur-coated urea (SCU) Polyolefin coated urea (e.g. Meister®) and coated NPK(+) compounds (e.g. Nutricote®)

Nitrogen and phosphorus losses from grassland soils and potential

abatement strategies

Catherine WatsonFertilizer Association of Southern Africa - 30th July 2015

• 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

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

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

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)

Effects of acid rain on Bleaklow Moor, Derbyshire

(http://www.bbc.co.uk/news/uk-england-17930662)

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?

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

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

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

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

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

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

• 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

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%

% 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

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

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

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

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

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

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

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

Direct N2O emission factors (%)


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

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


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

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

Controlling phosphorus losses in Northern Ireland

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

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

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

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

• 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

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


TP in

runo

ff (m

g P

L-1 )


Spring(Start 17 March)

0

5

10

15


TP in

runo

ff (m

g P

L-1 )


• 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

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%)


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


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


Total P (kg P year-1)

Total P inputs to wetland and exports from each pond for 12 months March 2006 - February 2007


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


Pond level (mm)

Water balance

Pond level


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



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



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



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





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


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


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

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