port phillip and westernport catchment
DESCRIPTION
Evaluating the effectiveness of agricultural management practices to reduce nutrient loads from farms in PPWP. Port Phillip and Westernport Catchment. Project Manager: Anja George (DPI) - Catchment and Agriculture Services -. Background. - PowerPoint PPT PresentationTRANSCRIPT
Evaluating the effectiveness of agricultural management practices to
reduce nutrient loads from farms in PPWP
Port Phillip and Westernport Catchment
Project Manager: Anja George (DPI)
- Catchment and Agriculture Services -
Background
Deteriorating water quality is a major threat to the waterways and bays of PPWP
In 2004, only 25% of the waterways were in good or very good condition.
50% of the PPWP regions is utilised for agr. pursuits (4,500 enterprises, annual production value $1 billion ).
Agricultural land is a significant contributor of nutrients (nitrogen and phosphorus).
What we ALREADY know...Clear link between the way agricultural land is managed
and nutrient export.
Nutrient export from some agr. pursuits is controlled through licensing, reducing nutrients from majority of land uses relies on BMP’s.
Appropriate management of agr. land through the adoption of BMP can reduce nutrient exports and minimise water quality impacts.
Ability to reduce nutrient exports varies from farm to farm, catchment to catchment, industry to industry.
Practices that are successful in one area may not be suitable for all farms or land uses in catchment.
What we DON’T know...
To what extent can agri BMP’s be used to reduce TN and TP exports from farms to waterways in PPWP?
• specific land uses and characteristics of PPWP (soils, rainfall)
Traditionally difficult to measure benefit of individual BMP’s on water quality
Research into nutrient export from agricultural land has focused predominantly on the paddock scale (very few at farm scale) AND not in PPWP.
Specific information on effectiveness of BMP’s in reducing N and P exports in PPWP is limited.
What we NEED to know...
For the major agricultural land uses in PPWP:
What are the agricultural sources of nutrients?
Transport pathways of nutrients from farms to waterways?
Catchment and Environmental factors that influence export?
Which BMP’s? (one, all, point, diffuse sources?)
Which land uses ? (eg. dairy, beef)
How? (feasibility, cost and implementation mechanisms )
Project overview:
Aim: To evaluate the effectiveness of agricultural BMP’s to reduce nutrient (TN and TP) exports from farms to waterways.
• Two year project (June 2005- June 2007).
• Partnership between DPI CAS and PIRVic Soil and Water Platform
• Working group (9 members-inter-agency, technical expertise)
Information from this project will help land managers and catchment planners make informed decisions on management of agr. land for water quality protection.
Working Group:Name
Anja George (Project Manager)DPI CAS – Port Phillip and Westernport
Ruth DuncanDPI PIRVic, Tatura – Senior Hydrologist
QJ WangDPI PIRVic, Tatura– Principal Scientist, Soil and Water
David NashDPI PIRVic, Ellinbank– Statewide Leader – Soil Chemistry
Kirsten Barlow- Senior ScientistDPI PIRVic, Water Quality Project Manager
Murray McIntyreDSE, Manager, Water and Catchment Services
David McKenzieEPA-Gippsland
Hannah PextonMelbourne Water (and DSS Project Manager)
Mark Hincksman DPI, CASWhole Farm Planning (Horticlture)
Land uses Investigated Project focuses on catchments and land uses that have been identified as key sources of Nitrogen and Phosphorus in
PPWP:
Dairy (Westernport)Beef (Westernport)Strawberry (representative of annual horticulture) (PP-
Yarra)
Methodology
2 sections:• Bayesian Network Model development
• Model application and demonstration (Scenario testing)
Part 1: Bayesian Network ModelsDevelopment of 5 Bayesian Networks Models (TN and TP): 2 x Dairy 1 x Beef 2 x Annual horticulture (Strawberry)
Bayesian Network Models: Describe cause and effect of management decisions on outcomes Incorporate qualitative and quantitative information from all levels
(farmers, industry, agency, scientists etc..) thereby reducing uncertainty. Calculates consequence of agri. management practices by determining
probability (%) of small, medium and large TP/TN load under different management scenarios and landscape characteristics
Limitations (What it can’t do!): Give absolute numbers on nutrient export loads (ie. t/ha/yr). This is
presented in probability (%).
Model at farm scale (not catchment). Scenario are used to test and demonstrate wider industry/catchment /regional application.
Spatial Distribution of Fert.
poorfairgood
10.075.015.0
Fertiliser Application Rate
lowmediumhigh
10.060.030.0
Sub-Surface Flow (mm)
smallmediumlarge
43.832.323.9
38.3 ± 18
TP Load from Stock Access (kg/ha)
lowmediumhigh
50.042.57.50
0.45 ± 0.59
Surface TP Load Export (kg/ha)
lowmediumhigh
75.423.21.34
3.8 ± 2.8
Sub-Surface Transport Capacity
lowmediumhigh
43.832.323.9
38.3 ± 18
Surface Slope
lowhigh
80.020.0
Infiltration Capacity
lowmediumhigh
20.446.333.3
Fertility
lowmediumhigh
5.0050.045.0
Sub-Surface Soil Texture
lightmediumheavy
30.050.020.0
Surface Soil Texture
lightmediumheavy
70.030.0 0
Sub-Surface Drainage
noyes
90.010.0
Fert. Application Effectiveness
poorfairgood
22.026.851.2
Stocking Rate (cows/ha)
lightmediumheavy
65.020.015.0
2 ± 0.8
Phosphorus Balance
neutralpositivevery positive
9.8952.138.0
Nutrient Retention
smallmediumlargevery large
19.060.020.0 1.0
0.612 ± 0.17
Point TP Load (kg/ha)
smallmediumlarge
42.055.72.34
0.834 ± 0.74
Point Availability of TP (kg/ha)
lowmediumhigh
33.464.02.59
0.939 ± 0.8
Dairy point source (kg/ha)
lowmediumhigh
34.763.22.10
0.906 ± 0.75
Storage of Hay/Silage (kg/ha)
poorgood
30.070.0
0.015 ± 0.023
Rainfall Annual
lowmediumhigh
12.038.050.0
0.595 ± 0.17
TP from Erosion (kg/ha)
lowmediumhigh
58.319.122.5
0.0771 ± 0.13
Availability of TP Tunnel/Gully Erosion (...
lowmediumhigh
60.020.020.0
0.06 ± 0.11
Surface Flow (mm)
smallmediumlarge
5.7555.339.0
180 ± 61
Rainfall Annual
lowmediumhigh
12.038.050.0
1080 ± 150
Total Runoff (mm)
lowmediumhigh
12.038.050.0
223 ± 46
Timing of Application
poorfairgood
10.020.070.0
Distance of point source to Watercourse
closemediumfar
30.055.015.0
0.675 ± 0.24
Duration
dairy onlydairy feedpad
95.05.00
0.55 ± 0.22
Dairy/Feed Pad Effluent Mgmt
poorfairgood
60.030.010.0
0.315 ± 0.19
Track Design and Mmgt
poorfairgood
20.060.020.0
0.15 ± 0.14
Diffuse Availability of TP (mg/L)
lowmediumhigh
24.635.739.7
2.28 ± 0.71
Soil Mgmt
poorfairgood
50.030.020.0
Bought in Feed
lowmediumhigh
30.050.020.0
Sub-Surface Soil
peaty sandyother
5.0095.0
0.05 ± 0.22
Sub-Surface Drainage Capacity
lowmediumhigh
45.039.415.6
Stock Access to Watercourses
yesno
50.050.0
0.25 ± 0.25
Sub-Surface TP Load Export kg/ha)
smallmediumlarge
95.0.0534.95
0.0104 ± 0.052
TP Load from Dairy Farm (kg/ha)
smallmediumlarge
75.323.31.39
3.81 ± 2.8
Surface and Point TP Load (kg/ha)
lowmediumhigh
45.346.97.79
5.7 ± 3.6
Diffuse Surface TP Load (kg/ha)
smallmediumlarge
13.556.030.5
4.34 ± 2.4
HYDROLOGY
DIFFUSE SOURCES
POINT SOURCES
LOAD OUTPUTS
Probability of TP load from Dairy farm
Example: Diffuse TP load (Dairy)
Spatial Distribution of Fert.
poorfairgood
33.333.333.3
Fertiliser Application Rate
lowmediumhigh
33.333.333.3
Fertility
lowmediumhigh
33.333.333.3
Fert. Application Effectiveness
poorfairgood
36.726.736.7
Phosphorus Balance
neutralpositivevery positive
18.051.330.7
Timing of Application
poorfairgood
33.333.333.3
Diffuse Availability of TP (mg/L)
lowmediumhigh
26.733.539.8
2.44 ± 0.96
Bought in Feed
lowmediumhigh
33.333.333.3
Model Applications Scenario Testing:
To demonstrate how changes in climate, landscape factors (eg. soil types, rainfall, slope) and management practices (eg. effluent and fertiliser management) can influence TN and TP export.
Scenarios DescriptionPoor Management Worst or poor management practices
Current Management Management of farms at time of investigation
Farmers Future Plans Landholder selected management practices they are
planning to implement within the next 5-10 years Greatest Nutrient Reduction
(A = feasible, B =not feasible)
Management practice with greatest capacity for reducing TN and TP export from farms as informed by models (top 3). Feasibility (cost effectiveness) is also investigated
Best Practice(A = feasible, B =not
feasible)
All best management practices as informed by industry guidelines.
Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5
VariablesPoor
PracticesCurrent
ManagementFarmers Planned
Greatest Nutrient
Reduction (cost-
effective)
Greatest Nutrient
Reduction (Not cost-effective)
Best Practice
(cost-effective)
Best Practice (Not
cost-effective)
Annual rainfall High
Surface soil texture Heavy 30%, Medium 70%
Sub-surface soil texture Heavy
Surface slope High
Sub-surface soil* Other
Fertility* High
Distance to waterways Close
Soil management Poor Fair Fair Fair Fair Good Good
Sub-surface drainage No No No No No No Yes
Timing of fertiliser application Poor Fair Fair Good Good Good Good
Spatial distribution of fertiliser Poor Poor Poor Poor Poor Good Good
Fertiliser application rate High High High Low Low Low Low
Bought in feed Low Low Low Low Low Low Low
Stocking rate Light Light Light Light Light Light Light
Effluent Management Poor Poor Good Poor Poor Good Good
Track design and management Poor Fair Fair Fair Fair Good Good
Storage of silage Poor Good Good Good Good Good Good
Stock access to watercourses YesYes 50% No 50%
Yes 50% No 50%
No No No No
Tunnel/Gully erosion* High High High High High Medium Low
Nutrient retention Small Small Small Medium Very Large Medium Very Large
Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5
Poor/PastPractices
Current Management
Farmers Planned
Greatest Nutrient
Reduction (cost-
effective)
Greatest Nutrient
Reduction (Not cost-effective)
Best Practice
(cost-effective)
Best Practice (Not cost-
effective)
Probability of SMALL TP load 15% 19% 24% 69% 100% 82% 100%
Probability of MEDIUM TP load 56% 59% 62% 31% 0% 19% 0%
Probability of LARGE TP load 28% 22% 14% 0% 0% 0% 0%
Change in Phosphorus Load 0.13 0.72 1.03 0.85 1.03
Improvement in TP load compared to current management
Large Very Large Very LargeVery
LargeVery Large
Change in Phosphorus Load 0.09 0.22 0.81 1.13 0.94 1.13
Improvement in TP load compared to poor management
Small Large Very Large Very LargeVery
LargeVery Large
Probability of SMALL TN load 1% 1% 4% 12% 28% 19% 31%
Probability of MEDIUM TN load 42% 54% 55% 72% 59% 73% 62%
Probability of LARGE TN load 57% 45% 42% 16% 13% 6% 7%
Change in Nitrogen Load 0.06 0.40 0.59 0.56 0.68
Improvement in TN load compared to current management
Small Very Large Very LargeVery Large
Very Large
Change in Nitrogen Load 0.12 0.18 0.52 0.71 0.69 0.80
Improvement in TN load compared to poor management
Large Large Very Large Very LargeVery
LargeVery Large
Probability of nutrient loads
Direction and magnitude of change in nutrient load to compare scenarios
Where to from here?
Assessment of results
What do these results mean for:a) Farmers?b) Land use and agri industry (ie. dairy)?c) Management of agricultural land in catchment?d) Broader application/PPWP/BBW Strategy?e) Future Implementation mechanisms?f) Knowledge and research gaps (R and D requirements)?
Final Project report due: June 2007.
Thank You
Anja GeorgeDepartment of Primary Industries
Woori YallockPh: (03) 5954 4001