Will climate change negate better farm management for improving water quality in the Mackay-Whitsunday region? - Peter Thorburn
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Will climate change negate better farm management for improving water quality in the Mackay-Whitsunday region? - Peter Thorburn
- 1. Will climate change negate better farm management for improving water quality in the Mackay-Whitsunday region? Peter Thorburn, Jody Biggs, Steve Crimp and (CSIRO Ecosystem Sciences) Will Higham (Reef Catchments Ltd)
- 2. Runoff from agriculture a threat to health of the Great Barrier Reef Brodie et al. (2008) Scientific Consensus Statement on Water Quality in the Great Barrier Reef. Federal Govt Reef Rescue $200M package 2008-2013 • $146M in incentives to farmers to adopt improved management practices • Delivered through NRM Bodies • Adoption of A-Class and B-Class practices • Phasing out of C-Class and D-Class practices
- 3. What, why and how APSIM Farming systems model Management practices (A-D) Predicted climate change • Sugarcane • Major source of dissolved N • Mackay-Whitsunday region • Biggest ‘single’ area of sugarcane • ~150,000 ha, 30% of total area • Dominates cropping (> 99%) • Approach...
- 4. A ‘typical’ sugarcane farming system • A basic planting/harvest schedule • Planted May • Plant Crop: 14 months long • 4 Ratoon Crops: 13 months long • Fallow: 6 months long • Bare OR Soybean (Leichhardt variety) • Limited irrigation (<= 100mm / crop) 14 mth 13 mth 13 mth 13 mth 13 mth 6 mth
- 5. Representing management practice classes • ABCD Management classes from Mackay-Whitsunday Water Quality Improvement Plan • Management of soil, fallow, N rate and tillage. Class Traffic Fallow N Fertiliser (kg/ha) plant / ratoons* Tillages per crop cycle A controlled Soy (harvest) 0 / ~85 (‘N-Replacement’) 1 B controlled Soy (cover) 0 / 130-140 (‘Soil specific’) 2 C conventional Bare 144 / 180 (‘Calcino’) 11 D conventional Bare 192 / 240 20 *Based on different recommendation systems
- 6. Representing controlled traffic • Controlled traffic reduces runoff c.f. conventional tillage (Masters et al. 2008) • APSIM determines runoff through curve numbers (CN) • A low CN results in higher infiltration and hence less runoff • CN affected by residue cover, tillage and soil water • APSIM CN values parameterised from Masters et al. (2008)
- 7. Representing regional variability • 3 soils (well tested) • Cracking clay / Heavy clay loam / Loam • 3 met stations (SILO) • Eton(En) / Plane Ck (Pk)/ Proserpine(Pr) • Long term simulation • ~70 years • Large and consistent effect of management class • Soils and Met combined Management class
- 8. Effect of management class: Yields not affected but N loads are • Median N loads reduced • Reduced from 31 to 3 kg N/ha/yr Historical climate, across all soils and met stations
- 9. Climate change predictions: Historical + 3 projections • All projections based on 2030 • CO2 increase to 437 ppm • A combination of GCM and historical trends in the distribution of climate extremes (Crimp et al. 2002). • CO2 fertilisation 0 1000 2000 3000 4000 Rain (mm) 26 27 28 29 30 Max Temp ( o C) 19 20 21 22 Daily Radn (MJ d -1 ) Current Weak Moderate Strong • Weak • MUIB/KMA ECHO-G / SRES B1 • Moderate • ECHAM5/MPI-OM / SRES A1B • Strong • GFDL CM2.1 / SRES A1FI • Historical (SILO climate data) Historical
- 10. Effect of climate change: Example for C Class management • Yields different by up to 15 t/ha/yr • Strong = Smallest yield • Weak = Largest yield • Moderate similar to Historical • N loads < 5 kg N/ha/yr different Historical Historical
- 11. Climate change compared to management change • Effect of management change >> greater than 2030 CC. • Class D = 31 kgN/ha/yr • Class A = 3 kgN/ha/yr • Maximum CC less than 5 kgN/ha/yr • In fact: • 1 Class change similar to maximum CC by 2030 Historical Weak Moderate Strong Historical Weak Moderate Strong Historical Weak Moderate Strong Historical Weak Moderate Strong 0 25 50 Median N loads (kgN/ha/yr) A C D B
- 12. Conclusions • Is best practice always going to be better? Yes. • Moving towards an ‘A’ class practice will provide significant improvements in N loads for all climate change scenarios investigated here. • Effect of weak climate change possibly good & strong bad • Production • N Loads • Predicted ‘benefits’ strongly affected by CO2 fertilisation • Substantial uncertainty
- 13. Acknowledgements: Steve Attard & Sarah Park (CSIRO) Staff of Reef Catchments Ltd Managing Climate Variability R&D Program
Editor's Notes
- Is best practice always going to better? The question we have tried to answer is: “In light of predicted climate change, what management choices will reduce N loads from sugarcane cropping in the Mackay-Whitsunday region?” We attack this problem by using a cropping systems model to predict the impact of a range of management options on productivity and the environment and then test options these against a range of possible climate change scenarios.
- For this study we had to define a sugarcane cropping cycle considered fairly typical of the Mackay-Whitsunday region. [Click] The plant crop was planted in May and harvested 14 mths later [Click] It was followed by 4 ratoons, all 13 mths in duration [Click] followed by a bare or soybean fallow The crops received 100mm or less in irrigation.
- Out of the Federal and State Governments ‘Reef Plan’, a WQIP for the Mackay-Whitsunday region was developed. In this WQIP, 4 classes of management were identified, labelled as A to D. A class A practice included: controlled traffic, a soybean fallow with the grain harvested, And a fertiliser rate determined using the ‘N-replacement’ concept (where N removed in the previous crop is replaced). And minimal tillage Class B: Had the controlled traffic, A soybean ‘cover’ crop where all the plant material is returned to the soil, And a fertiliser rate determined according to the currently recommended ‘soil specific nutrient guidelines’. Otherwise known as six easy steps. Class C representing conventional practice: Had no controlled traffic A bare fallow With fert rates based on Calcino’s industry wide recommendation. And significant number of tillage events Class D: Had no controlled traffic A bare fallow With a high rate of N applied And a large number of tillage operations.
- As mentioned before the WQIP identified that controlled traffic was important. There has been some work done in the region by Bronwyn Masters on pesticide/nutrient in runoff under controlled traffic versus conventional practice. Where she measured a reduction in runoff using controlled traffic. APSIM uses a parameter called curve number (devised by the USDA) to represent soils ability to produce runoff. Basically a low CN results in higher infiltration and hence less runoff And this CN is modified in the model on a daily basis by the amount of residue cover soil surface disturbance from tillage events and the current soil water content. We successfully parameterised APSIM to represent this effect of controlled traffic. Thank you Bronwyn.
- We also wanted to represent some of the variability in the region with respect to soils and climate. We used three soils from experimental work in the Mackay region (a loam, a heavy clay loam and a cracking clay) We selected three met stations from the region located at the Eton Police station, the Plane Ck Mill and the Proserpine PO, which covered the range of climates in the region. So we then performed long term simulations using ~ 70 yrs of historical climate information to run all combinations of the 3 soils, 3 met stations and 4 management classes. Before I move on. From now on when I refer to N loads, I’m referring to the total DIN in both runoff and deep drainage at the paddock scale. So this graph shows how N loads are affected by management (across the top) , met station or location (on the X axis), and soil type (on the Y axis). There is some soil and met station effects but these are small compared to the larger and consistent effect of management class. So for the sake of time I will from now on I describe the effect of management practice and climate change based on the medians (of all soils and met stations) My apologies for forgetting B class on this graphic.
- From this rather large dataset I’ll summarise some of the main points we have discovered. Firstly the effect of management class on cane yields and N loads. This represents the median cane yields and N loads for the historical climate for all soils and met stations. Yields are unaffected by the choice of management class. While median N loads are reduced from 31 to 3 kg N /ha/yr moving from Class D to A.
- So we have the management practices and the cropping systems model and the regional variability sorted it’s time to introduce the climate change sensitivity test. The climate change predictions used were short range with a focus on 2030 where CO2 concentrations are predicted to be 437 ppm. In the words of Steve Crimp “The effect of this CO2 level on the climate was represented by a combination of GCM and historical trends in the distribution of climate extremes.” I thank Steve Crimp for his help with this section of the work. This resulted in 4 climate scenarios. An example of the effect of these scenarios on max temperature, daily radiation and rainfall average at Plane Ck are shown here. The Current of historical climate A weak climate change scenario using the GCM described here with a low rate of global warming. Moderate climate change this GCM with a medium rate of global warming And High climate change using this GCM with a high rate of global warming. So we used APSIM to predict the cane yields and N loads from the 3 soils by 3 met stations by 5 management classes by 4 climate change scenarios for ~70 crops.
- Moving on to the effect of climate change. This is graph is just an example based on the C class management. But overall the largest difference in median yields due to CC was ~ 15 t/ha/yr. A strong climate change scenario producing the smallest yields and weak climate change the largest yields. The yields are a result of a balance between the advantages of CO2 fertilisation and disadvantages of temperature and water stress. If you remember the climate scenarios did not vary according to CO2 levels but according to the effect of that CO2 level on the climate. Interestingly, the median N loads for the 4 climate change scenarios differed by no more than 5 kgN/ha/yr.
- So with respect to N loads, the effect of management class [CLICK] is much greater than the range of climate change [CLICK] likely in 2030. In fact climate change is predicted to be unable to negate improvements resulting from even a single change in management class, for example D to C or B to A.