Wateruse efficiency

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Water-use efficiency crop simulationPractical
uses in the Riverine Plains
Sustainable Agriculture Flagship

• James Hunt
• Research Scientist
• Mulwala - 23 July 2009

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Take home messages

• Water-use efficiency (WUE) calculations and crop
  simulators are great tools for matching inputs to
  crop potential, benchmarking performance and
  diagnosing problems
• WUE better suited to benchmarking
• Crop simulators (APSIM, Yield Prophet) better
  suited to yield forecasting decision support
• Both useful for diagnosis if used alongside
  measurements
• Accurate measurements of plant available water
  (PAW) are vital for accuracy of both methods
• There are other issues for both these methods
  specific to the Riverine Plains, all problems
  should have a solution but will require research
  effort

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• Back to WUE basics

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French Schultz water-use efficiency

• French RJ Schultz JE (1984) Water use
  efficiency of wheat in a Mediterranean-type
  Environment. I The relation between yield, water
  use and climate. Australian Journal of
  Agricultural Research 35, 743-64
• 61 paddocks mostly from NW South Australia
• 1964 to 1975
• 275 to 450 mm growing season rainfall
• Some trials, some farmer paddocks
• selected to avoid water loss by run-off or deep
  drainage
• Mostly Halberd tall variety
• Soil moisture recorded at sowing and maturity
• Dry-matter and yield recorded

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Water use is defined by adding the change in
soil water content between sowing and maturity to
the rainfall in the same period. It incorporates
both the water lost by direct evaporation from
the soil and the crop, and the water transpired
by the crop.
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Dry matter water-use efficiency
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Grain yield water-use efficiency
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we have drawn an arbitrary line which encloses
almost all the highest yielding crops at
different levels of water use and thereby defines
a linear relation between potential yield and
water use Other evidence suggests that this
linearity continues up to about 500 mm water use,
provided waterlogging does not occur..
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Physiological basis

• Wheat transpiration efficiency constant in most
  southern Australian situations
• Plants convert water to dry-matter (biomass) at
  55 kg/ha per mm of water transpired
• Evaporation varies
• Harvest index of different crops varies
• Tall wheat 0.35
• Semi-dwarf wheat 0.40
• Grain yield water use efficiency of different
  crops varies
• Tall wheat 55 x 0.35 19.25
• Semi-dwarf wheat 55 x 0.40 22

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Important points to note

• Water-use available water at sowing available
  water at maturity rainfall in between
• Estimate of yield potential not a predictive
  model
• Evaporation term changes with soil type and
  environment (110 mm)
• Transpiration efficiency for dry matter constant
  (55 kg/ha/mm)
• Grain efficiency term (20 kg/ha/mm) changes with
  harvest index
• Harvest index varies according to frost, disease,
  heat shock, nutrition and post-anthesis water use

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Evaporation loss in different environments
Sowing-maturity rainfall lt150 mm
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How is it useful?

• Assessing crop performance relative to water
  limited potential
• How did my crops perform relative to
  water-limited potential?
• How can the difference be explained?
• Unproductive water loss (evaporation, run-off,
  drainage, weeds)?
• Too much water (water logging)
• Low harvest index (nutrition, frost, disease)

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Transpiration efficiency for dry matter constant
55 kg/ha/mm
55 kg/ha/mm
Vigorous crop
Poorly growing crop
Evaporated water
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Analysis of production zones
High yielding Initial PAW 23 mm Evaporation 60
mm Harvest index 0.4
Moderate yielding Initial PAW 15 mm Evaporation
93 mm Harvest index 0.35
Low yielding Initial PAW 20 mm Evaporation 123
mm Harvest index 0.25
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Diagnosing low WUE

• You can learn a lot about underperforming crops
  provided you measure
• Soil water at sowing
• Rainfall
• Dry matter at maturity
• Grain yield
• Harvest index
• Protein

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Limitations of WUE

• What should the evaporation term be?
• Rainfall distribution can make a big difference
• Provides potential yield, not achievable yield
• Waterlogging in high rainfall environments with
  difficult soils
• Late sowing
• To be effective relies on accurate estimate or
  measurement of plant available water (PAW) at
  sowing
• Achieving water limited potential is not always
  possible, and in many circumstances not
  profitable

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High WUE not always possible or profitable

• Yield Prophet dataset 2004-2007
• 334 wheat paddocks from around Australia
• Average WUE is 15.2 kg/ha/mm
• Change simulated management to close gap
• Sow as early as possible following breaking rain
• Consistent plant density (150 plants/m2)
• Ensure nitrogen not limiting (topdressing with
  50kg N/ha between sowing and flowering when soil
  N levels fell below 50kg N/ha)
• Average WUE increases to 21.4 kg/ha/mm
• These changes incur significant risk and are
  often impossible!

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2. Matching investment to potential - WUE tools
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Matching investment to potential - WUE

• WUE defines potential yield based on water supply
• Inputs can be adjusted accordingly
• Tools developed to help asses yield potential
  in-season (e.g. PYCal, Rainman)
• Use a measure or estimate of soil water at
  sowing, add rainfall to-date, make an assumption
  about how much will fall for the remainder of the
  season (e.g. deciles)

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In-season potential yield estimation
Potential yields (t/ha)
Yield estimation
Crop sown
Decile 9
Decile 8
Decile 7
Decile 6
Rainfall deciles
Decile 5
Today
Soil sampling? Soil water estimate?
Decile 4
Decile 3
Decile 2
Decile 1
March
May
April
July
September
August
November
October
June
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Limitations and pitfalls

• 1. An accurate measure of soil water is vital!

• Hochman et al. (in review)
• y 0.013x - 0.575
• r2 0.46

• Hochman et al. (in review)
• y 0.015x 1.010
• r2 0.68

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The results indicate the importance of stored
water at sowing to supplement seasonal rainfall
and show that stored water is more effective in
promoting yield than rainfall from sowing to
maturity, presumably because it is not subject to
evaporation loss.
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Measuring plant available water (PAW)

• Easier said than done!
• Gravimetric soil water bucket approach (Neal
  Dalgliesh, Steve Henry)
• Robust and requires no calibration
• Essential for simulation tools APSIM and Yield
  Prophet
• Time consuming and requires repeated sampling
• Variation across paddocks can be a problem
• In-situ methods e.g. Sentek EnviroSCAN
• Continually measure once installed
• Can infer soil water bucket
• Expensive
• Technical
• Require calibration and interpretation

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Estimating plant available water

• Can use rules of thumb to estimate PAW prior to
  sowing with some confidence
• Assumes no summer weeds or carry-over water from
  previous crop
• Fallow efficiency (monthly rainfall) 30 of
  total out-of-season rain available for crop use
• Or
• 20 of Nov-Feb rain, 50 of Mar-Apr
• Cumulative events (daily rainfall) sum amount
  of water arriving in discrete rainfall events
  over a certain amount e.g. 20 mm
• What works on the Riverine Plains???

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Pitfalls and limitations

• Evaporation term changes with rainfall, soil type
  and crop management!
• What figure should you use?
• Potential area for research in Riverine Plains
  area?
• Improve calculation of spatially variable
  potential?

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2. Matching investment to potential simulation
tools
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APSIM and Yield Prophet

• APSIM (Agricultural Production SIMulator)
• Modular, mathematical model of production systems
• Largely a research tool
• Yield Prophet is a web interface for APSIM
  designed to provide user friendly output to
  farmers and consultants
• Accounts for much more than just total water use
• Daily rainfall, temperature and radiation
• Soil water characteristics (PAWC)
• Nitrogen and carbon dynamics
• Stubble and soil organic matter
• Crop type, cultivar phenology
• Sowing date
• Plant density
• Provides additional output other than yield
  potential

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Yield Prophet simulation
Simulated yields (t/ha)
Report generated
Crop sown
100 years of daily climate data
Soil sampling (starting point)
Today
APSIM simulation (water and nitrogen balance,
crop growth)
March
May
April
July
September
August
November
October
June
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Phenology
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Sowing opportunity
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How is it useful?

• Assessing crop performance relative to
  environment limited potential
• Estimating potential yield in season
• Management what if questions
• Nitrogen management
• Sowing time, cultivar and density
• Hay yield vs. grain yield
• Stubble management
• Soil water and nitrogen status
• Predicting crop development and risk of
  frost/heat shock
• Effect of seasonal forecasts and climate change
  on likely yields

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Limitations

• Requires a lot of information
• To make it work in a given region
• To make it work each year
• Information must be accurate for yield simulation
  to be accurate
• Cant simulate effects of frost and waterlogging
  on yield
• It can give probabilities of events occurring
• Requires computer literacy
• Requires an investment in time to set up and
  interpret
• Some groups provide reports e.g. Weather or Not
• Validity of using past climate to predict the
  future???
• Costs money

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Regional data required

• Soil plant available water capacities (some
  available)
• Quality historic climate data
• Good phenology data of relevant varieties
• Effect of other regional quirks on water
  extraction e.g. acidity, stony profiles, grazing

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Year to year data

• Plant available water prior to sowing
• Nitrate and ammonium
• Daily rainfall
• Sowing date
• Crop type
• Cultivar
• Sowing density
• Stubble type and amount
• Nitrogen fertiliser applications

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Yield Prophet 2004-2007

• Hochman et al. (in review)
• 336 wheat paddocks
• r2 0.71
• RMSD 0.82
• Only about 50 within 0.5 t ha-1

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Thank you
CSIRO Plant Industry James Hunt Research
Scientist Phone [phone] Email
james.hunt_at_csiro.au Web www.pi.csiro.au
Contact UsPhone 1300 363 400 or 61 3 9545
2176Email Enquiries_at_csiro.au Web www.csiro.au