Department of Employment, Economic Development and Innovation

The expected value of seasonal stream-flow forecasts to a grain-cotton irrigator in the Condamine-Balonne catchment.

Brendan Power, Daniel Rodriguez, Jeff Perkins and Claire Hawksworth

2© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

• Seasonal stream flow forecasts • Whole-farm economic modelling of

irrigated grain/cotton farms with APSIM

• Case study results

Overview

3© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

www.bom.gov.au/water/ssf

Seasonal streamflow forecasts

4© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Forecast skill

5© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

What is APSIM?

A farming systems model created …• to model the farming system performance over

time• with equal emphasis on crop and soil

dimensions of agricultural systems• with a capability to deal comprehensively with

management – e.g. planting times, N, irrigation

• wide scope of application, from genetics (breeding) through farming systems to policy.

6© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

APSIM

Soilwat

SoilN

SurfaceOM

ChickpeaMaize

Wheat

SoilPH

SoilWat

SWIM

SoilP

Erosion

Manager

Paddock

7© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Pump cap.

Economics

Met

Manager

paddock7Soil

Weeds

Residue

Crops

paddock6 Soil

Weeds

Residue

Crops

Farm

paddock2 paddock3

SoilwatSoil

Residue

paddock8

Crops

paddock5Soil

SoilN

Residue

paddock4

Soil

Weeds

Crops

Crops

Weeds

Residue

Soil

Weeds

Crops

Residue

Soil

Weeds

Residue

Crops

paddock1Soil

Weeds

Crops

Residue

Water sources

Waters storages

Weeds

Irrigated APSIM farms

8© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Planting window: Sep 15 – Oct 15Stored water > 4ML/ha

Existing farm area planted to maize or sorghum less than 50%

Planting window: Oct 16 – Jan 15Rain over 4 days > 25mm

ESW > 150mmmaize or sorghum area < 50% Oct 15 – Nov15

Stored water > 4ML/hacotton area < 50%

Case studies

9© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Validation

10© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Validation

11© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Dalby case study farm

Dalby

12© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Dalby case study farm

• Total cropping area - 615ha• Furrow irrigation• 3 Storages - 2400 ML at 70ML/day• Sources of water

– On-farm runoff– Off-farm overland flow ~tr(0,200,400) ML/yr– Bores (172ML/yr at 12ML/day)– River flow

13© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

IQQM modelled Condamine river flow

14© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

• Streamflow forecasts not currently available in QLD (available from July 2012)

• The NINO3 index with a 2 month lag has the best skill at predicting summer (DJF) rainfall at Dalby (Schepen et al., 2011) .

• NINO3 index used as a proxy forecast for Condamine River flows.

Proxy streamflow forecasts

15© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Summer (DJF) rainfall

Positive forecastNegative forecastNo forecast

Rainfall (mm)

Pro

babi

lity

Summer (DJF) river flows

Positive forecastNegative forecastNo forecast

River flow (ML)

Pro

babi

lity

Oct NINO3 index

16© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Change in management• Vary cotton area based on the streamflow prediction• Assumed monoculture cotton for simplicity• Cotton area depends on the amount of stored water at

sowing• Optimised the cotton sowing rule based on NINO3

values w.r.t. required stored water (ML/ha) at sowing.• Results:

– Positive NINO3 predictions - 0 ML/ha (ie plant entire farm to cotton)

– Negative NINO3 – no change in management (ie 4 ML/ha)

– 20 out of 51 years predicted high river flows.

17© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Results

Current managementAdaptive management

High flow seasons

AU$31,000/year

Current managementAdaptive management

All seasons

18© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

What next?

• Realistic crop rotations• Implication for risk• Different farms and rivers • Out-of-sample tests• Environmental trade-offs

19© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

Summary:• Seasonal stream flow forecasts • Whole-farm economic modelling of

irrigated grain/cotton farms with APSIM

• Case study results

20© The State of Queensland, Department of Employment, Economic Development and Innovation, 2011

References• Australian Bureau of Meteorology (2010) Information sheet 9 Streamflow

forecasting: Days to seasons, Australian Government, retrieved from www.bom.gov.au/water/about/publications/document/InfoSheet_9.pdf

• Hammer GL, Nicholls N, Mitchell C (2000) Applications of Seasonal Climate Forecasting in Agricultural and Natural Ecosystems: The Australian Experience. Kluwer Academic,

• Power B, Rodriguez D, deVoil P, Harris G, Payero J (2011) A multi-field bio-economic model of irrigated grain-cotton farming systems. Field Crop Res.

• Schepen A, Wang QJ, Robertson D, (2011) Evidence for using climate indices to forecast Australian seasonal rainfall, J. Climate.

• The State of Queensland (DERM) (2010). Integrated Quantity and Quality Model (IQQM) output data for the Condamine Balonne ROP www.derm.qld.gov.au

Thanks.