Editors 1. D. Sturtz and A. L Chapman

Proceedings. of a Workshop at the NT Rural College, Katherine, 18-20 July, 1995

AUSTRALIAN INSTITUTE OF AGRICULTURAL SCIENCE, NORTHERN TERRITORY ZONE

DECEMBER 1996

National Library of Australia Cataloguing - in - Publication Entry

Conservation farming for the semi-arid tropics: proceedings of a workshop at the NT Rural College, Katherine, 18-20 July, 1995/ editors J.D. Sturtz and AL. Chapman.

Bibliography ISBN 0 85856 132 8

1. No-tillage - Australia, Northern - Congresses. 2. Soil conservation - Australia, Northern -Congresses. 3. Conservation tillage - Australia, Northern - Congresses. I. Sturtz, J. D. (John David). II. Chapman, A L. (Andrew Lewis). III. AlAS Occasional publication. IV. Title.

Published by Northern Territory Zone, Australian Institute of Agricultural Science. AlAS Occasional Publication No. 101 .

Available from: NT Zone, AlAS, PO Box 206, Berrimah, NT, Australia 0828

Cover Design: Melissa Spencer Cover Photographs: F. O'Gara and D. Abrecht

Printed by Zip.Print

II

PRELIMINARY ASSESSMENT OF CERES-MAIZE-SAT USING CROPLANDS EROSION RESEARCH PROJECT (CERP) DATA FROM DOUGLAS-DALY, NT.

J. A. Motha, M. Dilshad and L. J. Peel

Land Conservation Unit Department of Lands, Planning and Environment. G.P.O. Box 1680. Dam-in, NT.

Abstract: A new version of the CERES-Maize modeL enhanced to make it user friendly and modified to include physical and climatological conditions unique to the semi-arid tropics (SAT) of Australia. has been tested for Hycorn 9 maize on red earths at Douglas-Daly. This paper presents derived and estimated parameters for the model and some preliminary results from the simulation. Comparison of predicted and measured hydrologic and agronomic values show very good agreement. Further work is necessary to test the model under different physicaL climatological and management conditions.

INTRODUCTION

The CERES-Maize model was first developed in the U.S.A. (Jones and Kiniry 1986). The model has since been adopted by Australian scientists and has undergone changes to accommodate conditions unique to local environments (Carberry et al. 1989; Dimes and McCown 1992). A modified version of the model for the SAT of Australia has been presented by John Dimes (pers. comm.). Some work has been done on the parameterisation and predictability of this version for the SAT of the Northern Territory (NT), as previously reported by Motha et al. (1994). ,

This paper summarises the input values for Hycorn 9 maize grown under conventional tillage, presents preliminary results from the simulation and discusses the predictive ability of the model for the tested conditions.

THE SITE

Data from the Croplands Erosion Research Project (CERP) located at the Douglas-Daly Research Farm (DDRF), 250 km south-west of Darwin, has been used in this study. CERP was a joint project undertaken by the Conservation Commission of the Northern Territory (CCNT) and the Northern Territory Department of Primary Industry and Fisheries (NTDPIF). The project has been described by Dilshad and Jonauskas (1990) and Dilshad and Peel (1994).

Conditions in the 1986-87 season for the conventionally tilled paddock with double-spaced soil conservation banks were simulated in this study. The paddock, covering an area of 6.4 ha, was sown with maize cv. Hycorn 9 as described in Dilshad and Peel (1994). The paddock had previously been cropped with maize and soybean cv. Buchanan on an annual rotation.

MODEL INPUTS

Climate File

Climate data required for the simulation were daily rainfall, maximum temperature, minimum temperature and radiation. Rainfall (9am to 9am) was measured using 200 mm pluviometers (Meteorological Bureau issue) encircling the field site. Maximum and minimum daily temperature records at the site were incomplete and the gaps were filled using corresponding

173

data from the research farm about 2.5 km away. As radiation data was not recorded at the site during the period under consideration, data from the research farm were used.

Parameter File

The parameter file was constructed using measured values, standard values based on experience (Bateman pers. comm.), and best estimates (Thiagalingam pers. comm.) where standard values were not available or measured values were inarguably erroneous. Critical input parameter values included in the parameter file are summarised in Table 1. Nomenclature used in the CERES-Maize VII (Hargreaves and McCown 1988) documentation has been used herein.

RESULTS AND DISCUSSION

Runoff

The model uses the curve number method (CNM) of the Soil Conservation Service of the United States Department of Agriculture, described in detail by Dilshad and Peel (1994), to compute runoff. The cumulative runoff computed by CERES-Maize for CN2 values of 90 and 95 (Figs. 1 a and 1 b) is plotted together with measured runoff.

A CN2 value of 90 was derived from optimised CN 1 and CN3 values obtained by Dilshad and Peel (1994). CN1, CN2 and CN3 are the curve numbers for dry, average and wet antecedent soil moisture conditions, respectively.

The cumulative runoff for a CN2 value of 90 does not exhibit as good a comparison between the measured and predicted runoff, as does cumulative runoff for a CN2 value of 95. However, it is very important to note here that the CN2 value of 90 has been derived based on antecedent rainfall, whereas, the model uses antecedent soil moisture.

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Table 1. Critical parameter values used in the simulation

Management data

Plant population Sowing depth 3.6/m2 3.0cm F ertilisati on 02/01187 DAP 200 kglha 03102/87 Urea 100 kglha

Genetic data Cultivar PI P2 P5 G2 G3

Hycorn 9 209.0 0.52 1070.0 535.0 7.0

Soil data

Soil albedo Stage 1 Drainage rate Runoff coefficient evaporation coefficient CN2 coefficient U SWCON

0.20 1.00 0.70 90.0

Residue Depth of Residue C:N Root dry Root C:N weight residue weight

incorporation 60 kglha l.Ocm 60.0 2000 kglha 60.0

Layer Root Initial Organic Bulk pH NH4 N03 depth distn. moist. carbon density

weighting content (cm) ratio (%) (%) (glee) (%) (%)

15.0 0.86 18.0 0.87 1.57 6.5 11.2 3.9 15.0 0.64 22.0 0.59 1.57 6.2 3.6 0.7 15.0 0.47 25.0 0.27 1.58 6.3 1.4 0.8 lS.0 0.35 25.0 0.27 1.S8 6.4 0.9 0.7 15.0 0.26 25.0 0.20 1.S8 6.5 0.9 0.2 15.0 0.19 25.0 0.20 l.58 6.6 0.9 0.2 30.0 0.12 25.0 O.IS 1.58 6.6 0.9 0.1

P 1 Growing degree daysfom seedling emergence to end o.(juveni!e stage. P2 Photoperiod sensitivity coefficient (111,-1) P5 Growing degree days/i'om ,<dIking to maturi~v G2 Potential kernelnulllber (kernels/plant) G3 Potential kernel growth rate (11Ig/kerne//d)

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1 ..... 11

-II- Prodded

-B- Me.'ured

~~~~~~~M~~~~~~~~~~~~~ Day ('Inhc Ynr

Fig.1a Predicted and Measured Runoff (CERP Bay 21986·87) CN2 - 90

Soil Moisture

3:;0.0

0.0 -tf~!"I"\II!'I""r'IIT,rrl'TlIITI IITlrrl ITl'lT, ITI ,TTIITlI,rTl rr'1Tl'1T'1rTl'1 O~~~~~~N~~~~~~~~~~~~~

o.y "fthe nor Fig.l b Predicted and l\leasured Runoff (CERP Bay 2 1986(87) CN2=95

The predicted and measured soil moisture profiles, computed using a CN2 value of 90 for 7 January 1987 (day 7 i.e., 6th day'from sowing), 30 January 1987 (day 30), 27 February 1987 (day 58) and 10 April 1987 (day 100) are presented in Figs. 2a, 2b, 2c and 2d, respectively. The corresponding results for a CN2 value of 95 are presented in Figs. 3a, 3b, 3c and 3d, respectively. Figs. 2a, 2c and 2d, and 3a, 3c and 3d show good agreement between measured and predicted volumetric soil moisture contents. By comparison, the measured and predicted values for 30 January 1987 (Figs. 2b and 3b) differ considerably, although the agreement is slightly better for CN2 value of 95 than for 90. This is probably attributable to an underestimation in the eN value computed by the model for appropriate antecedent moisture conditions.

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45,(1

40,0

35,0

30.0 ,...., ,0 ~

" 25.0 E " .~

§ '20.0

~ 15,0

10,0

5,0

0,0

40.0

35.0

30.1)

~ ~5.0

~ .~ 2(1,0

j .J. 15.0

10,0

5,0

0,0

( CN2=90 )

0,0 20.0 40.0 60.0 Depthincm

80,0 100,0

Fig.2a Predicted and f\Ieasured Volumetric . Soil Moisture Contents for 07/01187

f),1) :0.0 40.0 00.(1 Depth in Ctn

80.0 100,il

Fig.2(' Predicted and Measured Volumetric Soil Moisture Contents for 27,02187

177

45.fl 1 4Cl.fl

35,0

30.0

~ ~

~ 25.0

(>

'5

~ 20.0 -0 >

15,0

10.0

S.n

0.(1

40.0

35.0

30.0

l25.0

~ .~ 20,0

j .J. 15.0

10.0

5,0

0.0

0.0 20,0

-e- Predicted

~ Measured

LowerUmft

Drain ed Upper Limit

Saturated Moisture Conlenl

40.0 60.CJ

Depth incm 80.0

Fig.2b Predicted and f\leasured Vollunetric . Soil f\1oisture Contents for 30/0l/87

C).O :W.O 40.0 60.0 80.0 1 fJ(l.O Depth incm

Fig.2d Predicted and f\leasured Volumetric Soil Moisture Contents for 10'04'87

~5.1)

40.0

35.0

30.1) ~

,0

~

~ 15.0

<> .... '" ] :!(J.O

0 :>

15.0

10.1)

5.0

0.0

40.0

35,0

30.0

~ 25,(1

()

E .~ 20.0

~ ;g 15.0

11).1)

5.0

0.0

( CN2=95 )

0,0 :0.0 40.0 60.0 Depthincm

80.0 1 (H),O

Fi:;!.3a Predicted and Measured Volumetric

0.0

, Soil!-.Ioisture Contents for 07101187

:w.o 40.0 60.0

Depth in cm 8(1,(1 1(10.0

Fig.3" Predicted and Measured Volumetric , Soil!-.Ioisture Contents for 27/02/87

Agronomy

~5.0

40.0

35.0

30.0

~ '!..

~ 25.0

.j5

~ 20.0 '0 >

15.0

10.0

5,0

0.0

4(1.0

35.0

30.0

~ 15.0

~ .~ 20.0

1 -!}. 15.0

11),0

5,0

(I.e)

(t,n 20.0

-e- Predicted

~ Measured

Lower Limit

Drained Upper Limit

Saturated Moisture Content

--10.0 60.0

Depth incm SO.n 100.0

Fi:;!.3b Predicted and !-.leasured Yohnnetric . Soil Moisture Contents for 30:01,87

0.0 20.0 40,0 60.0 8(1,(1 }(J(l,O Depth incm

Fig.3d Predicted and Measured Volumetric Soil!-.!oisture Contents for 10'04: 87

The predicted and measured agronomic attributes at maturity for CN2=90 and CN2=95 are compared in Fig. 4. The differences in predicted values for these two curve numbers are very

178

marginal. In both cases, predictions agree very well with the corresponding measured values of most attributes, the differences being less than 10% of the measured values. However, agreement between measured and predicted values is poor for final grains per square metre (GPSM), grain N (kg/ha) and the percentage grain nitrogen, with differences of about 25% for final GPSM to about 50% in the case of grain N (%).

!,..CN2 =90 1.80 450 10000

1.60 400 mm P~dicte-d 9000

1.40 350 \IIIIIIIIIIIII Measured 8000

1.20 300 iOOO

1.00 250 6000

5000 0.60 200

4000 0.60 150 3000 0.40 100 2000

0.20 50 1000

0.00 0 0

1.80 .!!:,.CN2 = 95

450 10000

1.60 400 9000

1.40 350 8000

1.20 300 ;000

1.00 250 6000

5000 0.60 200

4000 0.60 150

3000 0.40 100 2000

0.20 50 1000

0.00 0 0 Kern wi Grain N Terminal GrainN SiIking Maturity T olaf N Grain,,!'Iani gdry % leafn,. kg.\1a Day Day kg.l1a kg/ha

Fig.4 Predicted and Measured Agronomic Outputs

CONCLUSION

The predictive accuracy of the CERES-Maize-SAT version is satisfactory except for final GPSM, grain N (kg/ha) and grain N (%). The model also predicted the soil moisture profile reasonably welL Although a CN2 value of 90, estimated from published optimised values of CN1 and CN3 based on antecedent rainfall, seems appropriate for the case under consideration a CN2 value of 95 gives the best agreement between predicted and measured hydrologic and agronomic attributes. The fact that the optimised values were obtained using antecedent rainfall and the model calculates CN values based on antecedent soil moisture might account in part for the above discrepancies. It should, however, be noted that this simulation was done for one cultivar only, under conditions prevalent in one paddock of CERP in 1986-87. Further simulations for varying conditions are necessary for a more complete evaluation of the model for the SAT of the NT.

ACKNOWLEDGMENTS

The authors wish to thank J. Dimes, R. Bateman, P. Jonauskas, M. Silburn, K Thiagalingam and staff at the Douglas-Daly Research Farm for their help.

179

REFERENCES

Carberry, P.S., Muchow, RC., and McCown, R L. (1989). Testing the CERES-Maize Simulation Model in a Semi-arid Tropical Environment. Field Crops Research 20, 297-315.

Dilshad, M., and Jonauskas, P. E. (1990). Impact of Land Use on Agricultural Hydrology in the Northern Territory Semi-arid Tropics. Working Paper for Specialist Workshop on ErosioniProductivity and Erosion Modelling, 5th Australian Soil Conservation Conference, Perth. pp. 104-107.

Dilshad, M., and Peel, L. 1. (1994). Evaluating the USDA Curve Number Method for Agricultural Catchments in the Australian Semi-arid Tropics. Australian Joumal of Soil Research 32, 673-685.

Dimes, 1. P., and McCown, R L. (1992). Potentially mineralizable N - A new role in predicting soil N supply. Proceedings 6th Australian Society of Agronomy Conference, Armidale. pp. 374-377.

Hargreaves, 1. N. G., and McCown, R L. (1988). VII CERES-Maize A Visual Interactive version of CERES-Maize, CSIRO Division of Tropical Crops and Pastures, Brisbane. Tropical Agronomy Technical Memorandum No. 62.

Jones, C. A, and Kiniry, 1. R (1986). Ceres-Maize A Simulation Model of Maize Growth and Development, Texas A&M University Press, College Station, Texas.

Motha, 1. A, Dilshad, M., and Bateman, R (1994). Simulating Maize Growth and the Hydrologic Response of Red Earths in Northern Territory Semi-arid Tropics. Conservation Commission of the Northern Territory, Palmerston. Technical Memorandum 94/01.

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