Skip to main content

Advertisement

Log in

Testing and Application of the AquaCrop Model for Wheat Production Under Different Field Management Conditions in South-Eastern Australia

  • Full-Length Research Article
  • Published:
Agricultural Research Aims and scope Submit manuscript

Abstract

A field experiment involving two spring wheat varieties (EGA Gregory and Livingston) was conducted for 2 years (2013 and 2014), late sown in the first year and early sown in the second year, under two soil water regimes (rainfed and supplemental irrigation) at Wagga Wagga, Australia. The FAO’s AquaCrop model version 4.0 was calibrated and validated for crop canopy cover, dry aboveground biomass, soil water content and grain yield. The root-mean-square error (RMSE) for grain yield and dry aboveground biomass was 0.293 and 2.2 t ha−1, respectively. The RMSE for the rootzone soil water content was 25 mm. The validated model was used to analyse the effect of in-season and off-season conditions on grain yield and water productivity. Grain yield and water productivity decreased (50% for Gregory and 43% for Livingston) with the delay in sowing date. Applying four irrigations to the mid-May sown wheat resulted in a higher (6.5, 5.7 and 5.2 t ha−1, respectively, at 80% exceedance probability) yield relative to the mid-April and mid-June sowing dates. Applying supplemental irrigation both in September and October resulted in a better yield (6.7 vs. 6.0 t ha−1) and water productivity than applying irrigation only in October. The effect of off-season managements such as mulch and pre-irrigation on yield is 68% higher in low-rainfall years that that of in the wet years.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. ABARES (2011) Agricultural commodity statistics 2011. ABARES project 43047. Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra

    Google Scholar 

  2. Andarzian B, Bannayan M, Steduto P, Mazraeh H, Barati ME, Barati MA, Rahnama A (2011) Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran. Agric Water Manag 100:1–8

    Article  Google Scholar 

  3. Angus JF, Nix HA, Russell JS, Kruizinga JE (1980) Water use, growth and yield of wheat in a subtropical environment. Aust J Agric Res 31:873–886

    Article  Google Scholar 

  4. Araya A, Habtu S, Hadgu KM, Kebede A, Dejene T (2010) Test of AquaCrop model in simulating biomass and yield of water deficient and irrigated barley (Hordeum vulgare). Agric Water Manag 97(11):1838–1846

    Article  Google Scholar 

  5. Babel MS, Deb P, Soni P (2019) Performance evaluation of AquaCrop and DSSAT-CERES for maize under different irrigation and manure application rates in the Himalayan region of India. Agric Res 8(2):207–217. https://doi.org/10.1007/s40003-018-0366-y

    Article  Google Scholar 

  6. BOM (2015) Australian Government Bureau of Meteorology. Climate data services. http://www.bom.gov.au/

  7. Connor DJ (1975) Growth, water relations and yield of wheat. Aust J Plant Physiol 2:353–366

    Google Scholar 

  8. FAOSTAT (2013) FAO statistical yearbooks—world food and agriculture. Food Agric. Organization United Nations, Rome

    Google Scholar 

  9. Fischer RA (1979) Growth and water limitations to dryland wheat yield in Australia; a physiological framework. J Aust Inst Agric Sci 45:83–95

    Google Scholar 

  10. Food and Agricultural Organization (FAO) (2009) AquaCrop: the FAO crop-model to simulate yield response to water. http://www.fao.org/nr/water/aquacrop.html

  11. French RJ, Schultz JE (1984) Water use efficiency of wheat in a Mediterranean-type environment: 1. The relationship between yield, water use and climate. Aust J Agric Res 35:743–764

    Article  Google Scholar 

  12. García-Vila M, Fereres E, Mateos L, Orgaz F, Steduto P (2009) Deficit irrigation optimization of cotton with AquaCrop. Agron J 101(3):477–487. https://doi.org/10.2134/agronj2008.0179s

    Article  Google Scholar 

  13. Gomez-Machpherson H, Richards RA (1995) Effect of sowing time on yield and agronomic characteristics of wheat in south-eastern Australia. Aust J Agric Res 46:1381–1399

    Article  Google Scholar 

  14. Heng LK, Hsiao T, Evett S, Howell T, Steduto P (2009) Validating the FAO AquaCrop model for irrigated and water deficient field maize. Agron J 101(3):488–498. https://doi.org/10.2134/agronj2008.0029xs

    Article  Google Scholar 

  15. Hsiao TC, Heng L, Steduto P, Rojas-Lara B, Raes D, Fereres E (2009) AquaCrop—the FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agron J 101:448–459

    Article  Google Scholar 

  16. Iqbal MA, Shen Y, Stricevic R, Pei H, Sun H, Amiri E, Penas A, del Rio S (2014) Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation. Agric Water Manag 135:61–72

    Article  Google Scholar 

  17. Isbell RF (2002) The Australian soil classification. CSIRO Publishing, Melbourne

    Book  Google Scholar 

  18. Jeffrey SJ, Carter JO, Moodie KM, Beswick AR (2001) Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environ Model Softw 16:309–330

    Article  Google Scholar 

  19. Jin X, Yang G, Li Z, Xu X, Wang J, Lan Y (2018) Estimation of water productivity in winter wheat using the AquaCrop model with field hyperspectral data. Prec Agric 19:1–17

    Article  Google Scholar 

  20. Jones JW, Kiniry JR (1986) CERES-Maize: a simulation model of maize growth and development. Texas A&M University Press, College Station

    Google Scholar 

  21. Jones JW, Hoogenboom G, Porter C, Boote K, Batchelor W, Hunt L, Wilkens P, Singh U, Gijsman A, Ritchie J (2003) The DSSAT cropping system model. Eur J Agron 18:235–265

    Article  Google Scholar 

  22. Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JNG, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith CJ (2003) An overview of APSIM, a model designed for farming systems simulation. Eur J Agron 18(3–4):267–288

    Article  Google Scholar 

  23. Liu DL, Scott BJ, Pradhan UC, Martin P, Cole C (2003) Frost risk in New South Wales wheat belt. “Solutions for a better environment”. Edited by. In: Unkovich M, O’Leary G (eds) Proceedings of the 11th Australian Agronomy Conference. Geelong, Victoria

  24. Mancosu N, Snyder RL, Kyriakakis G, Spano D (2015) Water scarcity and future challenges for food production. Water 7:975–992

    Article  Google Scholar 

  25. Mhizha T, Geerts S, Vanuytrecht E, Makarau A, Raes D (2014) Use of the FAO AquaCrop model in developing sowing guidelines for rainfed maize in Zimbabwe. Water SA 40(32):233–244

    Article  Google Scholar 

  26. Mkhabela MS, Bullock PR (2012) Performance of the FAO AquaCrop model for wheat grain yield and soil moisture simulation in Western Canada. Agric Water Manag 110:16–24

    Article  Google Scholar 

  27. Neghassi HM, Heerman DF, Smika DE (1975) Wheat yield models with limited soil water. Trans Am Soc Agric Eng 18:549–557

    Article  Google Scholar 

  28. Nendel C, Berg M, Kersebaum KC, Mirschel W, Specka X, Wegehenkel M, Wenkel KO, Wieland R (2011) The MONICA model: testing predictability for crop growth, soil moisture and nitrogen dynamics. Ecol Model 222:1614–1625

    Article  CAS  Google Scholar 

  29. Passioura JB (1976) Physiology of grain yield in wheat growing on stored water. Aust J Plant Physiol 3:559–565

    Google Scholar 

  30. Penrose LDJ (1993) Yield of early dryland sowing of wheat with winter and spring habit in southern and central New South Wales. Aust J Expt Agric 33:601–608

    Article  Google Scholar 

  31. Pook M, Lisson S, Risbey J, Ummenhofer CC, McIntosh P, Rebbeck M (2009) The autumn break for cropping in southeast Australia: trends, synoptic influences and impacts on wheat yield. Int J Climatol 29:2012–2026. https://doi.org/10.1002/joc.1833

    Article  Google Scholar 

  32. Raes D, Steduto P, Hsiao TC, Fereres E (2009) AquaCrop—the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agron J 101(3):438–447. https://doi.org/10.2134/agronj2008.0140s

    Article  Google Scholar 

  33. Salemi H, Soom MAM, Lee TS, Mousav SF, Ganji A, Yusoff MK (2011) Application of AquaCrop model in deficit irrigation management of winter wheat in arid region. Afr J Agric Res 610:2204–2215

    Google Scholar 

  34. Scott BJ, Eberbach PL, Evans J, Wade LJ (2010) EH Graham Centre Monograph No. 1: stubble retention in cropping systems in Southern Australia: benefits and challenges. In: Clayton EH, Burns HM (eds) Industry & Investment NSW, Orange, Australia. http://www.csu.edu.au/research/grahamcentre

  35. Steduto P, Hsiao TC, Raes D, Fereres E (2009) AquaCrop - The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agron J 101(3):426–437. https://doi.org/10.2134/agronj2008.0139s

    Article  Google Scholar 

  36. Stockle CO, Donatelli M, Nelson R (2003) CropSyst, a cropping systems simulation model. Eur J Agron 18:289–307

    Article  Google Scholar 

  37. Tan S, Wang Q, Zhang J, Chen Y, Shan Y, Xu D (2018) Performance of AquaCrop model for cotton growth simulation under film-mulched drip irrigation in southern Xinjiang, China. Agric Water Manag 196:99–113

    Article  Google Scholar 

  38. Wellens J, Raes D, Traore F, Denis A, Djaby B, Tychon B (2013) Performance assessment of the FAO AquaCrop model for irrigated cabbage on farmer plots in a semi-arid environment. Agric Water Manag 127:40–47

    Article  Google Scholar 

  39. Williams JR, Jones CA, Dyke PT (1989) EPIC—erosion/productivity impact calculator. 1. The EPIC model. USDA-ARS, Temple

    Google Scholar 

  40. Willmott CJ (1982) Some comments on the evaluation of model performance. Bull Am Meteorol Soc 63:1309–1313

    Article  Google Scholar 

  41. Zeleke KT, Luckett D, Cowley R (2011) Calibration and testing of the FAO AquaCrop model for canola. Agron J 103(6):1610–1618

    Article  Google Scholar 

  42. Zydelis E, Weihermuller L, Herbst M, Klosterhalfen A, Lazauskas S (2018) A model study on the effect of water and cold stress on maize development under nemoral climate. Agric For Meteorol 263:169–179

    Article  Google Scholar 

Download references

Acknowledgements

The lead author was Alexander von Humboldt, a research fellow at Leibniz Centre for Agricultural Landscape Research (ZALF), Germany, when writing this manuscript. We thank Karl Moore for field technical assistance.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ketema Zeleke.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zeleke, K., Nendel, C. Testing and Application of the AquaCrop Model for Wheat Production Under Different Field Management Conditions in South-Eastern Australia. Agric Res 9, 379–391 (2020). https://doi.org/10.1007/s40003-019-00438-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40003-019-00438-2

Keywords

Navigation