Evaluation of Aqua-Crop Model using Onion Crop under Deficit Irrigation and Mulch in Semi-arid Nigeria

Abstract

The Aqua-Crop simulation model has been playing a crucial role in assessing the performance of the existing strategies for the management of irrigation schemes for improving agricultural water use efficiency. This study evaluated the Aqua-Crop model using Onion crops under deficit irrigation and mulch practices in semi-arid Nigeria. Measurements were taken from the experimental plots which consisted of irrigation and mulch each at 4 levels were used to evaluate the Aqua-Crop model using canopy cover, biomass, yield, actual crop ET, and water productivity of Onion during the 2021 irrigation season. The simulated results from the Aqua-Crop model were evaluated and statistically compared with the experimental results. The model simulated canopy cover with the highest degree of correlation coefficient (0.74 ≤ r ≤ 0.94). The model perfectly predicted Onion yield and biomass under full irrigation irrespective of the mulching. However, the model underestimated Onion yield and biomass at deficit irrigation. The model has perfectly estimated the seasonal actual crop evapotranspiration at different irrigation levels and mulch materials while underestimating water productivity in most of the treatments except at 100% irrigation under white synthetic mulch. However, both model and experimental water productivity were better at white synthetic mulch plots. Therefore, the Aqua-Crop model has proven to be a good Onion crop growth and yield predictor under different irrigation levels and mulch materials which can help improve Onion productivity in water-stressed areas like semi-arid Nigeria.

Keywords

• Deficit irrigation
• Aqua-Crop model
• Mulch
• Onion crop
• Semi-arid-Nigeria

References

1. Adeniji FA, Umara BG, Dibal JM and Amali AA (2013). Variation of infiltration rate with Soil texture. International Journal of Engineering and Innovative Technology (IJEIT), 3(2): 454-455.
2. Agbemabiese YK, Shaibu AG and Gbedzi VD (2017). Validation of Aqua-Crop for Different Irrigation Regimes of Onion (Allium Cepa) in Bontanga Irrigation Scheme, International Journal of Irrigation and Agricultural Development (IJIRAD), 1(1): 1-12.
3. Atefeh A and Ali N (2013). Evaluation of Aqua-Crop computer model in the potato under irrigation management; International Journal of Advanced Biological and Biomedical Research, 1(12): 1669-1678. http://www.ijabbr.com
4. Bagg JE and Turner NC (1976). Crop water deficits. Advances in Agronomy 28: 161-17.
5. Chukalla AD, M. S. Krol and A. Y Hoekstra (2015). Green and blue water footprint reduction in irrigated agriculture: effect of irrigation techniques, irrigation strategies and mulching. Hydrology and Earth System Sciences, 19(12): 4877-4891.
6. Corcoles J, Dominguez A, Moreno M, Ortega J and De Juan J (2015). A non-destructive method for estimating onion leaf area. Irish Journal of Agricultural and Food Research, 54(1): 17-30.
7. Darko OP, Yeboah S, Addy SNT, Amponsah S and Danquah EO (2013). Crop modelling: A tool for agricultural research-a review. Journal of Agricultural Research and Development, 2(1): 1-6.
8. Doorenbos J and Kassam AH (1979). Yield response to water. Irrigation and Drainage Paper No. 33. FAO, Rome, Italy.

9. FAO (1977). Guidelines for predicting crop water requirements by J. Doorenbos & W.O. Pruitt. FAO Irrigation and Drainage Paper No. 24. Rome.
10. FAO (2011). Food and Agriculture Organization of the United Nations. The State of the World’s Land and Water Resources: Managing Systems at Risk. London, Earth scan. Available from: http://www.fao.org/docrep/017/i1688e/i1688e.pdf
11. Farahani HJ, Izzi G and Oweis TY (2009). Parameterization and evaluation of the Aqua-Crop model for full and deficit irrigated cotton. Agronomy Journal, 101: 469-476.
12. Fereres E (2011). Deficit irrigation for reducing agricultural water use. Journal of Experimental Botany, 58:147-59.
13. Geertz S and Raes D (2010). Deficit irrigation as an on-farm strategy to maximize crop water Productivity in dry areas. Agricultural Water Management, 96: 1275–1284.
14. Heris AM, Nazemi NH and Sadraddini AA (2014). Effects of deficit irrigation on the yield, yield Components, water and irrigation water use efficiency of spring canola. Journal of Biodiversity and Environmental Sciences, 5(2): 44-53.
15. Hsiao TC, Heng L, Steduto P, Rojas-Lara B, Raes D and Fereres E (2009). Aqua-Crop-The FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal, 101(3): 448-459.
16. Heng LK, Hsiao T, Evett S, Howell T and Steduto P (2009). Validating of the FAO Aqua-Crop model for irrigated and water-deficient field maize. Agronomy Journal, 101(3): 488-498.
17. Igbadun HE, Ramalan AA and Oiganji E (2012). Effects of regulated deficit irrigation and mulch on yield, water use and crop water productivity of onion in Samaru, Nigeria. Agricultural Water Management, 109: 162-169.
18. Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens KPW, Singh U, Gijsman AJ and Ritchie JT (2003). Th e DSSAT cropping system model. European Journal of Agronomy, 18:235-265.
19. Kahimba FC, Sri Ranjan R, Froese J, Entz M and Nason R (2009). Cover Crop Effects on Infiltration, Soil Temperature, and Soil Moisture Distribution in the Canadian Prairies. Applied Engineering in Agriculture, 24(3): 321-333. doi: 10.13031/2013.24502
20. 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 and Smith CJ (2003). An overview of APSIM; A model designed for farming systems simulation. European Journal of Agronomy, 18: 267-288.
21. Khonok A (2013). The evaluation of water use efficiency in common bean (Phaseolus vulgaris L.) in irrigation conditions and mulch. Science of Agriculture, 2(3): 60-64.
22. Kiptum CK, Kipkorir EC, Munyao TM and Ndambuki JM (2013). Application of AquaCrop model in deficit irrigation management of cabbages in Keiyo Highlands. International Journal of Water Resources and Environmental Engineering, 5(7): 360-369.
23. Liu EK, He WQ and Yan CR (2014). White revolution to white pollution − Agricultural plastic film mulch in China. Environmental Research Letter, 9(9): (091001). ww.researchgate.net/publication/280115017
24. Nash JE and Sutcliffe JV (1970). River flow forecasting through conceptual models part- I: A discussion of principles. Journal of Hydrology, 10(3): 282-290.
25. Nasidi NM, Shanono NJ, Zakari MD, Ibrahim A and Bello MM (2015). Reclaiming salt-affected soil for the production of tomato at Barwa-Minjibir irrigation scheme, Kano. International Conference on Green Engineering for Sustainable Development, IC-GESD 2015. Held at Bayero University, Kano Nigeria.
26. Nazeer M (2009). Simulation of maize crop under irrigated and rainfed conditions with CropWat model. Journal of Agricultural and Biological Science, 4: 68-73.
27. Nazeer M and Hussein A (2012). Modelling the response of onion crop to deficit irrigation. Journal of Agricultural Technology, 8(1): 393-402.
28. Raes D, Steduto P, Hsiao TH and Fereres E (2009). AquaCrop-the FAO crop model for predicting yield response to water: II. Main algorithms and software description. Agronomy Journal, 101, 438-447. doi:10.2134/agronj2008.0140s
29. Rauff KO and Bello R (2015). A review of crop growth simulation models as tools for agricultural meteorology. Agricultural Sciences, 6(9): 1098-1105.
30. Sen R, Mondal ATMAI, Brahma S and Khan MS (2006). Effect of different soil moisture regimes on the yield and yield components of onion. Bangladesh Journal of Scientific and Industrial Research, 41 (1- 2): 109-112.
31. Shanono NJ (2019). Assessing the ımpact of human behaviour on reservoir system performance using dynamic co-evolution, A PhD Thesis Submitted to University of the Witwatersrand, Johannesburg. https://doi.org/http://wiredspace.wits.ac.za/handle/10539/29043
32. Shanono NJ, Nasidi NM, Zakari MD and Bello MM (2014). Assessment of Field Channels Performance at Watari Irrigation Project Kano, Nigeria. 1st International Conference on Dryland, Center for Dryland Agriculture, Bayero University Kano, Nigeria. 8th-12th December, 2014, 144-150.
33. Shanono NJ and Ndiritu J (2020). A conceptual framework for assessing the impact of human behaviour on water resource systems performance. Algerian Journal of Engineering and Technology, 3: 9-16. https://doi.org/http://dx.doi.org/10.5281/zenodo.3903787
34. Shanono NJ, Othman MK, Nasidi NM and Isma’il H (2012). Evaluation of Soil and Water Quality of Watari Irrigation Project in Semi-Arid Region, Kano, Nigeria. Proceedings of the 33rd National Conference and Annual General Meeting of the Nigerian Institute of Agricultural Engineers (NIAE) Bauchi., 181-186.
35. Sinnadurai S (1992). Vegetable Cultivation. Asempa Publishers. Accra, Ghana.
36. Steduto P, Hsiao T, Evett S, Heng LK and Howell T (2009a). Validating the FAO AquaCrop model for irrigated and water deficient field maize. Agronomy Journal, 101(3): 488-498.
37. Steduto P, Hsiao TC, Raes D and Fereres E (2009b). AquaCrop — the FAO Crop model to simulate yield response to water: I. Concepts and underlying principles. Agronomy Journal, 101: 426-437.
38. Steduto P, Hsiao TC, Fereres E and Raes D (2012). Crop Yield Response to Water. FAO Irrigation and Drainage Paper 66. Rome: FAO, 1–233.
39. Stöckle CO, Donatelli M and Nelson R (2003) CropSyst, a cropping systems simulation model. European Journal of Agronomy, 18: 289–307.
40. Tagar A, Chandio FA, Mari IA and Wagan B (2012) Comparative study of drip and furrow irrigation methods at Farmer’s field in Umarkot. International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering, 6(9): 788-792.
41. Toumi J, Er-Raki S, Ezzahar J, Khabba S, Jarlan L and Chehbouni A (2016). Performance Assessment of Aqua-Crop model for estimating evapotranspiration, soil water content and grain yield of winter wheat in
42. Tensift Al Haouz (Morocco): application to irrigation management. Agricultural Water Management, 163: 219-235.
43. Williams JR, Jones CA, Kiniry JR and Spanel DA (1989) The EPIC Crop Growth Model. Transactions of the ASAE. 32(2), 497-511. https://elibrary.asabe.org/abstract.asp?aid=31032
44. Zakari MD, Audu I, Shanono NJ, Maina MM, Abubakar MS and Mohammed D (2015). Sensitivity analysis of crop water requirement simulation model (CROPWAT (8.0) at Kano River Irrigation Project, Kano Nigeria. Proceedings for International Interdisciplinary Conference on Global Initiatives for Integrated Development (IICGIID 2015 Chukwuemka Odumegwu University, Igbariam Campus Nigeria), 502–510.
45. Zeleke KT, Luckett D and Cowley R (2011). Calibration and testing of the FAO AquaCrop model for Canola. Agronomy Journal, 103(6): 1610-1618.