Evaluation of Maize Response to Less Irrigation Management Using SWAP Model

Subject Areas : Journal of Crop Ecophysiology

Ebrahim Amiri ¹ , Fahimeh Shirshahi ²

1 - Iran lahijan
2 - Young Researchers and Elite Club, Arak Branch, Islamic Azad University, Arak, Iran.

Received: 2017-01-25 Accepted : 2018-02-19 Published : 2018-02-20

Keywords: Maize, yield, Shiraz, SWAP, drip irrigation,

Abstract :

This study was conducted to evaluate the response of hybrid varieties of maize (single cross 260) under drip irrigation treatments in the Fars province in 2012 and 2013 at the Experimental Field of Islamic Azad University of Shiraz. Irrigation levels were 20, 40, 60 and 80% deplection of moisture contents and experiment was conducted in a randomized complete block design. The triats measured were leaf area index, dry matter yield and total biomass in 2012 and the measurements were repeated in 2013 to validate the use of SWAP model. The results showed that simulated yield changes by the use of model, at different levels of irrigation levels in the farm, corresponded with the yield changes in the field. Statistical indices including correlation coefficient (greater than 0.9), t-test (greater than 0.05), the root mean square error and normalized root mean square error (RMSEn) equal to 1.9-6.9, indicate good performance for grain yield and total biomass by using the SWAP model.

References:

· Amiri, E., M. Kavoosi, and F. Kaveh. 2009. Evaluation of crop growth models ORYA2000, SWAP and WOFOST under different types of irrigation management. Journal of Agricultural Engineerin Research. 1(3):13-28. (In Persian(
· Amiri, E., M. Rezaei, M.K. Motamed, and S. Emami. 2010. Evaluation of the crop growth model WOFOST under irrigation management. Agronomy Journal (Pajouhesh & Sazandegi). 90: 9-17. (In Persian).
· Dehghan, H., A. Alizadeh, and S.A. Haghayeghi. 2011. Water balance components estimating in farm scale using simulation model SWAP (Case Study: Neyshabur Region). Journal of Water and Soil. 24(6): 1265-1275. (In Persian)
· Djaman, K., S. Irmak, W.R. Rathje, D.L. Martin, and D.E. Eisenhauer. 2013. Maize evap-otranspiration, yield production functions, biomass, grain yield, harvest index, and yield response factors under full and limited irrigation. Transactions of the American Society of Agricultural and Biological Engineers (ASABE). 56: 373–393.
· Doorenbos, J., and A.H. Kassam. 1979. Yield response to water. FAO Irrigation and Drainage paper, NO 33, Rome, Italy.
· Jiang, Y., X. Xu, Q.Z. Huang, Z.L. Huo, and G.H. Huang. 2015. Assessment of irrigationperformance and water productivity in irrigated areas of the middle Heihe Riverbasin using a distributed agro-hydrological model. Agricultural Water Management. 147: 67–81.
· Karimi goghari, Sh., and R. Asadi. 2012. Evaluation of SWAP model in predicting maize yield under deficit irrigation condition. Journal of Water Research in Agriculture. 26(4):  391-404. (In Persian).
· Khani, M., K. Davari, A. Alizadeh, H. Hashminia, and A. Zolfagharan. 2006. SWAp model assessment for simulating sugar beet yield under different irrigation water quantities and qualities. Irrigation and Drainage Journal of Iran. 2: 107-118. (In Persian).
· Liu, J., S.K. Sun, P.T. Wu, Y.B. Wang, and X.P. Zhao. 2015. Evaluation of crop production, trade, and consumption from the perspective of water resources A case study of the Hetao irrigation district, China, for 1960–2010. Science Total Environment. 505: 1174–1181.
· Roetter, R., C.T. Hoanh, and P.S. Teng. 1998. A systems approach to analyzing land use options for sustainable rural development in South and Southeast Asia. IRRI Discussion Paper Series 28. International Rice Research Institute, Los Banos, Philippines.110 pp.
· Rötter, R.P., T. Palosuo, K.C. Kersebaum, C. Angulo, M. Bindi, and F. Ewert. 2012. Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models. Field Crops Research. 133: 23-36.
· Sezen, S.M., A. Yazar, B. Kapur, and S. Tekin. 2011. Comparison of drip and sprinkler irrigation strategies on sunflower seed and oil yield and quality under Mediter-ranean climatic conditions. Agricultural Water Management. 98: 1153–1161.
· Shirshahi, F., H. Babazadeh, F. Kaveh, and E. Amiri. 2014. Assessment of water use efficiency and predicting wheat yield using SWAP model in partial of droudzan irrigation and drainage network. Water Research in Agriculture. 28(2): 273-283.  (In Persian).
· Singh, R., and J. Singh. 1996. Irrigation planning in cotton through simulation.  Modeling of Irrigation Science. 17: 31–36.
· Singh, R., R.K. Jhorar, J.C. van Dam, and R.A. Feddes. 2006. Distributed ecohydrological modeling to evaluate irrigation system performance in Sirsa district, India II: impact of viable water management scenarios. Journal of Hydrology. 329: 714–723.
· Supit, I., A.A. Hooijer, and C.A. van Diepen. 1994. System description of the WOFOST 6.0 crop simulation model implemented in CGMS. Brussels. 416 pp.
· van Dam, J.C., J. Huygen, J.G. Wesseling, R.A. Feddes, P. Kabat, P.E.V. van Walsum, P. Groenendijk, and C.A. van Diepen. 1997. Theory of SWAP, version 2. Simulation of water flow, solute transported plant growth in the soil-water-atmosphere-plant environment. Report No.71. Department of Water Resources Wagningen Agricultural University.
· Verdinejad, V.R., T. Sohrabi, M. Feizi, N. Heydari, and S.H. Araghinejad. 2010. Patterning different crops yield with saline water irrigation condition using SWAP model. Journal of Water and Soil Science. 20.1(4): 97-111. (In Persian).
· Wang, X.P., G.H. Huang, J.S. Yang, Q.Z. Huang, H.J. Liu, and L.P. Yu. 2015. An assessment of irrigation practices: sprinkler irrigation of winter wheat in the North China Plain. Agricultural Water Management. 159: 197–208.
· Wen, J., J. Li, and Y. Li. 2015. Response of maize growth and yield to different water and nitrogen schemes on very coarse sandy loam soil under sprinkler irrigation in the semi-arid region of China. Irrigation and Drainage. 64(5): 619-636.
· Wösten, J.H.M., A. Lilly, A. Nemes, and C. Le Bas. 1998. Using existing soil data to derive hydraulic parameters for simulation models in environmental studies and in land use planning. Report 156. DLO Winand staring Centre. The Netherlands.
· Xu, X., G.H. Huang, C. Sun, L.S. Pereira, T.B. Ramos, Q.Z. Huang, and Y. Hao. 2013. Assessing the effects of water table depth on water use, soil salinity and wheat yield: searching for a target depth for irrigated areas in the upper Yellow River basin. Agricultural Water Management. 125: 46–60.
· Xue, J., and L. Ren. 2016. Evaluation of crop water productivity under sprinkler irrigation regime using a distributed agro-hydrological model in an irrigation district of China. Agricultural Water Management.178: 350-365.