Authors

1 Assistant Professor, Water Engineering Department, Faculty of Agriculture, Shahid-Bahonar University of Kerman, Kerman, Iran

2 Islamic Azad University Kerman Branch, Kerman, Iran

10.22092/jwra.2013.131417

Abstract

Using mathematical models for irrigation management have great impacts on increasing irrigation efficiency and crop yield. Therefore, in order to evaluate the SWAP model performance in estimating corn production under water stress, a field experiment was conducted on grain maize in Urzuieh plain of Kerman province in Iran, during 2009 and 2010. The experimental design was split plot in randomized block with four replications. Water was used at four levels (100%, 80%, 60% of maize water requirement and a control treatment consisting of the amount of water used by the local farmers) as the main factor and the three varieties of maize (single cross 704, 700,404) were as the sub factor. The results showed perfect compliance of yield and leaf area index (LAI) between values simulated by the model and measured values in the field. In the two study years, R2 between the measured yield and values simulated by the model were 0.99 and 0.998, respectively, while the corresponding R2 for LAI were 0.86 and 0.87. Considering the salinity of irrigation water (EC = 4 dS/m), the volume of water for maximum relative yield (77%) was found to be 11000 cubic meter per hectare. Moreover, evaluation of water salinity levels, indicated 7 present yield reduction per 2 dS/m increase in water salinity. Therefore, calibrated SWAP model can be used as an instrumental tool for calculating all parameters of plant at field scale, with time and cost saving.

Keywords

  • Amiri, S., Noormohamadi, A., Jafari, A. and Chugan, R. 2009. Correlation, regression and path analysis for grain yield and yield components on early maturing hybrids of grain corn. 16: 99-112. (In Farsi).
  • Asadi, R., P. Gaghighatjo and Koohi, N. 2010. Evaluation of solar radiation and temperature based methods for estimating evapotranspiration of Kerman. The first international conference on plant, water, soil and weather modeling. Kerman. Iran.
  • Bastiaanssen, W. G. M., Allen, R. G., Droogers, P., D’urso, G. and Steduto, P. 2007. Twenty five years modeling irrigated and drained soils: State of the Art, Agricultural Water Management, 92: 111-125.
  • Broadcasting Agriculture Organization of Kerman province. 2007. Agriculture Organization of Kerman province, the management plan, the Department of Statistics and Information Technology. (In Farsi).
  • Cakir, R. 2004. Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops. 89: 1-16.
  • Dehghan, H., Alizadeh, A. and Haghayeghi, S. A. 2011. Water balance components estimating in farm scale using simulation model SWAP. Journal of water and soil. 24: 1265-1275. (In Farsi).
  • Doorenbas, J. and Pruitt, W. O. 1975. Guidelines for predicting crop water requirements. FAO irrigation and drainage paper (24).
  • Droogers, P., Torabi, M., Akbari, M. and Pazira, E. 2001. Field-Scale modeling to explore salinity problems in irrigated agriculture. Irrigation and drainage. 50: 77-90.
  • Ghahraman, N., Khalili, A., Liaghat, A. and Esmaiilnia, S. 2004. Investigation of SWAPCROP Model to evaluate wheat and barley yields in Karaj. The 2nd national student conference on water and soil resources. 23rd and 24th ordibehesht, 2004, Agriculture School, Shiraz. (In Farsi).
  • Homayonfar, F., Asadi R. and Arab, M. 2011. Assess the effect of water on soil moisture on corn grain yield using drip irrigation system in Kerman province. Eleventh Conference on Irrigation and reduce evaporation. Kerman. Iran.
  • Huygen, J., Van Dam, J. and Krose, J. 2000. Introduction to SwapGui, the Swap 2.0 graphical user interface. Unpublished manual. DLO-Staring Centre and Wageningen Agricultural University. 98p. Record No: H23829.
  • Khani, M., Davari, K., Alizadeh, A., Hashminia, H and Zolfagharan, A. 2008. SWAP model assessment for simulating sugar beet yield under different irrigation water quantities and qualities. Journal of Irrigation and Drainage. 2: 107-118. (In Farsi).
  • Kiani, A and Homaee, M. 2007. Evaluation SWAP model for simulation of water and solute transport in soil profit. Journal of Agricultural Engineering Research. 8: 13-30. (In Farsi).
  • Kroes, J and van Dam, J. 2003. Reference manual SWAP version 3.03. Altera Green World Research, Altera report 773. Wageningen University and Research Center, Wageningen, the Netherlands, 211 p. ISSN: 1566-7197.
  • Loauge, K and Green, R. 1991. Statistical and graphical methods for evaluating solute transport models: Overview and application, J. Cont. Hydrol. 7: 51-73.
  • Mostafazadeh-fard, B., Mansouri, H., Mousavi, F and Feyz, M. 2009. Effects of Different Levels of Irrigation Water Salinity and Leaching on Yield and Yield Components of Wheat in an Arid Region. J. Irri. And Drai. Eng. 135: 363-378.
  • Nahvinia, M., Shahidi, A., Parsinejad, M and Karimi, B. 2011. Assessing the performance of SWAP model in estimating the production of wheat under water stress and salinity in Birjans area. Journal of Water Research in Iran. 6: 43-58. (In Farsi).
  • Qureshi, S., Madramoto, C and Dodds, G. 2002. Evaluation of irrigation schemes for sugarcane in sindh, Pakistan, using SWAP93. Agricultural water management. 54: 37-48.
  • Ruiz, M and Utset, A. 2003.Models for predicting water use and crop yields. A Cuba experience. Available on the: ictp.it/~pub_off/lectures/lns018/28Ruiz.pdf. 323-328.
  • Saberi, A., Mazaheri, A and Heidari, H. 2007. Effect of vary density planting and arrangement on physiological indices and dry matter trend of corn. 13: 64-79. (In Farsi).
  • Singh, R., van Dam, J and Feddes, R. 2006. Water productivity analysis of irrigated crops in Sirsa district. India. Agricultural Water Management 82: 253-278.
  • Singh, R. 2004. Simulation on direct and cyclic use of saline waters for sustaining Cotton-Wheat in a semi-arid area of north-west India, J. of Agri. Water Manag., 66: 153-162.
  • Singh, R. 2005. Water productivity analysis from field to regional scale: integration of crop and soil modeling, remote sensing and geographical information, PhD thesis, Wageningen University, Wageningen, The Netherlands
  • Utset, A., Velicia, B., delRio, R., Morillo, J., Centeno A and Martinez, C. Calibrating and validating an agrohydrological model to simulate sugerbeet water use under mediterranean condition. Agricultural Water Management, 94: 11-21.
  • Van Dam J., Singh, R., Bessembinder, J., Bastiaanssen, W., Jhorar, P., Kroes, J and Droogers, P. 2006. Assessing options to increase water productivity in irrigated river basins using remote sensing and modeling tools. Water Res. Development. 22: 115-133.
  • Van Dam, J., Groenendijk, P., Hendriks, R and Kroes, J. 2008. Advances of modeling water flow in variably saturated soils with SWAP. Vadose Zone Journal. 7: 640-653.
  • Van Dam J., Huygen, J., Feddes, R., Kabat, P., VanWalsum, P., Groenendijk, P and Diepen, C. 1997. Theory of SWAP version 2.0. Technical Document 45. Wageningen Agricultural University and DLO Winand Staring Center.
  • Van Genuchten, M., Leij, N and Yates, S.. 1991. The RETC code for quantifying the hydraulic functions of unsaturated soils. Report No. EPA/600/2-91/065. Ada. Okla.u.s. Environmental protection Agency .Kerr, R.S. Environmental Research laboratory.