Optimization of the Cropping Pattern Using AquaCrop-GIS (Case Study: Dehloran Plain, Ilam Province)

Document Type : Research Paper

Authors

1 Ms.c Student Science and soil Engineering Department, Ilam University

2 Ilam university

3 Department of Water Engineering, College of Agriculture, Ilam University

Abstract

Optimization of cropping pattern is one of the most important methods to increase water productivity and protect the limited water resources throughout the country. The objective of this study was optimization of cropping pattern in Dehloran plain based on spatial variations of water quality, water availability, chemical and physical characteristics of soil, and groundwater level. To this end, the Dehloran plain was divided into four zones: area covered by the Meymeh networks, Doyraj, Tropical systems and lands covered by wells. Then, AquaCrop-GIS software was calibrated and validated by filed data. Finally, the production functions were extracted and the cropping pattern was optimized using the linear programming method and the objective function of maximum net benefit. The results showed that AquaCrop-GIS are a robust tool for analyzing spatial variation of parameters affecting yield and cropping pattern in a plain. Moreover, crop pattern optimization related to water quality and quantity features beside soil physical and chemical properties could be influential on the net benefit and water productivity to be increased by 30 to 120 percent in different regions of Dehloran plain.

Keywords

Main Subjects

References

Abrha, B., Delbecque Raes, D., Tsegay, A., Todorovic, M., Heng, L., Vanutrecht, E., Geerts, S., Garcia-Vila, M., Deckers, S. (2012). Sowing strategies for barley (Hordeum Vulgare L.) based on modelled yield response to water with AquaCrop. Expl. Agric. 48 (2), 252–271.
Alizadeh, H.A., Nazari, B., Parsinejad, M., Ramezani Eetedali, H., and Janbaz, H.R. (2010). Evaluation of AquaCrop model on wheat deficit irrigation in Karaj area. Iran J. Irrig Drain 2,273–283. (In Persian with English abstract).
Chiu, Y. C., Nishikawa, T., and Yeh, W. W. G. (2010). Optimal pump and recharge management model for nitrate removal in the Warren Groundwater basin, California. J Water Res. Pl, 136(3), 299-308.
 Farahani H.J., Izzi G., and Oweis T.Y. (2009). Parameterization and evaluation of the Aquacrop model for full and deficit irrigated Cotton. Agron. Agronomy journal, 101(3), 469-476.
Fereres, E., Soriano, M.A. (2007). Deficit irrigation for reducing agricultural water use. J. Exp. Bot. 58, 147–159.
García-Vilaa, M., and Fereresa, E. (2012). Combining the simulation crop model AquaCrop with an economic model for the optimization of irrigation management at farm level. Europ. J. Agronomy 36, 21– 31.
Ghasemi, M.M., Karamouz, M. and Shui, L.T.(2016). Farm-based cropping pattern optimization and conjunctive use planning using piece-wise genetic algorithm (PWGA): a case study. Modeling Earth Systems and Environment, 2(1), 1-12.
Hassani S, Ramroodi M, Naghashzadeh M. (2016). Designing cropping pattern by using analytical hierarchy process to allow for optimal exploitation of water. Electronic Journal of Biology. 12, 43-47.
 Heng, L. K., Hsiao, T. C., Evett, S., Howell, T., and Steduto, P. (2009). Validating the FAO AquaCrop model for irrigated and water deficient field maize. American Society of Agronomy, 101, 488-498. 30.
 Hsiao, T. C., Heng, L. K., Steduto, P., Rojas-Lara, B., Raes, D., and Fereres, E. (2009). AquaCrop-the FAO crop model to simulate yield response to water, III: Parameterization and testing for maize. Agronomy Journal, 101, 448-459.
Jiang, L., Ting, Z., Xiaomin, Maoa., Adebayo, A. (2016). Modeling crop water consumption and water productivity in the middle reaches of Heihe River Basin. Computers and Electronics in Agriculture. 123,242–255.
Jiang, Y., Xu, X., Huang, Q.Z., Huo, Z.L., Huang, G.H. (2015). Assessment of irrigation performance and water productivity in irrigated areas of the middle Heihe River Basin using a distributed agro-hydrological model. Agr. Water Manage. 147, 67–81.
Kangrang, A., & Compliew, S. (2010). An application of linear programming model for planning dry-seasonal irrigation system. Trends in Applied Sciences Research, 5(1), 64-70.
Kim, D., Kaluarachchi, J. (2015). Validating FAO AquaCrop using Landsat images and regional crop information. Agr. Water Manage. 149, 143–155.
Kumar, P., Sarangi, A., Singh, D. K., and Parihar, S. S. (2014). Evaluation of AquaCrop model in predicting wheat yield and water productivity under irrigated saline regimes. Irrigation and Drainage, 63, 474–487.
Langhorn, C.(2015). Simulation of climate change impacts on selected crop yields in southern Alberta (Doctoral dissertation, Lethbridge, Alta: University of Lethbridge, Dept. of Geography).
Lorite, I.J., García-Vila, M., Santos, C., Ruiz-Ramos, M., Fereres, E. (2013). AquaData and AquaGIS: two computer utilities for temporal and spatial simulations of water-limited yield with AquaCrop. Comput. Electron. Agr. 96 (96), 227–237.
Mirkarimi, S. H., Joolaie, R., Eshraghi, F., & Abadi, F. S. B. (2013). Application of fuzzy goal programming in cropping pattern management of selected crops in Mazandaran province: Case study of Amol township. International Journal of Agriculture and Crop Sciences, 6(15), 1062-1067.
Paredes, P., Wei, Z., Liu, Y., Xu, D., Xin, Y., Zhang, B., Pereira, L.S. (2015). Performance assessment of the FAO AquaCrop model for soil water, soil evaporation, biomass and yield of soybeans in North China Plain. Agr. Water Manage. 152, 57–71.
Raes, D., Steduto, P., Hsiao, T. C., and Fereres, E.(2009). AquaCrop-The FAO crop model for predictingyield response to water: II. Main algorithms and soft ware description. Agron. J. 101, 438-447
Raes, D., Steduto, P., Hsiao, T.C., Fereres, E. (2013). Refernce Manual: AquaCrop Plug -in Program Version (4.0). FAO, Land and Water Division, Rome, Italy.              
Shekari, H. (2017). Optimization of cropping pattern in fields with arid and hot conditions for different crops in Dehloran area. PhD thesis.
Shreedhar, R., Hiremath, CG., Shetty, GG. (2015). Optimization of Cropping pattern using Linear Programming Model for Markandeya Command Area. International Journal of Scientific & Engineering Research. 6(9),1311-1326.
Singh, A.K., R. Tripathy, and U.K. Chopra. 2008. Evaluation of CERESWheat and CropSyst models for water—Nitrogen interactions in wheat crop. Agricultural water management. 95:776–786.
Steduto, P., Hsiao, T.C., Raes, D., Fereres, E. (2009). AquaCrop—the FAO crop model to simulate yield response water: I concepts and underlying principles. Agron. J.101 (3), 426–437.
Tomohari, H., Okamoto, K., yoshihiro, M., Nohara, D. 2015. An optimization scheme of cropping pattern under the variation of water and climate condition. Proceeding of the 36th IAHR World Congress. 28 June – 3 July, 2015, The Hague, the Netherlands.
Vanuytrecht, E., Raes, D., Steduto, P., Hsiao, T.C., Fereres, E., Heng, L.K., Garcia Vila, M., Mejias Moreno, P. (2014). AquaCrop: FAO’s crop water productivity and yield response model. Environ. Model. Softw. 62, 351–360.
Voloudakis, D., Karamanos, A., Economou, G., Kalivas, D., Vahamidis, P., Kotoulas, V., Kapsomenakis, J., Zerefos, C. (2015). Prediction of climate change impacts on cotton yields in Greece under eight climatic models using the AquaCrop crop simulation model and discriminant function analysis. Agr. Water Manage. 147, 116–128.
 
 
 
 
Iranian Journal of Soil and Water Research
Volume 49, Issue 4
July and August 2018
Pages 865-877

Files

Share

How to cite

Statistics