Regional modeling of wheat yield production using the distributed agro-hydrological SWAP: (case study: Doroudzan irrigation and drainage network)
Subject Areas : Agroecology JournalElnaz Noroozi 1 , Hosein Babazadeh 2 , Majid Vazifehdoost 3 , Fereidoon Kaveh 4
1 - Ph.D. Student, respectively, Science and Research Branch, Islamic Azad University of Tehran, Tehran, Iran.
2 - Assistant Prof, respectively, Science and Research Branch, Islamic Azad University of Tehran, Tehran, Iran.
3 - Assistant Prof., Agriculture Faculty, Gilan University, Gilan, Iran.
4 - Associate Prof., respectively, Science and Research Branch, Islamic Azad University of Tehran, Tehran, Iran.
Keywords: simulation, production, yield, Wheat, distributed SWAP,
Abstract :
Many decisions and policies in water management are made in a spatial scale larger than farm scale. In this study, the distributed SWAP model was evaluated to simulate wheat yield production in the Doroudzan irrigation and drainage network (Fars province, Iran) in wet, normal and dry years. The study area was divided into 86 simulation units and yield production was determined in each spatial unit with the distributed SWAP. MATLAB program was used for regionalizing the SWAP model and making relationship between this model and input data in each simulation unit. The goodness-of-fit measures, such as correlation coefficient and maximum error were calculated as 88% and 0.94 ton/ha, respectively. In addition, the determined mean square error was less than standard deviation and the modeling efficiency was estimated satisfactorily. In this research, yield production in the simulation period was evaluated higher than the observed values. In farms located at the end of the network, the error percentage of the simulated performance was higher than other spatial units due to water deficit and soil salinity. In general, since there was a good consistency between simulated and observed crop production in Doroudzan network, distributed SWAP model can be used with a good accuracy to simulate and predict yield production and to manage irrigation network.
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