Evaluating the Efficiency of SURFACE and SRFR Models in Simulation of Application Efficiency of Border Irrigation in Wheat Farms
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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:

Due to the high sensitivity of irrigation efficiency management in farms and to reduce water consumption in agriculture, it is necessary to optimise the application efficiency of farms using the relationships governing water management as well as the advanced models in this field. SURFACE and SRFR are models which can be used for farms’ water management. The SURFACE model has a simpler structure. By entering details of the irrigation method, soil penetration, irrigation time, area of irrigation, and the farm’s water delivery schedule, it is possible to investigate the irrigation and applicable management approaches and choose the most appropriate method. Similar parameters can be investigated in the SRFR model, in addition to optimising the dimensions, application efficiency indices, and uniform distribution. In this research, using the measured data of border irrigation in the crop year of 2015-2016, the two models of SURFACE and SRFR for wheat cultivation conditions are evaluated for a better estimation of water application efficiency in farms. The results show that the SRFR model estimated the application efficiency approximately 3.2% lower and compared to the average of data has a 12% error. However, the SURFACE model simulates the application efficiency with an error of 7%. The optimised dimension of border irrigation was estimated by these models and were applied in the second crop year (2016-2017). The results show that these models are very powerful in the estimation of border irrigation and can provide suitable results with 6% to 12% error. The comparison of these two models has also shown an error level of approximately 5% and 9% for the SURFACE and SRFR models, respectively. Hence, the SURFACE model is more accurate for irrigation management.

Language:
Persian
Published:
Journal of Water and Sustainable Development, Volume:6 Issue: 3, 2020
Pages:
79 to 87
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