DESIGN OF CENTER PIVOT IRRIGATION SYSTEM BASED ON SIMULATION MODEL TECHNIQUE | ||||
Misr Journal of Agricultural Engineering | ||||
Article 13, Volume 31, Issue 4, October 2014, Page 1441-1458 PDF (1.41 MB) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/mjae.2014.98396 | ||||
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Authors | ||||
Yousria Atef1; Abdel-Ghany M. El-Gindy1; Yasser E. Arafa1; Essam A. Wassif2 | ||||
1Agric. Eng. Dept., Fac. of Agric., Ain Shams Univ., Egypt. | ||||
2Agric. Eng. Research Institute, ARC, Egypt. | ||||
Abstract | ||||
Centre pivot irrigation system is a promising and precise system, for increasing the utilization efficiency of unit water. Hence, A CPIM simulation model has been developed and validated, however, A CPIM model is based on crop type, weather data, and soil characteristics. The model comprises five sub-models for: (a) main sub-model; (b) data entry sub-model; (c) weather sub-model; (d) irrigation sub-model; and (e) results sub-model. The most important simulation outputs of the CPIM model include nozzle flow rate (m3/h), application rate (mm/h), and throw diameter (m). These outputs (outputs of 9 scenarios) were compared with observed/manufactured data for the calibration and validation of the model. Results of this comparison show that differences in model accuracy owing to different variables affecting the design and management of the center pivot were not significant. The relationships between the observed/manufactured and simulated results have a good correlation with high value of coefficient of determination and the best models are as follows: 1- Nozzle flow rate (m3/h) was in scenario 5 with R2 = 0.967 and explained by an exponential model: Q SIM = 0.1067e4.1131 (Q obs). 2- Application rate (mm/h) was in all scenarios with a very high R2 and explained by a linear model. 3- Throw diameter (m) was in scenario 1 with R2 = 0.942 and explained by a power model: Dw SIM = 3.9064 (Dw MFD)0.4361. | ||||
Keywords | ||||
Simulation; Model; Validation; Verification; Center pivot | ||||
References | ||||
Al Ghobari, H. M. (2004). Sprinkler Irrigation systems. Textbook, College of Food and Agricultural Sciences, King Saud University, Saudi Arabia (Arabic).
Bittinger, M. W. and R. A. Longenbaugh (1962). Theoretical distribution of water from a moving irrigation sprinkler. Trans. Amer. Soc. Agric. Eng. 5(1): 26-30.
Bremond, B., and B. Molle (1995). Characterization of rainfall under center-pivot: influence of measuring procedure. Journal of Irrigation and Drainage Engineering: ASCE, 121(5): 347–353.
Cape, J. (1998). Using software to review sprinkler performance. Irrigation Australia, 13(3): 18-20.
Carrion, P., J. M. Tarjuelo and J. Montero (2001). SIRIAS: A simulation model for sprinkler irrigation 1, Description of the model. Irrigation Science, 20(2): 73-84.
Faci, J. M., R. Salvador, E. Playán and H. Sourell (2001). ‘‘Comparison of fixed and rotating spray plate sprinklers’’. Journal of Irrigation and Drainage Engineering: ASCE, 127(4):224–233.
Heermann, D. F. and K. Stahl (2004). Center pivot evaluation and design package (CPED) – Users’ manual. Ft. Collins, CO, USA: USDA-ARS-NPA-WMU.
Heermann, D. F. and P. R. Hein (1968). Performance characteristics of self-propelled center pivot sprinkler irrigation system. Transactions of the ASAE, 11(1): 11–15.
Keller, J. and R. D. Blienser (1990). Sprinkler and Trickle Irrigation. Van Nostrand Reinhold. New York. Pp. 99-115.
Merkley, G. P. and R. G. Allen (2007). Sprinkler and Trickle Irrigation. Lecture Notes, Utah State Univ., Logan, UT. Biological and Irrigation Engineering Department.
Montero, J., J. M. Tarjuelo and P. Carrion (2001). SIRIAS: A simulation model for sprinkler irrigation 2, Calibration and validation of the model. Irrigation Science, 20(2): 85-98.
Smith, R. J., M. H. Gillies, G. Newell and J. P. Foley (2008). A decision support model for travelling gun irrigation machines. Biosystems Engineering, 100(1): 126-136.
Razali, N. M. and Y. B. Wah (2011). Power comparisions of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. Journal of Statistical Modeling and analytics, 2(1), 21-33.
Doane, D. P. and L. E. Seward (2011). Measuring Skewness Journal of Statistics Education, 19(2): 1-18.
Martin, W. E. and K. D. Bridgmon (2012). Quantitative and Statistical Research Methods: From Hypothesis to Results. John Wiley and Sons, Somerset, NJ, US.
Summers, C. G. and D. H. Putnam (2008). Irrigated Alfalfa Management for Mediterranean and Desert Zones, University of California, Agriculture and Natural Resources.
Chung, C. A., 2003. Simulation Modeling Handbook: A Practical Approach, Taylor & Francis.
Evans, R. G., S. Han, L. G. James and M. W. Kroeger (1993). CPIM- A computer simulation program for center pivot irrigation systems. ASAE Paper No. 93-3065. St. Joseph, MI, USA: ASAE. | ||||
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