Precision Agriculture and Irrigation

Document Type : review paper

Authors

• rasool pordel noughabi
• Fatemeh Attarzadeh

Ferdowsi university of mashhad

10.22067/jwsd.v5i2.69880

Abstract

Agriculture uses a significant portion of water consumption. Therefore, the policy of optimal management of water consumption is essential. To achieve this, it is necessary to improve the design and use of advanced technologies and management. Precision irrigation creates coordination between advanced irrigation management, monitoring and investigation of data, modeling, and control. The purpose of this system is to automatically and continuously adjust the irrigation application system to a desired performance, and account for any variability (temporal or spatial) in crop water requirements or water intake across the field. This article describes the latest hardware and software technologies for precision irrigation on both farm-scale and larger regional scales, such as soil moisture mapping, wireless sensor networks, and precision irrigation management. Finally, trends for advanced irrigation technologies are presented.

Keywords

• precision irrigation
• Rael time data
• Water use efficiency

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References

اردمه، م.ر. 1394. طراحی و ساخت یک سامانه‌ی اتوماسیون آبیاری شیاری به‏صورت به‌هنگام به کمک میکروکنترلرهای AVR و ارزیابی عملکرد آن. پایان‌نامه کارشناسی ارشد. دانشگاه فردوسی مشهد. مشهد. ایران.

درگاه شبکه مطالعات سیاست‌گذاری عمومی. 1394.

http://npps.ir/ArticlePreview.aspx?id=61518

Broring A., Echterhoff J., Jirka S. and et al., 2011. New generation sensor web enablement. Sensors, 11: 2652–2699.

Cardenas-Lailhacar B., Dukes M.D. and Miller G.L. 2010. Sensor-based automation of irrigation on bermudagrass during dry weather conditions. Journal of Irrigation and Drainage Engineering, 136(3): 161–223

Carrion P., Tarjuelo J.M. and Montero J. 2001. Sirias: A simulation model for sprinkler irrigation 1, Description of the model. Irrigation Science, 20(2): 73–84.

Evans R.G., Iversen W.M. and Kim Y. 2012. Integrated decision support, sensor networks, and adaptive control for wireless site-specific sprinkler irrigation.Applied Engineering in Agriculture, 28(3): 377–387.

Falkenberg N.R., Piccinni G., Cothren J.T., Leskovar D.I. and Rush C.M. 2007. Remote sensing of biotic and abiotic stress for irrigation management of cotton. Agriculture Water Management, 87: 23–31.

Foley J. 2011. Performance improvement of centre pivots and lateral moves. PhD Dissertation, Faculty of Engineering and Surveying, University of Southern Queensland.

Gillies M.H., Smith R.J., Williamson B. and Shanahan M. 2010. Improving performance of bay irrigation through higher flow rates. Australian Irrigation Conference and Exhibition .Irrigation Australia Limited. Mascot, NSW, Sydney.

Gonzalez-Dugo V., Zarco-Tejada P., Nicolas, E. and et al. 2013. Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard. Precision Agriculture, 14(6): 660–678.

Hedley C.B., Roudier P., Yule I.J., Ekanayake J. and Bradbury S. 2013. Soil water status and water table modelling using electromagnetic surveys for precision irrigation scheduling. Geoderma, 199: 22–29

Işık M.F., Sönmez Y., Yılmaz C., Özdemir V. and Yılmaz E.N. 2017. Precision Irrigation System (PIS) Using Sensor Network Technology Integrated with IOS/Android Application. Applied Sciences, 7(9): 891.

Jonard F., Weihermuller L., Jadoon K.Z. and et al. 2011. Mapping field-scale soil moisture with L-band radiometer and ground-penetrating radar over bare soil. IEEE Transactions on Geoscience and Remote Sensing, 49: 2863–2875.

Kelly B.F.J., Acworth R.I. and Greve A.K. 2011. Better placement of soil moisture point measurements guided by 2D resistivity tomography for improved irrigation scheduling. Soil Research, 49: 504–512.

Khatri K.L. and Smith R.J. 2007. Toward a simple real-time control system for efficient management of furrow irrigation. Irrigation and Drainage, 56(4): 463–475.

Kseneman M., Gleich D. and Potocnik B. 2012. Soil-moisture estimation from TerraSAR-X data using neural networks. Machine Vision and Applications, 23: 937–952.

Lyle W.M. and Bordovsky J.P. 1983. LEPA irrigation system evaluation. Transactions of the ASAE, 26: 776–781.

Montero J., Tarjuelo J.M. and Carrion P. 2001. Sirias: A simulation model for sprinkler irrigation 2. Calibration and validation of the model. Irrigation Science, 20(2): 85–98.

Niblack M. and Sanchez C.A. 2008. Automation of surface irrigation by cut-off time or cut-off distance control. Applied Engineering in Agriculture, 24(5): 611–614.

O’Shaughnessy S.A. and Rush, C. 2014. Precision agriculture: irrigation.

Peters R.T., Evett S.R. 2008. Automation of a centre pivot using the temperaturetime-threshold method of irrigation scheduling. Journal of Irrigation and Drainage Engineering ASCE, 134: 286–291.

Precision Irrigation. 2014. Available at:

http://www.precisionirrigation.co.nz/ (accessed 14.01.14).

Rowshon M.K., Amin M.S.M., Lee T.S., Shariff R.M. 2009. GIS-integrated rice irrigation management information system for a river-fed scheme. WaterResources Management, 23: 2841–2866.

Schache M. 2011. Identifying best management practice through irrigation benchmarking: Would you like probes with your drippers? In: Irrigation Australia, Irrigation & Drainage Conference, Launceston, Tasmania. Mascot, NSW, Sydney: Irrigation Australia Limited.

Smith R.J., Raine S.R. and Minkovich J. 2005. Irrigation application efficiency and deep drainage potential under surface irrigated cotton. Agricultural Water Management, 71(2): 117–130.

Smith R.J., Gillies M.H., Newell G. and Foley J.P. 2008. A decision support model for travelling gun irrigation machines. Biosystems Engineering, 100(1): 126–136.