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Sustainability 2017, 9(3), 353; doi:10.3390/su9030353

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

1
Engineering Department, Harper Adams University, Newport, Shropshire TF10 7BP, UK
2
M3-BIORES research group, Division of Animal and Human Health Engineering, Department of Biosystems, Katholieke Universiteit L, Kasteelpark Arenberg 30, 3001 Leuven, Belgium
*
Author to whom correspondence should be addressed.
Academic Editors: Spyros Fountas and Konstantinos G. Arvanitis
Received: 21 November 2016 / Revised: 2 February 2017 / Accepted: 15 February 2017 / Published: 28 February 2017
View Full-Text   |   Download PDF [735 KB, uploaded 28 February 2017]   |  

Abstract

Globally, the irrigation of crops is the largest consumptive user of fresh water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This paper discusses how incorporating adaptive decision support systems into precision irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil–plant–atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation. View Full-Text
Keywords: precision irrigation; adaptive decision support systems; model predictive control; crop yield; water savings; sustainability precision irrigation; adaptive decision support systems; model predictive control; crop yield; water savings; sustainability
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Adeyemi, O.; Grove, I.; Peets, S.; Norton, T. Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation. Sustainability 2017, 9, 353.

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