Development and simulation of sensor-based irrigation control strategies for cotton using the VARIwise simulation framework

McCarthy, Alison; Hancock, Nicola; Raine, Steven R.

doi:10.1016/j.compag.2013.12.014

Cited by 17 publications

(11 citation statements)

References 18 publications

(16 reference statements)

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“…However, the performance of these irrigation systems in field applications is affected by many factors, such as field attributes, the spatial resolution of the sensors used in irrigation management and temporal resolution of data inputs, as well as unexpected environmental conditions. Hence, adaptive irrigation management strategies and active research support are required to enhance the adoption and application of VRI [20,50]. by opening or closing individual nozzles and by changing the speed of the pivot [45].…”

Section: Variable-rate Irrigation Technologiesmentioning

confidence: 99%

Agronomic Basis and Strategies for Precision Water Management: A Review

Neupane

Guo

2019

Agronomy

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Agriculture faces the challenge of feeding a growing population with limited or depleting fresh water resources. Advances in irrigation systems and technologies allow site-specific application of irrigation water within the field to improve water use efficiency or reduce water usage for sustainable crop production, especially in arid and semi-arid regions. This paper discusses recent development of variable-rate irrigation (VRI) technologies, data and information for VRI application, and impacts of VRI, including profitability using this technology, with a focus on agronomic factors in precision water management. The development in sprinkler systems enabled irrigation application with greater precision at the scale of individual nozzle control. Further research is required to evaluate VRI prescription maps integrating different soil and crop characteristics in different environments. On-farm trials and whole-field studies are needed to provide support information for practical VRI applications. Future research also needs to address the adjustment of the spatial distribution of prescription zones in response to temporal variability in soil water status and crop growing conditions, which can be evaluated by incorporating remote and proximal sensing data. Comprehensive decision support tools are required to help the user decide where to apply how much irrigation water at different crop growth stages to optimize water use and crop production based on the regional climate conditions and cropping systems.

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Section: Variable-rate Irrigation Technologiesmentioning

confidence: 99%

Agronomic Basis and Strategies for Precision Water Management: A Review

Neupane

Guo

2019

Agronomy

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“…Closed-loop irrigation strategies aim to irrigate: when the soil moisture content reaches a certain threshold [103][104][105]; when plant sensors indicate a certain stress threshold [93,106,107] or with feedback from crop simulation models with the aim of attaining a certain yield, crop physiological response or economic objective [108]. These closed-loop irrigation strategies have been shown to improve water use efficiency in the production of horticultural crops under protected environments.…”

Section: Decision Supportmentioning

confidence: 99%

“…In control theory an adaptive control system is generally accepted as a control system able to adjust its controller parameters based on sensor feedback from a process, such that the controlled process behaves in a desirable way [11]. McCarthy et al [108] noted that an adaptive decision support system for irrigation may either be sensor-based if they use direct sensor measurements for the irrigation strategy or model-based if they use a calibrated simulation model to aid irrigation decisions.…”

Section: Adaptive Decision Supportmentioning

confidence: 99%

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Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

et al. 2017

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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.

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“…Conventional center pivot systems manage a field as a uniform unit, thus ignoring the heterogeneity across the field, and often management decisions are based on average field conditions (i.e. average soil hydraulic properties, average soil water content (SWC); McCarthy et al 2014). Consequently, expected crop yield may differ in sub-regions of a field due to variations in SWC and physical properties.…”

Section: Introductionmentioning

confidence: 99%

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

et al. 2018

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Precision agriculture offers the technologies to manage for infield variability and incorporate variability into irrigation management decisions. The major limitation of this technology often lies in the reconciliation of disparate data sources and the generation of irrigation prescription maps. Here the authors explore the utility of the cosmic-ray neutron probe (CRNP) which measures volumetric soil water content (SWC) in the top ~ 30 cm of the soil profile. The key advantages of CRNP is that the sensor is passive, non-invasive, mobile and soil temperature-invariant, making data collection more compatible with existing farm operations and extending the mapping period. The objectives of this study were to: (1) improve the delineation of irrigation management zones within a field and (2) estimate spatial soil hydraulic properties to make effective irrigation prescriptions. Ten CRNP SWC surveys were collected in a 53-ha field in Nebraska. The SWC surveys were analyzed using Empirical Orthogonal Functions (EOFs) to isolate the underlying spatial structure. A statistical bootstrapping analysis confirmed the CRNP + EOF provided superior soil hydraulic property estimates, compared to other hydrogeophysical datasets, when linearly correlated to laboratory measured soil hydraulic properties (field capacitydigitalcommons.unl.edu F i n k e n b i n e r e t a l . i n P r e c i s i o n A g r i c u lt u r e , 2 0 1 8 2estimates reduced 20-25% in root mean square error). The authors propose a soil sampling strategy for better quantifying soil hydraulic properties using CRNP + EOF methods. Here, five CRNP surveys and 6-8 sample locations for laboratory analysis were sufficient to describe the spatial distribution of soil hydraulic properties within this field. While the proposed strategy may increase overall effort, rising scrutiny for agricultural water-use could make this technology cost-effective.

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Development and simulation of sensor-based irrigation control strategies for cotton using the VARIwise simulation framework

Cited by 17 publications

References 18 publications

Agronomic Basis and Strategies for Precision Water Management: A Review

Agronomic Basis and Strategies for Precision Water Management: A Review

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

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