Optimization, Control, and Adoption of Irrigation Decision Support Tools

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Technology".

Deadline for manuscript submissions: closed (20 March 2021) | Viewed by 5374

Special Issue Editor

Global Engineering and Research Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
Interests: water treatment; groundwater brackish; desalination; electrodialysis; arsenic remediation; drip irrigation; development engineering; global engineering

Special Issue Information

Dear Colleagues,

Over one billion people are facing severe water scarcity at least one month of the year, and agricultural irrigation accounts for the vast majority (more than 70%) of our freshwater use. Irrigation decision support (IDS) tools have the potential to reduce water consumption and improve crop productivity by optimizing the volume of water delivered and the timing of irrigation events, based on models and measurements of plant physiology, evapotranspiration, soil hydrology, and groundwater recharge. Employing IDS tools can make it easier to integrate with renewable power sources, allowing systems to optimize irrigation timing in a way that maximizes the utilization of the variable power source, reducing battery requirements and minimizing costs. IDS tools can also integrate information from crop and soil sensors, remote sensing equipment, Internet of Things (IoT)-enabled devices, regional databases, and other sources, to produce crop-specific and location-specific water demand predictions. IDS tools have demonstrated significant water savings in theoretical and pilot studies, indicating their potential to address water scarcity. However, initial adoption among farmers has been limited and slow. To understand the current state, unrealized potential, and challenges of this field, this Special Issue invites recent findings related to the optimization, control, and adoption of IDS tools. Relevant literature includes (but is not limited to):

  • The creation, validation, and exploration of theory and optimization models to design low-cost and environmentally sustainable irrigation systems, including their integration with renewable power sources;
  • The creation, validation, and exploration of theory and optimization models to support operational decisions that minimize water use and maximize crop productivity based on predictive models, inputs from sensors, and other sources;
  • The design and validation of the control theory and hardware necessary to implement an IDS strategy in the field; and
  • Current implementations and challenges regarding the adoption and use of IDS tools and IDS-enabled systems by farmers in the field.

Dr. Susan Amrose
Guest Editor

Manuscript Submission Information

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Keywords

  • irrigation decision support
  • optimization
  • renewable power
  • solar
  • agricultural sensors
  • remote sensing
  • agricultural engineering
  • sensor applications
  • adoption
  • irrigation tools and technologies
  • water use efficiency
  • Internet of Things (IoT)
  • controls
  • controllers

Published Papers (1 paper)

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Research

12 pages, 603 KiB  
Article
Simulation of Internet of Things Water Management for Efficient Rice Irrigation in Rwanda
by Peace Bamurigire, Anthony Vodacek, Andras Valko and Said Rutabayiro Ngoga
Agriculture 2020, 10(10), 431; https://doi.org/10.3390/agriculture10100431 - 25 Sep 2020
Cited by 14 | Viewed by 4378
Abstract
The central role of water access for agriculture is a clear challenge anywhere in the world and particularly in areas with significant seasonal variation in rainfall such as in Eastern and Central Africa. The combination of modern sensor technologies, the Internet, and advanced [...] Read more.
The central role of water access for agriculture is a clear challenge anywhere in the world and particularly in areas with significant seasonal variation in rainfall such as in Eastern and Central Africa. The combination of modern sensor technologies, the Internet, and advanced irrigation equipment combined in an Internet of Things (IoT) approach allow a relatively precise control of agricultural irrigation and creating the opportunity for high efficiency of water use for agricultural demands. This IoT approach can thereby increase the resilience of agricultural systems in the face of complex demands for water use. Most previous works on agricultural IoT systems are in the context of countries with higher levels of economic development. However, in Rwanda, with a low level of economic development, the advantages of efficient water use from the application of IoT technology requires overcoming constraints such as lack of irrigation control for individual farmers, lack of access to equipment, and low reliability of power and Internet access. In this work, we describe an approach for adapting previous studies to the Rwandan context for rice (Oryza sativa) farming with irrigation. The proposed low cost system would automatically provide irrigation control according to seasonal and daily irrigational needs when the system sensors and communications are operating correctly. In cases of system component failure, the system switches to an alternative prediction mode and messages farmers with information about the faults and realistic irrigation options until the failure is corrected. We use simulations to demonstrate, for the Muvumba Rice Irrigation Project in Northeast Rwanda, how the system would respond to growth stage, effective rainfall, and evapotranspiration for both correct operation and failure scenarios. Full article
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