Special Issue "Optimization, Control, and Adoption of Irrigation Decision Support Tools"
Deadline for manuscript submissions: closed (20 March 2021) | Viewed by 4756
Interests: water treatment; groundwater brackish; desalination; electrodialysis; arsenic remediation; drip irrigation; development engineering; global engineering
Special Issues, Collections and Topics in MDPI journals
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
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- irrigation decision support
- renewable power
- agricultural sensors
- remote sensing
- agricultural engineering
- sensor applications
- irrigation tools and technologies
- water use efficiency
- Internet of Things (IoT)