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  4. Validation of an Analytical Model to Lower the Cost of Solar-Powered Drip Irrigation Systems for Smallholder Farmers in the Mena Region

Validation of an Analytical Model to Lower the Cost of Solar-Powered Drip Irrigation Systems for Smallholder Farmers in the Mena Region

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sword-2022-01-26T19:03:48.original.xml (130 B)
Original SWORD entry document
Author(s)
Grant, Fiona
•
Sheline, Carolyn
•
Amrose, Susan
•
Brownell, Elizabeth
•
Nangia, Vinay
•
Talozi, Samer
•
Winter, Amos
Date Issued
2020
Journal
Volume 11B: 46th Design Automation Conference (DAC)
Publisher
ASME International
Citation
Grant, Fiona, Sheline, Carolyn, Amrose, Susan, Brownell, Elizabeth, Nangia, Vinay et al. 2020. "Validation of an Analytical Model to Lower the Cost of Solar-Powered Drip Irrigation Systems for Smallholder Farmers in the Mena Region." Volume 11B: 46th Design Automation Conference (DAC).
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Final published version
Abstract
Abstract
Drip irrigation is a micro-irrigation technology that has been shown to conserve water and significantly increase crop yield. This technology could be particularly beneficial to the world’s estimated 500 million smallholder farmers, but drip systems tend to be financially inaccessible to this population. Drip systems require costly components including a pipe network, emitters, a pump and power system. Due to limited access to electricity, many smallholder farmers would require off-grid solutions. Designing reliable, low cost, off-grid drip irrigation systems for smallholder farms could significantly reduce the barrier to adoption. This paper builds on an integrated solar-powered drip irrigation model that was shown to improve upon an existing software. Field trials of the small-scale drip system were conducted on research farms in Jordan and Morocco for a full growing season. Data collected from these field trials are used to validate the hydraulics portion of the systems-level model. In addition, the insights gained from the field trials were formed into design requirements for future iterations of the model. These include optimizing for the system life cycle cost, as opposed to capital cost, the ability to simulate the system operation over a season, the capability to input a user’s irrigation schedule, incorporating locally-available components, and incorporating a system reliability constraint based on more detailed agronomic calculations.
MIT Department
Massachusetts Institute of Technology. Global Engineering and Research Laboratory
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
https://hdl.handle.net/1721.1/139752
DOI of Published Version
https://doi.org/10.1115/DETC2020-22610
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