Improved Water and Economic Sustainability with Low-Input Compact Bed Plasticulture and Precision Irrigation

Document Type

Article

Publication Date

7-1-2019

Abstract

Raised-bed plasticulture is used globally to produce fresh market vegetables, fruits, and other crops. A novel compact bed geometry, designed to improve the system efficiency of plasticulture, was evaluated for its ability to reduce water and other inputs and facilitate the adoption of precision irrigation using savings from reduced input costs. Using measurements and modeling (HYDRUS), precision soil moisture-based irrigation management (SM) and grower-based irrigation management (GR) were evaluated for conventional and compact beds. Similar to previous studies, SM reduced applied irrigation by 20% and deep percolation losses by 30% compared to GR for conventional beds. However, the significant investment needed to buy and maintain modern soil moisture measurement systems is likely to limit the adoption of SM. Compact bed geometries, taller and narrower than conventional beds, can sustain yields while reducing inputs of water, pesticide, fertilizer, fuel, and plastic. Cost savings of $154-$789/ha associated with the reduced inputs for compact beds can cover the cost of a soil-moisture sensor network with an automated irrigation system for a typical 65-ha fresh produce farm. Model simulations showed that compact beds with SM reduced irrigation volume by 8%-36% and deep percolation losses by 18%-54% compared to the traditional practice of conventional beds with GR. Compact beds with SM also reduced runoff volume by increasing evaporation by 15%-35%, available soil water storage by 12%-13%, and field infiltration of rainfall by 9%-18%. A basin-wide adoption of compact beds with precision irrigation can help reduce excessive downstream flows and nutrient loads in warmer and ecologically sensitive production regions such as the Everglades and the Chesapeake Bay.

Publication Title

Journal of Irrigation and Drainage Engineering

Volume

145

Issue

7

Digital Object Identifier (DOI)

10.1061/(ASCE)IR.1943-4774.0001397

ISSN

07339437

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