Smart Irrigation Systems

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Project Abstract

Project is in collaboration with Ensemble Scientific and University of British Columbia Center for Sustainable Food Systems (LiteFarm).

Irrigation is a key piece of Alberta agriculture and essential for growing many high value and specialty crops. Effective water management (limiting water stress and avoiding saturation) can be challenging and time consuming.

This project will build on and scale up a recently completed precision irrigation project that generated prescription maps for a variable rate irrigation (VRI) pivot. We will deploy full-stack irrigation prescription systems on two VRI & two uniform rate irrigation (URI) fields/yr to continue development of the system in field settings.

This will allow us to tailor our models to specific soil types and environments. We aim to build functionality for a broader range of irrigated crops, irrigation equipment types, and irrigator water management strategies.

Project Details
Timeline	2024-2027
Principal Investigator:	Ken Coles Farming Smarter
Project Contact:	Lewis Baarda
Ensemble Scientific Contact:	Mark Johnson
LiteFarm Platform Conact:	Divya Chayanam
Funded By:	Agriculture Funding Consortium, Farming Smarter, LiteFarm, Ensemble Scientific

Project Objectives

Develop decision support systems for VRI and URI irrigators that provide accurate and usable water management recommendations using real-time soil water analyses, hyper-local weather forecasts, and crop-specific growth models.

Develop a full-stack VRI management system farmers can use to achieve the full benefit of existing VRI technology to build functional autonomous zone-based differential irrigation.

Encourage adoption of these irrigation innovations across a wide range of crops and environments by developing the above capabilities on the free, open-source LiteFarm platform.

Deploy state-of-the-art evapotranspiration (ET) measurement stations to ensure project's ET data can be used to update crop ET curve databases to include irrigated specialty crops.

Methods

Collaborators
Farming Smarter	Coordinate collaboration with irrigation farmers, design & carry out field trials, support field analysis and collect sensor data
LiteFarm	Provide system expertise for open-source farm management platform, integrate system with existing VRI controllers
Ensemble Scientific	Supervise data collection of ET monitoring stations, compile sensor analytics, downscale regional weather forecasts to hyper-local level

Treatments

Four commercial crop fields will be selected each year for in-field studies to provide a wide range of soil and crop types

The following crops have been identified as a priority for the project:

Potatoes
Dry beans
Sugar beets
Seed/production canola
Seed alfalfa
Cereals
Sweet corn
Garden/processing peas
Forage/feed crops (corn, barley, alfalfa hay, timothy hay, etc.)

Each field will use 5 sensor arrays and one weather station. Sensor arrays include soil water sensors installed at 3 depths within the root zone, located across a gradient of 5 zones between lower, wetter areas to midslope to drier hilltops.

Use machine learning to derive hyper-local, field-specific weather forecasts that will address specific outcomes measured at each field location. Ensure crop ET and water balance model inputs are accurate and relevant.

Measurements

Mapped field data (EC, topography, soil texture, historic yield)	Weather station at each field site (temperature, relative humidity, wind speed, precipitation)	Soil moisture (proximal and distal to sensors)
Crop performance (georeferenced data on emergence, vigour, canopy closure, disease, biomass, yield)	Irrigation water applied

Results

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Results

Preliminary results will be released in Spring 2025.

Recommendations

Early recommendations will be based off initial observations of the 2024 growing season. These recommendations may change throughout the duration of the project.

News Articles

Smart Irrigation Support System Delivers Promising Start

Quick View

Friday, November 22, 2024

The first year of an innovative irrigation system has wrapped and data analysis is underway. This project aims to support decision-making in irrigated fields with an easy-to-use app that connects your phone to your soil.