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Variable Rate Irrigation

Farming Smarter Project

Timeline: May 2021 – December 2022

Project Contact: Lewis Baarda

Sensor Contact: Mark Johnson

LiteFarm Platform Contact: Kevin Cussen

  

Abstract

Project is in collaboration with Ensemble Scietific and University of BC centre for sustainable food systems.

Alberta is known as the capital of irrigation in Canada with 500,000 Ha irrigated on more than 2,100 farms in the province. Crucially, >95% of Alberta’s irrigation water comes from off-farm sources. Given this distinction, our proposal to integrate smart-sensor irrigation technology with data-driven decision models is particularly powerful. Our approach has the potential to increase farm productivity, reduce water usage, and provide higher quality agricultural products. We propose to develop, deploy, and assess an automated, sensor-integrated open-source system to provide continually updated irrigation prescription maps for variable rate irrigation systems with our farm partner in Alberta.

We will combine real-time sensor-based assessments of soil moisture and precipitation in the field with data analytics of crop calendars and farm-level weather data. These near real-time, data-driven updates to irrigation prescription maps provide a key component to unlocking the improvements in irrigation efficiency that are possible with variable rate irrigation systems, yet are largely unused in Canada. This central feature will be combined with other valuable readings and data sources into powerful visualizations on the LiteFarm platform so that farmers can understand the state of their farm in real-time and over time. Since LiteFarm is open-sourced public good, these scientific advancements in farm productivity can be spread widely throughout Alberta and the world.

Objectives

The long-term goal of the partnership is to develop and implement precision irrigation solutions that align with and support the Government of Alberta’s 2020 announced investment in increasing irrigated areas in the province.

Our 2021-2022 project objective is to develop a full-stack smart irrigation system that will be developed, assessed and demonstrated on a farm in the Lethbridge area. The system will provide near real-time data visualizations to farmers so they can understand the evolving irrigation situation in their fields.

By the end of the project, we commit to delivering:

  • A LiteFarm module containing data visualizations of soil water status, crop calendars, crop water needs by crop stage, soil characteristics, and local weather and evapotranspiration forecasts.
  • An algorithm to dynamically generate irrigation prescription maps and communicate them with a VRI pivot system installed on a Farming Smarter partner farm.
  • An assessment of water use during the 2022 cropping season under full-stack precision irrigation system compared to current approaches.
  • Numerous knowledge transfer activities regarding on-farm use of automated precision irrigation.
  • Integrate the research into Farming Smarter’s Field Tested program

Method

The pivot field will be sectioned into 8 “slices”, with 3 of the 8 slices randomly assigned to the precision irrigation treatment. All slices will use static VRI prescriptions in 2021, with dynamic irrigation prescriptions implemented in 2022.

We will also compare full-stack precision irrigation results against the Alberta Irrigation Management Model (AIMM) and IRRI-Cast irrigation decision support system.

Overall, we will evaluate the technology according to the following performance measures:

  1.  Volume of water applied
  2.  Soil water content
  3.  Crop biomass, yield and grain quality
  4.  Power savings
  5.  Usability
  6.  Potential to improve low producing areas/expand arable land
  7.  Potential to reduce runoff

Results

Check back in 2022 to see our results!

Recommendations

Check back in 2022 for this section.

Media

We will add videos as they become available through seasonal Plot Shots, public events or off-season conference presentations. This is also where you will find links to agricultural media stories that may come from the project.

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