Project 3.1.2

Improving water quality for the Great Barrier Reef and wetlands by better managing irrigation in the sugarcane farming system

Led by: Assoc Prof Yvette Everingham, JCU

Co-collaborator: Steve Attard, AgriTech Solutions

Project Summary

In pursuit of delivering multiple benefits across multiple ecosystems such as freshwater estuaries, wetlands and reefs, this project will work in partnership with industry, extension, NRM, research and government organizations to develop and deploy an irrigation system that is automatically controlled by remotely accessing feedback from the IrrigWeb decision support tool. Irrigweb provides optimal irrigation schedules on a paddock-by-paddock basis by linking information about climate, soils and management regimes. If new water quality targets as specified in the revised Burdekin Water Quality Improvement Plan are to be met by 2025, it will be critical to establish pathways that enable industry partners to capitalize on new technologies.

Project Publications

 

 

Project Videos

Problem Statements

Problem

Specific problem being addressed

The revised WQIP is aiming to have 60% of areas managed using high efficiency irrigation techniques by 2025. Unfortunately, only 10% of canegrowing areas in the Burdekin are irrigating at this efficiency (based on 2013/14 data).

Proposed solution

Create an efficient and effortless precision irrigation system for the farmer that automatically applies the right amount of water, at the right time, in the right paddock, to match the crop’s requirements.

How Research Addresses Problem

The revised Burdekin water quality improvement plan has aspirations to achieve an 80% reduction in DIN. Reduction in DIN cannot occur by adjusting N rate only. Because of the strong linkage between irrigation management and DIN losses, managing DIN must involve both managing the N rate that is applied, and irrigation subsequent to that. This project focuses on the later. To achieve this goal, there will need to be widespread adoption of practices and technologies that deliver high irrigation use efficiency in the Burdekin by 2025.

This is easier said than done. Barriers that frequently impede the adoption of new practices and technologies include but are not limited to:

(i) lack of trust

(ii) fear of disruption,

(iii) limited time to change practice and interact with technologies

(iv) proof of value

(v) reliability and

(vi) mismatch between what the technology actually delivers and what it should deliver.

If the Burdekin is to achieve a reduction in DIN through improved irrigation practices, then we need a solution to overcome these barriers. Typically, decision support tools such as APSIM, CANEGRO, WATERSENSE and in the case of the Burdekin, IrrigWeb are turned to as a solution to this problem. However, adoption theories tell us that unless the outputs from a decision support tool are reduced to a rule of thumb, they are rarely adopted and applied in practice (Thorburn, Jakku, Webster, Everingham, Int. J. Agricultural Sustainability, 2011). Rarely is it possible to generate rules of thumb for irrigation management from decision support tools, because the crop irrigation system is dynamic. This means that IrrigWeb requires frequent updating and ultimately leads to failed adoption practices because farmers do not have the time to do this. One way around this problem is to embed the IrrigWeb knowledge within IOT (Internet of Things) systems.

To achieve this goal we must work closely with key stakeholder groups to improve our understanding of how industry engages with and perceives new irrigation technologies that promote best management practices. Understanding farmers’ expectations and perceptions of new technologies is more likely to produce useful tools and services that increase industry competitiveness and deliver better environmental outcomes. We should also appreciate that computing and sensor costs have been decimated in recent years and are expected to decrease further in price. It will therefore be opportunistic if we develop systems today that exploit these enabling technologies for tomorrow. This will help set the industry up to achieve an 80% reduction in DIN by 2025.

This project will build on the investment that a) BPS Ltd have made in the subscription to IrrigWeb for its members via financial support from the RWUE program, Smartcane BMP and QDAF and b) an SRA research project that seeks to automate furrow irrigation in the sugar industry (SRA Project number 2014/079). Specifically, we propose to:

(i) Develop and deploy a prototype for automatic controlling and remote accessing of irrigation systems based on feedback from the IrrigWeb decision support tool.

(ii) Work in partnership with farmers, extension officers, commercial providers (WiSA, IrrigWeb), research groups (SRA, NQ Dry Tropics, JCU) and government agencies (DoEE) as part of an action learning environment, to:

– simultaneously harness the ideas, needs and wants of stakeholder groups

– identify the perceived or real barriers to the adoption of the precision irrigation system

– explore ways to overcome these barriers.

(iii) Facilitate ownership, confidence and ‘know-how’ of the proposed IOT and IrrigWeb technologies amongst farmer and extension groups.

(iv) Identify options for adoption pathways of high irrigation use efficiency practices in the Burdekin canegrowing areas.

Alignment with NESP Research Priorities

1a) Provide science to support existing field trials that develop/evaluate practical on-farm nutrient and sediment loss mitigation/capture and land management practices that will influence behavioural change and improve water quality outcomes. Field trials should include key growers and change agents and demonstrate water quality outcomes.

Project Keywords

IOT; Irrigation; Burdekin; Sugarcane; IrrigWeb.

Project Funding

This project is jointly funded through JCU, Burdekin Productivity Services, SQR Software Limited, Sugar Research Australia, NQ Dry Tropics, WiSA Global, Growers, AgriTech Solutions and the Australian Government’s National Environmental Science Programme.

Project Map

https://eatlas.org.au/nesp-twq-3/iot-irrigation-system-3-1-2