Reducing Irrigation Water Wastage with Precision Agriculture

Fresh water sources are becoming increasingly scarce around the world, and what water we have access to is used inefficiently. With current rates of water consumption, it is estimated that by 2025 two thirds of the global population will face water shortages. Agricultural systems use around 70% of the world’s fresh water, but as much as 60% is believed to be wasted in the process, making it imperative that water in this sector be used more judiciously. Precision agriculture is gaining traction due to its highly adaptable use of technologies to observe, measure, and apply exact quantities of inputs to crops on a large scale. Robotics and artificial intelligence have been woven into irrigation systems for a number of years now, but increasingly advanced and scalable systems are needed as temperatures rise and aquifers dry out.

How Precision Agtech Improves Irrigation Efficiency

There are a number of precision agriculture technologies that have been around for years, but are now being tailored to specifically focus on water conservation in irrigation systems. Variable Rate Irrigation (VRI) technologies create an opportunity for farmers to adapt and vary how their water is applied spatially and temporally. It is designed to put water inputs to better use by irrigating areas that are in need and taking away unnecessary irrigation dead zones. For example, using map analysis VRI could be programmed to apply more irrigation to sloped areas that experience heavy run-off from rain, or to avoid watering anomalous, uncropped spots like streams or rock piles. The automation of this is interconnected with artificial intelligence, which has become the beating heart of many agtech systems. AI can process complex data inputs and create tailored schedules and recommendations for water application. When combined with centre pivot irrigation — which is an irrigation method where sprinklers rotate on a pivot and disperse water in a circular pattern — AI has the potential to control and create fully autonomous irrigation networks.

Part of the data processed by AI is collected via remote sensors in the soil, which are wireless and have been designed to measure a whole sleuth of things. Amongst them are soil water sensors and temperature sensors, which can provide current information about soil moisture availability for plants and how quickly it is expected to dissipate. These sensors also connect to IoT clouds that farmers can access from their phones, so they can remotely manage their irrigation systems and detect issues as they arise. Before the scheduled irrigation, the sensors will read the moisture level where they are buried at the root zone of the crop, and if it is above the threshold, the water inputs for that zone are paused. Soil moisture sensors have been proven to conserve water with this method by preventing unnecessary irrigation and flooding.

Main Challenges to Implementation

We have the technology to streamline irrigation systems and reduce water wastage, so what are the main barriers to establishing them across the board? Firstly, the costs associated with robotics and AI are still high, as are the IT repairs and maintenance of them — a service which is not necessarily accessible in farming regions. The cultural impacts of precision agriculture technologies can also pose a significant barrier, particularly in developing nations where foreign agribusinesses have a vast history of exploitation. There is an inherent distrust of technological interventions in many farming communities where industrialized agriculture has had negative impacts. In surveys, farmers have been reported to say that agriculture is already so risk-vulnerable that they would rather trust people to manually operate machines over AI and robotics, fearing that the latter would be unable to adapt to unforeseen situations. This brings up another significant impact, which is the job loss for farm workers associated with autonomous irrigation systems. The livelihoods of farmers and farm workers cannot be left behind with the spread of precision agriculture, and prioritizing education and retraining programs for farmers in IT systems and management is crucial in supporting the transition. Farmers are high priority stakeholders whose opinions should be reflected in the technologies they use, so that the full potential of these solutions can be realized and water effectively conserved.

Sources

1. WWF. (2021). Water Scarcity. World Wildlife Fund. https://www.worldwildlife.org/threats/water-scarcity
2. Derek, H. M. (2017, October 20). Considerations in Adopting Variable Rate Irrigation. University of Nebraska–Lincoln. https://water.unl.edu/article/agricultural-irrigation/considerations-adopting-variable-rate-irrigation
3. Mowitz, D. (2020, November 23). Irrigation: autonomous pivots Fully automatic irrigation is a reality. Successful Farming.
4. The World Bank. (2020, May 8). Water in Agriculture. The World Bank. https://www.worldbank.org/en/topic/water-in-agriculture
5. Shet, Akshay & Shekar, Priya. (2020). Artificial Intelligence And Robotics In The Field Of Agriculture. 10.13140/RG.2.2.10162.84167.
6. Talaviya, T., Shah, D., Patel, N., Yagnik, H., & Shah, M. (2020). Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides. Artificial Intelligence in Agriculture.