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How artificial intelligence (AI) can help optimise irrigation water use

About the blog

Manuel Martín Arroyo
Forestry Engineer and Agricultural Engineer with certification in Marketing and Communication, dedicated to the development of projects and solutions in the fields of water and agriculture. I also work as an agricultural producer.
  • How artificial intelligence (AI) can help optimise irrigation water use

Artificial intelligence (AI) is a great ally in addressing the challenges we face in water management for irrigation agriculture, as it can help increase water use efficiency.

But what is artificial intelligence? It is a field of computer science that develops systems capable of mimicking human intelligence to perform tasks such as learning from data, recognizing patterns, and making decisions, all without direct human intervention.

Currently, AI is omnipresent in society, impacting various aspects of our daily lives, from virtual assistants like Siri and Alexa that help us manage our tasks, to systems that make recommendations on entertainment platforms like Netflix and Spotify to personalize our experience. AI is constantly evolving and driving significant advances in important areas such as healthcare, where it is used for precision medical diagnosis and the development of personalized treatments. On the other hand, in sectors such as digital advertising and financial safety, AI is essential to target ads more accurately and detect potential fraud. In the automotive industry, AI powers the development of autonomous vehicles, promising a future of safer and more efficient transportation.

These are just a few examples of how artificial intelligence has transformed the way we interact with technology and how companies operate today. Its impact continues to expand as new applications are discovered and existing techniques are perfected.

The agricultural sector is not exempt from this trend, and the use of AI in this sector is transforming agriculture by enabling more precise and efficient decision-making in areas such as predicting and preventing pests and diseases, optimizing agricultural production through real-time recommendations, precision agriculture using technology, automation of agricultural tasks using robots, efficient management of water resources, and genetic improvement of crops through genetic data analysis. All of this results in increased productivity, reduced costs, and increased sustainability in the agricultural sector.

The application of AI in agriculture, particularly to improve the efficiency of irrigation water use, is an increasingly important area of research and development. By analyzing historical and real-time data, AI can predict water demand for irrigation, allowing for more precise planning of the water supply. Additionally, intelligent irrigation systems, controlled by AI algorithms, can precisely adjust the amount of water supplied based on various variables such as soil moisture, crop status, vegetation index, and irrigation strategy, automatically acting on automation elements. This ensures optimal water use.

AI algorithms, in addition to using data for optimal irrigation scheduling, can analyse satellite images and sensor data to detect anomalies in crop growth patterns that may indicate irrigation problems, such as water stress. This allows for timely corrective actions to be taken.

In crop planning, the use of AI allows for the analysis of a large volume of data related to the variables involved in crop selection and, based on this analysis, the selection of the most suitable crop based on the particular characteristics in each case, as well as making predictive models of how these variables will behave. Regarding the optimal use of irrigation water, this allows for crops adapted to both current and future water availability according to the predictive model.

Among the applications of AI at the level of irrigation water user associations, in addition to those listed above, we can highlight the prediction of water demand according to user behaviour models and the prediction of breakdowns and anomalies in irrigation facilities to ensure proper predictive maintenance. All of this, in addition to resulting in water optimization, allows for a reduction in operation and maintenance costs.

At the basin scale, AI can be used to develop predictive models of water systems, allowing for more efficient and sustainable management of water resources on a large scale. These models can take into account factors such as water availability, agricultural irrigation demand, water quality, and environmental constraints. In the particular case of groundwater, the use of AI is particularly important as it will enable anticipating how aquifers will behave and predicting water availability and quality, so that appropriate measures can be taken to prevent overexploitation of aquifers.

However, although the use of AI in irrigation has countless benefits, it should be noted that to achieve these benefits, it is necessary to start with irrigation (and planting) systems designed optimally and managed efficiently. Therefore, the application of AI will be a plus.

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