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Agri 3.0 – Irrigation Model

    Home Insights Agri 3.0 – Irrigation Model
    irrigation model
    Insights, Agriculture | 0 comment | 20 July, 2021 | 0

    Creating an irrigation model was one of Matogen Applied Insights’ (MAI) earliest projects within the agricultural sector. It examined how data-driven farm management can optimise irrigation practices.

    Crop irrigation optimisation

    Due to population growth, industrialisation and contamination, there is increasing pressure on the amount of water available for irrigating agricultural crops. It has become critical to optimise crop irrigation to provide the most beneficial amount of water at the correct time, in order to maximise crop yields while limiting wastage. Too little water puts crops in excessive drought stress, whereas too much water results in waste and could potentially flood the nutrients away from the roots, hampering effective absorption, and therefore, yield.

    Crop irrigation scheduling has traditionally been based on theoretical crop coefficient values, which are primarily based on annual seasonal changes. These values are used as a reference point when determining total water, crop and season allocations. However, these coefficients still have a coarse, monthly resolution at best and true water needs of crops deviate strongly, especially given increasingly erratic weather conditions.

    Evaporation, Transpiration and Evapotranspiration 

    Evaporation is the process whereby liquid water is converted to water vapour, “vaporisation”, and removed from the evaporating surface, “vapour removal”. Water evaporates from a variety of surfaces, such as soil and wet vegetation, as well as lakes, rivers and pavements. The evaporation process is influenced by climatological parameters such as solar radiation, air temperature, air humidity and wind speed.

    Transpiration denotes the vaporisation of liquid water contained in plant tissues and the vapour removal to the atmosphere. Crops predominately lose their water through stomata, small openings on the plant leaf through which gases and water vapour pass.Transpiration, like direct evaporation, is affected by weather conditions.

    Evaporation and transpiration occur simultaneously and the processes are difficult to distinguish. Evaporation from cropped soil is mainly determined by the fraction of solar radiation reaching the soil surface, which decreases as crops develop and more canopy increases shade. Initially, water loss is largely due to evaporation, but at later crop growth stages, transpiration becomes the main process. 

    Evapotranspiration is the combined name for the processes of evaporation and transpiration. It is abbreviated as ETc and is used to express crop water usage. It varies from region to region depending on crop type, stage of growth, soil, and climate conditions. Different evapotranspiration rates may be observed even in different parts of the same region. Considering global warming and climate change in recent years, it is clear that the predicted ET values of a year cannot be used safely for upcoming years.

    Crop irrigation model

    An international client in the agriculture sector contracted Matogen Applied Insights (MAI) to analyse data derived from telemetry readings from on-site probes dedicated to measuring the water moisture at various depths. This data was combined with climate data, specifically temperature, to enhance crop water requirement predictions. 

    By exploring the data it was revealed that there was a significant deviation of (30% – 50%)  between expected and actual crop water consumption. An algorithm was created to derive a more refined crop coefficient curve from probe readings. In addition, these new crop coefficients were linked to heat readings from annual temperature data to produce more nuanced predictions that accommodate temperature fluctuations within seasons, instead of only using the broader time definition, “season”. A feedback loop was created to update and improve the water crop coefficient in an iterative fashion, continually improving model performance.

    Agricultural software

    MAI’s predictive irrigation model was incorporated into a multifunctional agricultural software product developed by its sister company, Matogen Corporate Software Development. It delivers an irrigation scheduling tool that can be used with a wide range of telemetry devices and along with the other product components, offers actionable information on a variety of agricultural aspects, including weather and spray condition forecasts and soil classification — all of which are critical for efficient and sustainable farm management.

    agriculture, data science, machine learning, irrigation systems, agri 3.0, agritech, data-driven farming, farming technology, predictive analytics, modelling

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