MATHEMATICAL MODELING OF SOIL MOISTURE CHANGES CONSIDERING IMPULSE EFFECTS IN DIGITAL AGRICULTURE
DOI:
https://doi.org/10.32718/agroengineering2025.29.9-15Keywords:
humidity modelingAbstract
One of the key topics requiring attention within the framework of precision agriculture is soil moisture control. This parameter directly affects crop yield levels, the efficiency of water resource utilization, and the overall condition of the agroecosystem. Insufficient moisture can significantly reduce yield, while excessive moisture can cause nutrient leaching and even soil erosion. Therefore, it is crucial to understand how soil moisture changes under the influence of various factors, such as precipitation, evaporation, infiltration, and plant uptake. To improve agricultural practices, it is important to develop effective mathematical models that facilitate the analysis of soil moisture dynamics. This, in turn, will enable accurate determination of the need for additional irrigation at optimal times.
The aim of this work is to form a mathematical model of changes in soil moisture dynamics taking into account irrigation in the form of pulse action, which allows to establish optimal time for irrigation, and therefore - to increase the efficiency of water use in precision agriculture. Methodology and results consist in the application of a differential equation with pulse action to consider pulse irrigation under the conditions of achieving the required level of drainage (i.e. dehumidification). The time points of reaching critical moisture levels that require the introduction of an irrigation pulse have been determined (for samples of different types of soils). The model presented in the work can be used for automated control of irrigation systems, assessment of the efficiency of moisture retention in different types of soils, as well as for optimization of agrotechnical measures in precision agriculture. Scientific novelty and practical significance lie in the proposed pulse mathematical model of moisture dynamics, which allows to accurately formalize the moments of necessary irrigation. The results can be used to create automated irrigation control systems in precision agriculture, reducing water waste and increasing yields.
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