In the context of the current discussions about climate change, the issue of protecting natural resources, especially water resources, is becoming more and more relevant. In many climate regions the availability of water in soils decides to a large extent their agricultural productiveness.
Information about soil water dynamics provides valuable data to optimize irrigation practice with regard to volume and duration of irrigation. Irrigation must be based on objective and quantitative criteria, which focus primarily on soil properties and hydrological balances. Novel irrigation
equipment requires detailed knowledge of the water distribution in the soil. Thus, a dense soil-hydrological measuring network must ideally be composed of special calibrated micro-sensors which are distributed in the soil for measuring soil moisture at high temporal and spatial resolutions.
However, a proof of concept of the setup and operation of such a sensor network is needed before it may be realized. The management and control of sensor networks can best be modelled using an agent-based approach, where each sensor is represented by an agent in the model. The main result
of this agent-based simulation is a detailed dynamic irrigation schedule based on water fluxes in the soil, adapting to real-time sensor information on soil moisture. This schedule results in a minimum amount of water used with maximum efficiency of irrigation.
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