Abstract

An important step in today’s modern precision crop production systems is the development of an irrigation system for arable lands. Most of these systems only examine the top, 10 cm layer of the soil. The problem is that the root system of the crops also penetrates and grows into the deeper layers while absorbing water. For this reason, there is a need for a cost-effective solution to quantify the amount of water up to 1 meter depth. Sentek EnviroSCAN sensors were used to measure soil moisture (SM) values of different soil types located in Hungary having different soil mechanical and chemical attributes. SM values were only measured at certain depths. The missing depths are supplemented with estimated data done by interpolation. However, these estimations are not enough, as these sensors were located on different soil types, i.e. one kind of interpolation method may not be suitable to all sensors without significant statistical error.Several soil moisture sensors were deployed. Each of them is placed on a specific soil type. The measured SM depth values were then used to produce estimated SM values lasting from 10 to 100 cm by using 8 types of interpolation methods. The interpolation was performed using a Python framework called Scipy. The final result of the research is the evaluation of the model performance of the soil moisture data estimated by 8 types of interpolation methods for different soil types in Hungary.

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