Metode za merjenje vsebnosti vode v tleh

Water has a significant influence on fundamental biophysical processes in the soil. It is one of the limiting factors for plant growth, which is why monitoring the water content in the field is particularly important in agriculture. In this article we present the methods currently used to measure the soil water content. We have described their functional principles, advantages, disadvantages and possible applications. Due to their widespread use in agriculture, we have focused on dielectric sensors, which are classified as electromagnetic methods. We have investigated the influence of soil properties on measurements with dielectric sensors and described possible methods for soil-specific calibration. In agriculture and environmental sciences, measurements of soil water content are particularly important for irrigation management. Irrigation based on measurements enables us to optimize the use of water resources and reduce the negative impact on the environment. For the correct functioning of such sensors it is necessary to check the suitability of the factory calibration function. Special attention is required when installing the sensors, as the presence of air gaps causes errors in the measurements.

Assessment of the Combined Effect of Temperature and Salinity on the Outputs of Soil Dielectric Sensors in Coconut Fiber

Dielectric sensors are useful instruments for measuring soil moisture and salinity. The soil moisture is determined by measuring the dielectric permittivity, while bulk electrical conductivity (EC) is measured directly. However, permittivity and bulk EC can be altered by many variables such as measurement frequency, soil texture, salinity, or temperature. Soil temperature variation is a crucial factor as there is much evidence showing that global warming is taking place. This work aims to assess how variations in the temperature and salinity of coconut fiber affect the output of EC5 (voltage) and GS3 (permittivity and bulk EC) Decagon sensors. The results showed that the effect of temperature and salinity on the output of the sensors can lead to substantial errors in moisture estimations. At low salinity values, permittivity readings decreased as temperature increased, while voltage readings were not affected, regardless of substrate moisture. The GS3 sensor underestimated the bulk EC when it is measured below 25 °C. The temperature dependence of the voltage of EC5 was not significant up to 10 dS m−1, and the permittivity of the GS3 was more affected by the interaction between temperature and salinity. The effect that salinity has on the permittivity of the GS3 sensor can be reduced if a permittivity–moisture calibration is performed with saline solutions, while the effect resulting from the interaction between temperature and salinity can be minimized using a regression model that considers such an interaction.

The Effect of Soil Iron on the Estimation of Soil Water Content Using Dielectric Sensors

Nowadays, the estimation of volumetric soil water content (θ) through apparent dielectric permittivity (εa) is the most widely used method. The purpose of this study is to investigate the effect of the high iron content of two sandy loam soils on estimating their water content using two dielectric sensors. These sensors are the WET sensor operating at 20 MHz and the ML2 sensor operating at 100 MHz. Experiments on specific soil columns, in the laboratory, by mixing different amounts of water in the soils to obtain a range of θ values under constant temperature conditions were conducted. Analysis of the results showed that both sensors, based on manufacturer calibration, led to overestimation of θ. This overestimation is due to the high measured values of εa by both sensors used. The WET sensor, operating at a lower frequency and being strongly affected by soil characteristics, showed the greatest overestimation. The difference of εa values between the two sensors ranged from 14 to 19 units at the maximum actual soil water content (θm). Compared to the Topp equation, the WET sensor measures 2.3 to 2.8 fold higher value of εa. From the results, it was shown that the relationship θm-εa0.5 remained linear even in the case of these soils with high iron content and the multi-point calibration (CALALL) is a good option where individual calibration is needed.