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Grzegorz Janik  - - - 
Top co-authors See all
Wojciech Skierucha

86 shared publications

Polish Academy of Sciences, Institute of Agrophysics, Lublin, Poland

Jolanta Cieśla

56 shared publications

Institute of Agrophysics, Polish Academy of Sciences; Doswiadczalna 4 20-290 Lublin Poland

Andrzej Wilczek

29 shared publications

Polish Academy of Sciences, Institute of Agrophysics, Lublin, Poland

Agnieszka Szypłowska

22 shared publications

Polish Academy of Sciences, Institute of Agrophysics, Lublin, Poland

Anna Nakonieczna

18 shared publications

University of Warsaw

Publication Record
Distribution of Articles published per year 
(2012 - 2018)
Total number of journals
published in
Publications See all
PROCEEDINGS-ARTICLE 0 Reads 0 Citations Applicability of LP/ms Type Sensors for Determination of Moisture Dynamics of Injection-Irrigated Soil Grzegorz Janik, Amadeusz Walczak, Tadeusz Reinhard Published: 01 June 2018
2018 12th International Conference on Electromagnetic Wave Interaction with Water and Moist Substances (ISEMA), doi: 10.1109/isema.2018.8442325
DOI See at publisher website
Article 2 Reads 0 Citations Evaluation of Apple Maturity with Two Types of Dielectric Probes Marcin Kafarski, Andrzej Wilczek, Agnieszka Szypłowska, Arka... Published: 04 January 2018
Sensors, doi: 10.3390/s18010121
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
The observed dielectric spectrum of ripe apples in the last period of shelf-life was analyzed using a multipole dielectric relaxation model, which assumes three active relaxation processes: primary α-process (water relaxation) and two secondary processes caused by solid-water-ion interactions α’ (bound water relaxations), as well as β’ (Maxwell-Wagner effect). The performance of two designs of the dielectric probe was compared: a classical coaxial open-ended probe (OE probe) and an open-ended probe with a prolonged central conductor in a form of an antenna (OE-A-probe). The OE-A probe increases the measurement volume and consequently extends the range of applications to other materials, like granulated agricultural products, soils, or liquid suspensions. However, its measurement frequency range is limited as compared to the OE probe because, above 1.5 GHz, the probe with the antenna generates higher propagation modes and the applied calibrations and calculations are not sufficient. It was shown that data from measurements using the OE-A probe gave slightly stronger correlations with apples’ quality parameters than using the typical OE probe. Additionally, we have compared twelve multipole fitting models with different combinations of poles (eight three-pole and four two-pole models). It was shown that the best fit is obtained using a two-pole model for data collected for the OE-A probe and a three-pole model for the OE probe, using only Cole-Cole poles in both cases.
Article 0 Reads 0 Citations BONITATION ANALYSIS OF TURF ON CITY STADIUM IN WROCLAW IN THE SEASON OF EURO 2012 Karol Wolski, Jarosław Czarnecki, Justyna Ziarko, Marta Tala... Published: 01 January 2016
Journal of Ecological Engineering, doi: 10.12911/22998993/64561
DOI See at publisher website
Article 1 Read 3 Citations Applicability of Geostatistical Tools and Fractal Theory for the Estimation of the Effect of a River on Water Relations ... G. Janik, B. Olszewska, L. Pływaczyk, W. Łyczko, M. Albert, ... Published: 14 October 2015
River Research and Applications, doi: 10.1002/rra.2970
DOI See at publisher website
Article 0 Reads 1 Citation Detection of Atmospheric Water Deposits in Porous Media Using the TDR Technique Anna Nakonieczna, Marcin Kafarski, Andrzej Wilczek, Agnieszk... Published: 13 April 2015
Sensors, doi: 10.3390/s150408464
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Investigating the intensity of atmospheric water deposition and its diurnal distribution is essential from the ecological perspective, especially regarding dry geographic regions. It is also important in the context of monitoring the amount of moisture present within building materials in order to protect them from excessive humidity. The objective of this study was to test a constructed sensor and determine whether it could detect and track changes in the intensity of atmospheric water deposition. An operating principle of the device is based on the time-domain reflectometry technique. Two sensors of different plate volumes were manufactured. They were calibrated at several temperatures and tested during field measurements. The calibration turned out to be temperature independent. The outdoor measurements indicated that the upper limits of the measurement ranges of the sensors depended on the volumes of the plates and were equal to 1:2 and 2:8 mm H₂O. The respective sensitivities were equal to 3.2 x 10⁻³ and 7.5 x 10⁻³ g∙ps⁻¹. The conducted experiments showed that the construction of the designed device and the time-domain reflectometry technique were appropriate for detecting and tracing the dynamics of atmospheric water deposition. The obtained outcomes were also collated with the readings taken in an actual soil sample. For this purpose, an open container sensor, which allows investigating atmospheric water deposition in soil, was manufactured. It turned out that the readings taken by the porous ceramic plate sensor reflected the outcomes of the measurements performed in a soil sample.
Article 1 Read 1 Citation TDR Technique for Estimating the Intensity of Evapotranspiration of Turfgrasses Grzegorz Janik, Karol Wolski, Anna Daniel, Małgorzata Albert... Published: 01 January 2015
The Scientific World Journal, doi: 10.1155/2015/626545
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
The paper presents a method for precise estimation of evapotranspiration of selected turfgrass species. The evapotranspiration functions, whose domains are only two relatively easy to measure parameters, were developed separately for each of the grass species. Those parameters are the temperature and the volumetric moisture of soil at the depth of 2.5 cm. Evapotranspiration has the character of a modified logistic function with empirical parameters. It assumes the form , where: is evapotranspiration [mm·h−1], is volumetric moisture of soil at the depth of 2.5 cm [m3·m−3], is soil temperature at the depth of 2.5 cm [°C], and A, B, and C are empirical coefficients calculated individually for each of the grass species [mm·h1], and [—], [(m3·m−3·°C)−1]. The values of evapotranspiration calculated on the basis of the presented function can be used as input data for the design of systems for the automatic control of irrigation systems ensuring optimum moisture conditions in the active layer of lawn swards.1. IntroductionLimited water resources are a challenge in the maintenance of a suitable visual quality of lawns [1, 2]. Quantitative determination of evapotranspiration is of fundamental importance in the design of lawn irrigation systems [3, 4]. It depends on the kind and moisture of the soil, on the plant species, variety, and development phase of the grass, and on the atmospheric conditions [5–9]. One of the methods of estimating soil surface evaporation and water uptake by plant roots is the application of physical and mathematical empirical models [10–13]. Such models take into account a large number of input parameters. As an example, in the model developed by Fedes et al. [14] one should give the following: heat flux from the soil surface to the atmosphere, heat flux used for evaporation, heat flux from net radiation, latent heat of evaporation, vapour flux, and the incident heat flux received by the soil. In the empirical model one needs to additionally specify the root mass density and precisely define the physical properties of soil and for improved accuracy also determine the material functions of the soil [15]. In universal empirical models it is additionally required to analyse the input data from multiple synoptic stations. As an example, the estimation of ET0 by means of the Penman-Monteith model for the territory of Iran required the collection of data from as many as 181 synoptic stations [16–19]. Another method for estimation of ET0 is the application of energy budget methods in which parameters are determined by using the remote-sensing technique [20]. The intensity of evapotranspiration is also determined by the toilsome lysimetric research [21–23]. The objective of this study was the presentation of a method permitting precise calculation of evapotranspiration, with a short 1-hour time step, on the example of selected turfgrasses. The advantage of the method is that its application requires parameters that are relatively easy to measure—the temperature and moisture of the surface layer of soil. Since our considerations omitted the effect of the location of the lawn (built-up area, nonbuilt-up area, stadium, or green roof), calibration is required for every location. A similar approach, consisting in performing the calibration of Penman-Monteith (PM) formulae for a case when complete weather data are not available, was applied by Gao et al. [24]. In the study by Gao et al., the data required for the estimation of evapotranspiration (ET0) include temperature (), relative humidity (RH), and sunshine duration (). Yang et al. [25] applied an ETR estimation method based on meteorological data such as incoming solar radiation, air temperature, water vapour pressure, wind speed, and atmospheric pressure. The method presented here, after calibration, can also be applied to other plant species.2. Materials and MethodsIt was assumed that the evapotranspiration of selected turfgrass species can be calculated on the basis of a function whose domain is only two values: temperature and volumetric moisture of the surface layer of soil. The function can be determined on the basis of an experiment. The values that constitute its domain are relatively easy to measure, while the evapotranspiration can be calculated using the time-domain reflectometry (TDR), as illustrated in Figure 1.Figure 1: Dynamics of volumetric moisture as information on evapotranspiration; is volumetric moisture in th layer at the initial (final) moment [m3·m−3], is volume of water in layers 1, 2, and 3 at the initial (final) moment [m3], is evapotranspiration [mm·h−1], is unit intensity of water flux between layers 1 and 2 (2 and 3) [mm·h−1], is surface area of soil column cross section [m2], is volume of th layer [m3], is time step [h], is initial (final) moment, and is soil layer height [m].A soil column with plant root system was divided into 3 layers with identical volume . The justification for the number of layers is given at the description of the Figure 2. During a nonrainfall period the water balance equation for the upper layer () is as follows:where is volumetric moisture in layer 1 at the initial (final) moment [m3·m−3], is volume of layer 1 [m3], is evapotranspiration [m·h−1], is intensity of water flux between layers 1 and 2 [m·h−1], is time step [h], and is soil column cross-section surface area [m2].Figure 2: Schematic diagram of the experiment.In (1), the values of and can be measured with high accuracy and freely selected with a small (even 1 minute) time step by means of the TDR technique. Values , result from the dimensions of the soil monolith. The value of time step is set individually for each experiment. The value of is calculated in stages. First, we construct the balance equation for the bottom layer 3:where is volumetric moisture in layer 3 at the initial (final) moment [m3·m−3] and is unit intensity of water flux between layers 2 and 3 [m·s−1], other symbols as in relation (1).The only unknown of (2) is the value of . Then we construct the equation for layer 2:where is volumetric moisture in layer 2 at the initial (final) moment [m3·m−3], other symbols as in relations (1) and (2).Finally, making use of relations (1), (2), and (3), we can calculate the loss of water from the whole volume of the monolith for time step :where is height of the soil layer, other symbols as in relations (1), (2), and (3).The experiment aimed at the determination of evapotranspiration using the method proposed above (4) was conducted in June 2013. Only an 11-day nonrainfall period, that is, from the 11th to the 21st of June, was taken into consideration for the analyses aimed at the construction of the evapotranspiration function. Cylindrical soil samples were covered with 4 different turfgrasses: Poa pratensis L. cult. Niweta, Lolium perenne L. cult. Nira, Festuca rubra L. cult. Sawa, and the grass mix SPORT (Lolium perenne L. (60%) cult. Nira, Niga; Festuca rubra L. (20%) cult. Sawa, Nimba; Poa pratensis L. (20%) cult. Alicja and Niweta). Further on in the text, they will be referred to as Niweta, Nira, Sawa, and grass mix SPORT, respectively. The grass species chosen—Niweta, Nira, and Sawa—are basic turfgrasses commonly used for sowing lawns and recreational areas. The grass mix SPORT is used primarily for football fields. The soil monoliths for the analyses were taken from an experiment setup with the split-plot method at the Agricultural Experimental Station Swojec in Wrocław (Poland) (E 17°08′22,56′′ N 51°06′59,04′′). That experiment was established on an alluvial soil developed on loamy sand, overlying light sand. The samples were taken so as to leave the soil structure undisturbed. Only the root systems were slightly damaged due to cutting on the edges of the monolith. The dimensions of the soil profiles are shown in Figure 2. They are the standard dimensions of turf samplers. The height of the soil column equals 15 cm. This is due to the fact that such is the depth of the vegetation horizon in the turf of football fields. Soil column diameter of = 10 cm results from the dimensions of the zone of sensitivity of the sensors used in the experiment. The soil profiles collected are homogeneous. The particle size distribution of the substrate conforms with the parameters required for the construction of the vegetation layer of sports objects (DIN 18035-4). As in the method described above, 3 layers were separated in the columns, with identical dimensions. The volumetric moisture was recorded at the centre points of the layers, using TDR probes type LP/ms, manufactured at the Institute of Agrophysics PAS in Lublin (Poland) [26]. In addition, an LP/ temperature sensor was installed at the central point of the top layer (at the depth of 2.5 cm). Based on a pilot study, it was found that, for a monolith height of 15 cm, the division of the column into 3 layers (3 TDR probes) is optimum for correct characterisation of moisture. Although increasing the number of layers (e.g., 5 TDR probes) might improve the accuracy of the water balance determined, at the same time it would cause greater disturbance of the water flow. It determines the depth of the sensors installation: 2.5 cm, 7.5 cm, and 12.5 cm. All measurements were made at the time step of = 1 h. In that way, a set of data was acquired to enable the calculation of the evapotranspiration for each measured temperature and moisture value of the top layer of soil. A schematic of probe distribution and of the experiment is presented in Figure 2.3. ResultsFigure 3 presents the measured data for each of the grasses—the dynamics of volumetric moisture in 3 soil layers and the dynamics of temperature in the top layers. The initial values of soil moisture (on the first day of the experiment) fall within the range from 0.3 m3·m−3 to nearly 0.4 m3·m−3.Figure 3: Dynamics of moisture in the period of 11–21.06.2013 for 4 grasses; is volumetric moisture in th layer and is temperature at the depth of