Cezary Sławiński

Database of Polish arable mineral soils: a review

Abstract The database of Polish arable mineral soils is presented. The database includes a lot of information about the basic properties of soils and their dynamic characteristics. It was elaborated for about 1 000 representative profiles of soils in Poland The database concerns: particle size distribution, organic carbon content, acidity-pH, specific surface area, hydrophobicity - solidliquid contact angle, static and dynamic hydrophysical properties, oxidation-reduction properties and selected biological (microbiological) properties of soils. Knowledge about soil characteristics is indispensable for description, interpretation and prediction of the course of physical, chemical and biological processes, and modelling these processes requires representative data. The utility of simulation and prediction models describing phenomena which take place in the soil-plant-atmosphere system greatly depends on the precision of data concerning characteristics of soil. On the basis of this database, maps of chosen soil properties are constructed. The aim of maps is to provide specialists in agriculture, ecology, and environment protection with an opportunity to gain knowledge of soil properties and their spatial and seasonal variability.

A TDR-Based Soil Moisture Monitoring System with Simultaneous Measurement of Soil Temperature and Electrical Conductivity

Elements of design and a field application of a TDR-based soil moisture and electrical conductivity monitoring system are described with detailed presentation of the time delay units with a resolution of 10 ps. Other issues discussed include the temperature correction of the applied time delay units, battery supply characteristics and the measurement results from one of the installed ground measurement stations in the Polesie National Park in Poland.

Impact of diverse tillage on soil moisture dynamics

Impact of diverse tillage on soil moisture dynamics The influences of traditional and reduced tillage on the water content dynamics of two soils were investigated in a long-term field experiment under nearly the same meteorological conditions for a winter wheat monoculture during three years. In addition to the moisture changes, the basic physicochemical properties, water retention, differential porosity and hydraulic conductivity of the investigated soils were measured. The results have shown the dependence between moisture and the tillage system applied for both types of soil. The soil water content was higher under reduced tillage in comparison to traditional management.

Fractal dimension of peat soils from adsorption and from water retention experiments

Samples of peat soils characterized by different degree of the secondary transformation are studied by means of nitrogen and water vapor sorption. Moreover, we have also determined the water retention curves and the dependence of the hydraulic conductivity on water potential. The experimental data are interpreted in terms of fractal theories of adsorption and retention, yielding the values of the corresponding fractal dimensions. We discuss the relation between surface fractal dimensions obtained from nitrogen and water sorption data, as well as between the mass fractal dimension resulting from retention data. We have also tried to correlate the fractal dimensions to other physico-chemical properties of investigated soils.

Pedotransfer studies in Poland

Publisher Summary This chapter presents the investigations of the impact of soil physical and chemical parameters on the water retention curve and water conductivity curve that were initiated in Poland. This research aimed at finding relations between the contents of granulometric fractions and the water contents at various values of the soil water potential. Soil organic matter affects water retention because it can retain water by itself and it strongly affects soil microstructure. It was difficult to establish direct relationships between the organic matter content and the water content at a given soil water potential. However, organic matter content is frequently taken into account as a complementary parameter in soil hydraulic property estimations. The chapter performs investigations that aim at estimating the soil hydraulic conductivity of undisturbed structure. The impact of soil physical parameters on the unsaturated hydraulic conductivity at selected soil water potential values is also investigated in the chapter.

Effect of data resolution on soil hydraulic conductivity prediction

The aim of the paper is to compare results of the instantaneous profile method (IPM) for measurement and calculation of unsaturated hydraulic conductivity k(Ψ) of soils obtained with different measurement data resolution. The application of IPM allows to realize a great number of k(Ψ) measurements for the purpose of mapping soil properties on large areas. Application of shorter samples i.e. less sensors makes the method even more quick and cheap. The calculation of unsaturated soil water conductivity by the IPM method bases on measurements of time and space variability of water content and water pressure within the soil sample in a cylinder. The spatial resolution of data depends on the number of probes applied in the core, The question arises how the number of compartments within one core influences the calculation of soil hydraulic conductivity. Application of three sensors instead of five reduced the accuracy of calculation but allowes to use 5 cm long standard cores during unsaturated flow experiment.

An estimation of the main wetting branch of the soil water retention curve based on its main drying branch using the machine learning method

PUBLICATIONS Water Resources Research RESEARCH ARTICLE 10.1002/2016WR019533 Key Points: The main wetting branch of the soil water retention curve is estimated based on its main drying branch The machine learning method is used for analysis Results are compared with classical methods of estimating the main wetting branch Supporting Information: Supporting Information S1 Data Set S1 Correspondence to: K. Lamorski, k.lamorski@ipan.lublin.pl Citation: Lamorski, K., J. r Sim˚unek, C. Slawi nski, and J. Lamorska (2017), An estimation of the main wetting branch of the soil water retention curve based on its main drying branch using the machine learning method, Water Resour. Res., 53, doi:10.1002/2016WR019533. Received 19 JUL 2016 Accepted 28 JAN 2017 Accepted article online 3 FEB 2017 An estimation of the main wetting branch of the soil water retention curve based on its main drying branch using the machine learning method unek 2 , Cezary Slawi n ski 1 , and Joanna Lamorska 3 Krzysztof Lamorski 1 , Ji r i Sim˚ Institute of Agrophysics, Polish Academy of Sciences, Lublin, Poland, 2 Department of Environmental Sciences, University of California Riverside, Riverside, California, USA, 3 Institute of Agricultural Sciences, State School of Higher Education in Chelm, Chelm, Poland Abstract In this paper, we estimated using the machine learning methodology the main wetting branch of the soil water retention curve based on the knowledge of the main drying branch and other, optional, basic soil characteristics (particle size distribution, bulk density, organic matter content, or soil specific surface). The support vector machine algorithm was used for the models’ development. The data needed by this algorithm for model training and validation consisted of 104 different undisturbed soil core samples collected from the topsoil layer (A horizon) of different soil profiles in Poland. The main wetting and drying branches of SWRC, as well as other basic soil physical characteristics, were determined for all soil samples. Models relying on different sets of input parameters were developed and validated. The analysis showed that taking into account other input parameters (i.e., particle size distribution, bulk density, organic matter content, or soil specific surface) than information about the drying branch of the SWRC has essentially no impact on the models’ estimations. Developed models are validated and compared with well-known models that can be used for the same purpose, such as the Mualem (1977) (M77) and Kool and Parker (1987) (KP87) models. The developed models estimate the main wetting SWRC branch with estimation errors (RMSE 5 0.018 m 3 /m 3 ) that are significantly lower than those for the M77 (RMSE 5 0.025 m 3 /m 3 ) or KP87 (RMSE 5 0. 047 m 3 /m 3 ) models. 1. Introduction Soil water retention curves (SWRCs) are one of the most important soil hydrological characteristics required for both agricultural and environmental research related to the vadose zone. SWRCs link the soil water con- tent with the soil water potential and represent indispensable information for the modeling of soil water flow processes. Although laboratory measurements are the ultimate source of information about retention curves, for many reasons SWRCs are commonly estimated using various statistical models, such as the so- called pedotransfer functions (PTF) [e.g., Vereecken et al., 1989, 2016; Schaap et al., 2001]. The main reason for using PTF estimations of SWRCs instead of direct measurements is their long duration and high cost. Typical steady state equilibrium measurements of the retention curve for a full range of soil water potentials can last several months. PTFs estimate SWRCs based on various physical and chemical soil characteristics. For example, particle size dis- tribution and dry bulk density are commonly used predictor variables in PTFs. Additional soil variables such as organic carbon content, soil-specific surface area, and/or cation exchange capacity can also be used. There were numerous PTF models developed utilizing different statistical and/or soft computing methods for SWRC estimation. Early PTFs were often developed using statistical regression [Rawls et al., 1982; Vereecken et al., € sten et al., 1999; Walczak et al., 2006], leading to some still often used models. Various soft computing 1989; W o methods of statistical inference such as artificial neural networks (ANN) [Schaap et al., 2001; Jana et al., 2008], th et al., the k-nearest neighbors algorithm (k-NN) [Nemes et al., 2006; Botula et al., 2013], regression trees [T o 2012, 2015], or support vector machines (SVM) [Lamorski et al., 2008] were used later on. C 2017. American Geophysical Union. V All Rights Reserved. LAMORSKI ET AL. Soil water retention curves of many soil materials exhibit hysteretic behavior, which means that the depen- dence between the soil water potential (h) and the soil water content (h) is not unique and depends on the ESTIMATION OF WETTING FROM DRYING BRANCH OF RC

Water conductivity of arctic zone soils (Spitsbergen)

Abstract The water conductivity of arctic zone soils derived in different micro-relief forms was determined. The greatest water conductivity at the 0-5 cm depth for the higher values of water potentials (> -7 kJ m-3) was shown by tundra polygons (Brunic-Turbic Cryosol, Arenic) - 904-0.09 cm day-1, whereas the lowest were exhibited by Turbic Cryosols - 95-0.05 cm day-1. Between -16 and -100 kJ m-3, the water conductivity for tundra polygons rapidly decreased to 0.0001 cm day-1, whereas their decrease for the other forms was much lower and in consequence the values were 0.007, 0.04, and 0.01 cm day-1 for the mud boils (Turbic Cryosol (Siltic, Skeletic)), cell forms (Turbic Cryosol (Siltic, Skeletic)), and sorted circles (Turbic Cryosol (Skeletic)), respectively. In the 10-15 cm layer, the shape of water conductivity curves for the higher values of water potentials is nearly the same as for the upper layer. Similarly, the water conductivity is the highest - 0.2 cm day-1 for tundra polygons. For the lower water potentials, the differences in water conductivity increase to the decrease of soil water potential. At the lowest potential the water conductivity is the highest for sorted circles - 0.02 cm day-1 and the lowest in tundra polygons - 0.00002 cm day-1.

Hydrophysical characteristics of selected soils from arctic and temperate zones

Abstract Hydrophysical characteristics of arctic and temperate zones soils were determined. The soils from the temperate zone showed a greater capability of water retention than those from the arctic zone. In both investigated depths (surface and subsurface layers), the highest water content was observed for the Sądecki Regosol, and the lowest one for Turbic Cryosol formed in the cell forms from Spitsbergen at all soil water potentials. The differences between water content for these soils at the same soil water potentials varied between 20 and 25% vol. in the surface layer, and from 19 to 22% vol. in the subsurface, respectively. The lowest differences (2.7-5.0% vol.) in water content were noticed between the Wyspowy Regosol and Turbic Cryosol (Skeletic) derived in the sorted circles. In both depths, higher values of water conductivity were observed for Regosols than for Cryosols at high soil water potentials, from -0.1 till -7 kJ m-3. These differences were especially high at -0.1 kJ m-3 and they were three or four times higher for soils from the temperate zone than from the arctic ones. For lower water potentials, the differences in water conductivity do not exceed one order in the surface layer and two orders in the subsurface.

Effects of reduced and traditional tillage on soil properties and diversity of diatoms under winter wheat

Abstract The aim of this study was to quantify soil properties, microbial biodiversity and crop yield under two tillage systems used for winter wheat production in monoculture. The study was conducted in the period 2013-2016, on a long-term field experiment on a silt loam at the Krasne Research Station near Rzeszów, Poland. Traditional tillage involved soil inversion whereas reduced tillage was a non-inversion system. The following soil properties: chemical (soil organic carbon, pH, available P, K, Mg), physical (soil bulk density, water content, stability in water), and biological (the diversity of diatoms) were measured on samples collected throughout the growing season and at harvest. Soil organic carbon content, water content and bulk density in the 0-5 and 5-10 cm layers were greater in reduced tillage than in traditional tillage. Under reduced tillage the amount of readily dispersible clay was reduced giving increased soil stability in water. Soil under reduced tillage had greater diversity of diatoms (139 taxa) than that under traditional tillage (102 taxa). Wheat yields were positively correlated with precipitation, soil water content and soil organic carbon, and negatively correlated with readily dispersible clay.