The water contained in the soil is one of the most important components of the environment. Soil moisture governs the partitioning of energy and mass fluxes on the Earth. Recognition and understanding of temporal changes and spatial distributions of soil moisture are essential to solve many fundamental scientific and utilitarian issues. Knowledge about soil moisture is very important in the management of water resources, assessment of droughts, and in the prediction of floods and surface runoffs. Without water disposed in soil any growth or development of plants on the lands would be impossible. For those reasons, information on soil moisture is so important for applications in agriculture, such as determining the time of sowing, irrigation management and crop forecasting.

Although soil moisture is so significant and desired a parameter, its measurement raises many difficulties. Due to the fact that the soil moisture can be spatially variable, its ground-based measurements are often very time-consuming and costly, but relatively precise. On the contrary, measurements of soil moisture from satellites are cost-effective, fast and consistent, but uncertain in absolute measures, so they need to be validated using ground-based measurements. The comparison issue, connected to that, often causes the scaling problem which can be solved using statistical and geostatistical methods. These methods allow one to describe the relationship between the easily- and non-easily-measurable variables, are useful to determine the spatial dependences and are used to acquire maps of the spatial distribution of examined variables.

The study investigated the spatial distributions and time series of surface soil moisture, soil bulk density and soil particle size distribution. The distributions of soil moisture were obtained from ground-based measurements and satellite images. The time series were acquired by a network of automatic agrometeorological stations, belonging to the Institute of Agrophysics PAS in Lublin, and a series of SMOS satellite images. The effect of altitude on surface soil moisture on a local scale was examined. For the years 2010-2011, time series of soil moisture measured on the ground and from satellite in Eastern Poland were analysed, taking into account the properties of the soil. Surface soil moisture distribution maps were obtained for Poland and their properties were tested, taking into account the soils granulometric fractions. All analyses were performed using statistical and geostatistical methods.

It was concluded that locally a negative correlation between soil moisture and altitude exists. SMOS satellite measurements reflect well the trends of soil moisture observed on the ground and can be used to detect wet areas, the phenomena of drought, snow and frost. SMOS satellite indicates soil moisture content usually lower than the in situ measurements, although this depends on the soil properties and the environment around the ground reference. Measurements of soil moisture using ASAR satellite instrument are affected by large error due to the presence of vegetation, which underestimates the resulting soil moisture. Taking into account the soil moisture in Eastern Poland, year 2011 was drier and more variable than 2010. In the event of interference of satellite measurements, resulting in some loss of the data, geostatistical methods allow for a good interpolation of missing measurements.