Abstract

The assessment of water resources in soil is important in understanding the water cycle in the natural environment and the processes of water exchange between the soil and the atmosphere. The main objective of the study was to assess water resources (in 2010–2013) in the topsoil from satellite (SMOS) and in situ (ground) measurements using the SWEX_PD approach (Soil Water EXtent at Penetration Depth). The SWEX_PD is a result of multiplying soil moisture (SM) and radiation penetration depth (PD) for each pixel derived from the SMOS satellite. The PD, being a manifold of the wavelength λ0 equal to 21 cm, was determined from the weekly SMOS L2 measurement data based on the real and imaginary part of complex dielectric constant. The SWEX_PD data were compared with soil water resources (WR) calculated from the sum of components derived from multiplication of soil moisture (SM) and layer thickness in nine agrometeorological stations located along the eastern border of Poland. Each study site consisted of seven neighbouring Discrete Global Grid pixels (nodes spaced at 15 km) including the central ones with agrometeorological stations. The study area included different types of soils and land covers. The agreement between the water resources obtained from the SWEX_PD and ground measurements (WR) was quantified using classical statistics and Bland–Altman's plots. Calibrated Layer Thickness (CLT = dbias) from 8 to 28 cm was obtained with a low values of bias (close to zero), limits of agreements, and confidence intervals for all the SWEX_PD, depending on the pixel location. The results revealed that the use of the SWEX_PD for assessing soil water resources is the most reliable approach in the study area. Additionally, the data from Bland–Altman plots and the equation proposed in these studies allowed calculation of the Equivalent Layer Thickness (ELT = d_{ei}^{SWEX}), which corresponds to the water resources derived from the SMOS satellite at the same time as (SM) measurements performed in the agrometeorological stations. The ranges of the mean, standard deviation, minimum, maximum, and coefficient of variation (CV) of ELT among all pixels and stations were 8.28–28.7 cm, 3.27–12.66 cm, 3.03–10.87 cm, 19.23–94.97 cm, and 24.72–98.79%, respectively. The ranges of the characteristics depended on environmental conditions and their means were close to the values of the calibrated layer thickness. The impacts of soil texture, organic matter, vegetation, and their interactive effects on the differentiation and agreement of soil water resources obtained from SWEX_PD vs. data from ground measurements in the study area are discussed. Further studies are required to address the impact of the environmental factors to improve the assessment of soil water resources based on satellite SM products (retrievals).

Highlights

  • The results revealed that the use of the Soil Water EXtent at Penetration Depth (SWEX_PD) for assessing soil water resources is the most reliable approach in the study area

  • Comparison of soil water resources from SWEX_PD with ground measurements WR. The use of both coarse and exact steps depending on the soil moisture (SM) sensor types and their installation depths allowed estimation of soil depths at which the soil water resources from ground measurements (WRj0) were similar or equal to those from the SWEX_PDjk based on the satellite data, as quantified by the Bland–Altman plots

  • The majority of SWEX_PDjk − WRj0 vs. (SWEX_PDjk + WRj0)/2 values were within the defined limit of agreement (LoA), some were within confidence interval (CI), and only few were beyond the areas of both LoAs and CIs

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Summary

Objectives

The main objective of the study was to assess water resources in the topsoil from satellite (SMOS) and in situ measurements using the SWEX_PD approach (Soil Water EXtent at Penetration Depth). The aim of this study was to assess soil water resources using the new concept Soil Water EXtent at Penetration Depth (SWEX_PD) as the product of soil moisture (SM) and radiation penetration depth (PD), both from SMOS L2 satellite data

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