A broadband soil dielectric spectra retrieval approach ( 1 MHz⁻ 2 GHz) has been implemented for a layered half space. The inversion kernel consists of a two-port transmission line forward model in ...the frequency domain and a constitutive material equation based on a power law soil mixture rule (Complex Refractive Index Model - CRIM). The spatially-distributed retrieval of broadband dielectric spectra was achieved with a global optimization approach based on a Shuffled Complex Evolution (SCE) algorithm using the full set of the scattering parameters. For each layer, the broadband dielectric spectra were retrieved with the corresponding parameters thickness, porosity, water saturation and electrical conductivity of the aqueous pore solution. For the validation of the approach, a coaxial transmission line cell measured with a network analyzer was used. The possibilities and limitations of the inverse parameter estimation were numerically analyzed in four scenarios. Expected and retrieved layer thicknesses, soil properties and broadband dielectric spectra in each scenario were in reasonable agreement. Hence, the model is suitable for an estimation of in-homogeneous material parameter distributions. Moreover, the proposed frequency domain approach allows an automatic adaptation of layer number and thickness or regular grids in time and/or space.
Environmental sensor networks produce continuously increasing volumes of raw data that need to be transformed into usable data for monitoring ongoing environmental changes and decision-support. The ...crucial challenge is providing data in real-time, which requires the rigorous automation of quality control (QC) workflows using suitable software tools. We present the System for automated Quality Control (SaQC), a software package for the automated quality control of environmental time series data that is universal and that can be expanded in its set of domain-agnostic QC and processing functionalities, while at the same time being user-friendly in its low-code configuration environment. Two applications present the configuration of basic and advanced quality control applications using SaQC. We also elaborate on the explicit user controls over the handling of quality flags and how SaQC can be used to make QC-workflows traceable and reproducible, thus promoting FAIR data streams of high quality.
•We present the Python package System for automated Quality Control (SaQC).•SaQC facilitates the implementation of workflows for automated quality control•It is designed for domain scientists that manage environmental sensor networks.•It is universal, user-friendly and can be extended.•It addresses crucial challenges regarding quality control and the FAIRness of data streams.
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