Soils represent a major global source and sink of greenhouse gases (GHGs). Many studies of GHG fluxes between soil, plant and atmosphere rely on chamber measurements. Different chamber techniques have been developed over the last decades, each characterised by different requirements and limitations. In this manuscript, we focus on the non‐steady‐state technique which is widely used for manual measurements but also in automatic systems. Although the measurement method appears very simple, experience gained over the years shows that there are many details which have to be taken into account to obtain reliable measurement results.This manuscript aims to share lessons learnt and pass on experiences in order to assist the reader with possible questions or unexpected challenges, ranging from the planning of the design of studies and chambers to the practical handling of the chambers and the quality assurance of the gas and data analysis. This concise introduction refers to a more extensive Best Practice Guideline initiated by the Working Group Soil Gases (AG Bodengase) of the German Soil Science Society (Deutsche Bodenkundliche Gesellschaft). The intention was to collect and aggregate the expertise of different working groups in the research field. As a compendium, this Best Practice Guideline is intended to help both beginners and experts to meet the practical and theoretical challenges of measuring soil gas fluxes with non‐steady‐state chamber systems and to improve the quality of the individual flux measurements and thus entire GHG studies by reducing sources of uncertainty and error.

Soil hydraulic properties are often derived indirectly, i.e. computed from easily available soil properties with pedotransfer functions (PTFs), when those are needed for catchment, regional or continental scale applications. When predicted soil hydraulic parameters are used for the modelling of the state and flux of water in soils, uncertainty of the computed values can provide more detailed information when drawing conclusions. The aim of this study was to update the previously published European PTFs (Tóth et al., 2015, euptf v1.4.0) by providing prediction uncertainty calculation built into the transfer functions. The new set of algorithms was derived for point predictions of soil water content at saturation (0 cm matric potential head), field capacity (both −100 and −330 cm matric potential head), wilting point (−15 000 cm matric potential head), plant available water, and saturated hydraulic conductivity, as well as the Mualem–van Genuchten model parameters of the moisture retention and hydraulic conductivity curve. The minimum set of input properties for the prediction is soil depth and sand, silt and clay content. The effect of including additional information like soil organic carbon content, bulk density, calcium carbonate content, pH and cation exchange capacity were extensively analysed. The PTFs were derived adopting the random forest method. The advantage of the new PTFs is that they (i) provide information about prediction uncertainty, (ii) are significantly more accurate than the euptfv1, (iii) can be applied for more predictor variable combinations than the euptfv1, 32 instead of 5, and (iv) are now also derived for the prediction of water content at −100 cm matric potential head and plant available water content. A practical guidance on how to use the derived PTFs is provided.

A generalized modular framework for partitioning soil hydraulic property (SHP) functions into a capillary and a noncapillary part is developed. The full water retention curve (WRC) is modeled as a weighted sum of a parametric capillary saturation function and a new general model for the noncapillary saturation function. This model is directly computed from any selected capillary saturation function. With it, a physically complete, continuous, and flexible representation of the WRC is achieved, ensuring zero water content at oven dryness. In a modular and hierarchical framework, the expressions for the capillary and noncapillary saturation function are used to calculate the respective hydraulic conductivity curves (HCC). This is achieved by adopting Mualem's integral for the capillary part of the HCC only and calculating the noncapillary HCC directly from the new noncapillary saturation function. This leads to consistent descriptions of measured HCC data, including the often observed change in slope beyond −100 cm pressure head. Compared to the classical van Genuchten‐Mualem approach, it requires only one additional model parameter. The SHP framework model describes both WRC and HCC adequately and coherently. We demonstrate the suitability of the SHP framework and versatility by describing measured WRC and HCC data across the full moisture range using soil samples from a wide range of textures and origins. The modular framework was implemented in the soil physics and soil hydrology (spsh) R‐package, available from the Comprehensive R Archive Network. It contains several SHP models, model parameter estimation, and features options for goodness of fit statistics, and model selection.

High-resolution climate model projections for a range of emission scenarios are needed for designing regional and local adaptation strategies and planning in the context of climate change. To this end, the future climate simulations of global circulation models (GCMs) are the main sources of critical information. However, these simulations are not only coarse in resolution but also associated with biases and high uncertainty. To make the simulations useful for impact modeling at regional and local level, we utilized thebias correction constructed analogues with quantile mapping reordering(BCCAQ) statistical downscaling technique to produce a 10 km spatial resolution climate change projections database based on 16 CMIP6 GCMs under three emission scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5). The downscaling strategy was evaluated using aperfect siblingapproach and detailed results are presented by taking two contrasting (the worst and best performing models) GCMs as a showcase. The evaluation results demonstrate that the downscaling approach substantially reduced model biases and generated higher resolution daily data compared to the original GCM outputs.

In ombrotrophic peatlands, the moisture content of the vadose zone (acrotelm) controls oxygen diffusion rates, redox state, and the turnover of organic matter. Whether peatlands act as sinks or sources of atmospheric carbon thus relies on variably saturated flow processes. The Richards equation is the standard model for water flow in soils, but it is not clear whether it can be applied to simulate water flow in live Sphagnum moss. Transient laboratory evaporation experiments were conducted to observe evaporative water fluxes in the acrotelm, containing living Sphagnum moss, and a deeper layer containing decomposed moss peat. The experimental data were evaluated by inverse modeling using the Richards equation as process model for variably‐saturated flow. It was tested whether water fluxes and time series of measured pressure heads during evaporation could be simulated. The results showed that the measurements could be matched very well providing the hydraulic properties are represented by a suitable model. For this, a trimodal parametrization of the underlying pore‐size distribution was necessary which reflects three distinct pore systems of the Sphagnum constituted by inter‐, intra‐, and inner‐plant water. While the traditional van Genuchten‐Mualem model led to great discrepancies, the physically more comprehensive Peters‐Durner‐Iden model which accounts for capillary and noncapillary flow, led to a more consistent description of the observations. We conclude that the Richards equation is a valid process description for variably saturated moisture fluxes over a wide pressure range in peatlands supporting the conceptualization of the live moss as part of the vadose zone.