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ispartof: VADOSE ZONE JOURNAL vol:21 issue:1 status: published

Multiannual data (2016–2018) from 12 weighed lysimeters (four soil types with textures ranging from sandy loam to silt loam, three replicates) of the TERENO SOILCan network were used to evaluate if evaporation (E) rates could be predicted from weather data using the FAO Penman–Monteith (PM) method combined with soil water flow simulations using the Richards equation. Soil hydraulic properties (SHPs) were estimated either from soil texture using the ROSETTA pedotransfer functions, from in situ measured water retention curves, or from soil surface water contents using inverse modeling. In all years, E was water limited and the measured evaporation rates (Em) surprisingly did not vary significantly among the four different soil types. When SHPs derived from pedotransfer functions were used, simulated evaporation rates of the finer textured soils overestimated the measured ones considerably. Better agreement was obtained when simulations were based on in situ measured or inversely estimated SHPs. The SHPs estimated from pedotransfer functions represented unrealistically large characteristic lengths of evaporation (Lc), and Lc was found to be a useful characteristic to constrain estimates of SHPs. Also, when soil evaporation was water limited and Em rates were below Epot (PM evaporation scaled by an empirical coefficient), the diurnal dynamics of Em followed those of Epot. The Richards equation that considers only isothermal liquid water flow did not reproduce these dynamics caused by temperature dependent vapor transport in the soil.

Terrestrial evapotranspiration (ET) is the second largest water flux in the global water cycle. It can be measured with different techniques; weighable lysimeters can provide very accurate measurements, and some very long‐term time series exist. However, these lysimeter time series are affected by data gaps that must be filled to estimate actual ET totals and long‐term trends. In this paper, we explore four different gap‐filling methods: the potential ET‐method, the ratio method, the FAO‐based water balance method, and HYDRUS modeling. These gap‐filling methods were evaluated for three time series of actual ET measured by lysimeters and meteorological data of three European sites. Separate evaluations were made for the five driest and five wettest April–October periods to investigate whether the performance of the gap‐filling methods was affected by hydrological conditions. Series of random gaps were artificially created for the three time series, including gaps of four different lengths. Actual ET was estimated for these gaps with the gap‐filling methods, which were evaluated based on RMSE and mean bias error. The results show that the ratio method outperformed other methods for gap filling of lysimeter data for Basel (Switzerland), whereas the HYDRUS method outperformed other methods for Rheindahlen (Germany). For Rietholzbach (Switzerland), the different methods performed very similarly, except that the FAO method gives slightly larger RMSEs. The gap‐filling methods do not perform very differently for dry and wet conditions. The ratio method is recommended for filling smaller gaps, and the HYDRUS method is recommended for longer gaps of 30 d., Vadose Zone Journal, 19 (1), ISSN:1539-1663

© 2019 The Author(s). Roots are known to use biopores as preferential growth pathways to overcome hard soil layers and access subsoil water resources. This study evaluates root- biopore interactions at the root-system scale under different soil physical and environmental conditions using a mechanistic simulation model and extensive experimental field data. In a field experiment, spring wheat (Triticum aestivum L.) was grown on silt loam with a large biopore density. X-ray computed tomography scans of soil columns from the field site were used to provide a realistic biopore network as input for the three-dimensional numerical R-SWMS model, which was then applied to simulate root architecture as well as water flow in the root-biopore-soil continuum. The model was calibrated against observed root length densities in both the bulk soil and biopores by optimizing root growth model input parameters. By implementing known interactions between root growth and soil penetration resistance into our model, we could simulate root systems whose response to biopores in the soil corresponded well to experimental observations described in the literature, such as increased total root length and increased rooting depth. For all considered soil physical (soil texture and bulk density) and environmental conditions (years of varying dryness), we found biopores to substantially mitigate transpiration deficits in times of drought by allowing roots to take up water from wetter and deeper soil layers. This was even the case when assuming reduced root water uptake in biopores due to limited root-soil contact. The beneficial impact of biopores on root water uptake was larger for more compact and less conductive soils. ispartof: VADOSE ZONE JOURNAL vol:18 issue:1 status: published

A process-based knowledge of the sorption mechanisms in soils is a prerequisite for the prediction of radionuclide transport in soils, plant availability, and leaching risk into groundwater. The present study combined batch sorption experiments of Cs+ and Sr2+ in agricultural soils of differing soil texture with numerical experiments using PHREEQC to identify key processes of sorption at different temperatures. Sorption was simulated for both radionuclides using cation exchange models. In addition, surface complexation was integrated into the reaction network for Sr2+. Our geochemical simulations identified cation exchange on illite as the dominant sorption process for Cs+. Selection of the site types in Cs+ sorption was mainly driven by Cs+ concentration. At low Cs+ concentrations the highly selective frayed edge sites dominated sorption behavior, while less affine site types on illite constituted the major sorption partners at high concentrations. We identified undefined cation exchange as the dominant sorption process for Sr2+, followed by surface complexation on organic matter. These process-based analyses were the basis for field-scale simulations to predict the leaching risk of Cs and Sr radionuclides in agricultural soils under humid climate conditions. For both soils and radionuclides, the distribution coefficients (Kd) varied distinctly with time in shallow layers due to changes in temperature, saturation, and the prevailing dominant sorption processes. During a 3-yr-simulation period, 137Cs+ migrated to depths of 3.6 cm (silty loam) and 7.6 cm (sandy loam), while 90Sr2+ migrated to depths of 15.6 cm (silty loam) and 23.6 cm (sandy loam) due to competitive sorption of infiltrating Ca2+ and Mg2+ ions reducing 90Sr2+ sorption and displacing 90Sr2+ from its exchange sites.

Soil greenhouse gas (GHG) emissions contribute to global warming. To support mitigation measures against global warming, it is important to understand the controlling processes of GHG emissions. Previous studies focusing mainly on paddy rice fields or wetlands showed a strong relationship between soil redox potential and GHG emission (e.g., N2O). However, the interpretation of redox potentials for the understanding of the controlling factors of GHG emission is limited due to the low number of continuous redox measurements in most ecosystems. Recent sensor developments open the possibility for the long-term monitoring of field-scale soil redox potential changes. We performed laboratory lysimeter experiments to investigate how changes in the redox potential, induced by changes in the water level, affect GHG emissions from agricultural soil. Under our experimental conditions, we found that N2O emissions followed closely the changes in redox potential. The dynamics of redox potential were induced by changing the water-table depth in a laboratory lysimeter. Before fertilization during saturated conditions, we found a clear negative correlation between redox potentials and N2O emission rates. After switching from saturated to unsaturated conditions, N2O emission quickly decreased, indicating denitrification as the main source of N2O. In contrast, the emissions of CO2 increased with increasing soil redox potentials. After fertilization, N2O emission peaked at high redox potential, suggesting nitrification as the main production pathway, which was confirmed by isotope analysis of N2O. We propose that redox potential measurements are a viable method for better understanding of the controlling factors of GHG emissions, for the differentiation between different source processes, and for the improvement of process-based GHG models.

Evaporation from bare soil surfaces can be restrained to a great extent with the development of a dry layer at the soil surface where capillary hydraulic conductance ceases and water flow proceeds only by gas phase transport. Model calculations and preliminary experiments with model porous media have shown that this surface layer can be very thin. An accurate characterization of these processes is required, which is provided by noninvasive magnetic resonance (MR) methods. The evaporative drying of a silt loam and a sandy loam was monitored at high spatial resolution in laboratory experiments. The MR data were used to assess the performance of two numerical models: (i) the Richards equation, which considers isothermal liquid water flow, and (ii) a coupled soil water, heat, and vapor flow numerical model. The experimental results reveal two distinct drying regimes for both soil types where, at the onset of the second evaporation stage, a dry surface zone developed with increasing thickness over time. This layer revealed that water loss inside the soil coincided with a relatively low evaporation rate as the liquid continuity to the soil surface vanished. The modeling results clearly demonstrated the need to consider heat and vapor flow. It was shown, as a proof of principle, that MR relaxation time spectra may serve as a proxy to follow desaturation processes where spatially resolved transverse relaxation can reveal a secondary evaporation front.

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

Limited knowledge about the spatial distribution of aquifer properties typically constrains our ability to predict subsurface flow and transport. Here we investigate the value of using high resolution full-waveform inversion of cross-borehole ground penetrating radar (GPR) data for aquifer characterization. By stitching together GPR tomograms from multiple adjacent crosshole planes, we are able to image, with a decimeter scale resolution, the dielectric permittivity and electrical conductivity of an alluvial aquifer along cross sections of 50 m length and 10 m depth. A logistic regression model is employed to predict the spatial distribution of lithological facies on the basis of the GPR results. Vertical profiles of porosity and hydraulic conductivity from direct-push, flowmeter and grain size data suggest that the GPR predicted facies classification is meaningful with regard to porosity and hydraulic conductivity, even though the distributions of individual facies show some overlap and the absolute hydraulic conductivities from the different methods (direct-push, flowmeter, grain size) differ up to approximately one order of magnitude. Comparison of the GPR predicted facies architecture with tracer test data suggests that the plume splitting observed in a tracer experiment was caused by a hydraulically low-conductive sand layer with a thickness of only a few decimeters. Because this sand layer is identified by GPR full-waveform inversion but not by conventional GPR ray-based inversion we conclude that the improvement in spatial resolution due to full-waveform inversion is crucial to detect small-scale aquifer structures that are highly relevant for solute transport.