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Despite previous reports on European growing seasons lengthening due to global warming, evidence shows that this trend has been reversing in the past decade due to increased transpiration needs. To asses this, we used an innovative method along with space-based observations to determine the timing of greening and dormancy and then to determine existing trends of them and causes. Early greening still occurs, albeit at slower rates than before. However, a recent (2011–2020) shift in the timing of dormancy has caused the season length to decrease back to 1980s levels. This shortening of season length is attributed primarily to higher atmospheric water demand in summer that suppresses transpiration even for soil moisture levels as of previous years. Transpiration suppression implies that vegetation is unable to meet the high transpiration needs. Our results have implications for future management of European ecosystems (e.g., net carbon balance and water and energy exchange with atmosphere) in a warmer world., Communications Earth & Environment, 4 (1), ISSN:2662-4435

In his seminal paper on the solution of the infiltration equation, Philip (1969), https://doi.org/10.1016/b978-1-4831-9936-8.50010-6 proposed a gravity time, tgrav, to estimate practical convergence time and the time domain validity of his infinite time series expansion, TSE, for describing the transient state. The parameter tgrav refers to a point in time where infiltration is dominated equally by capillarity and gravity as derived from the first two (dominant) terms of the TSE. Evidence suggests that applicability of the truncated two-term equation of Philip has a time limit requiring higher-order TSE terms to better describe the infiltration process for times exceeding that limit. Since the conceptual definition of tgrav is valid regardless of the infiltration model used, we opted to reformulate tgrav using the analytic implicit model proposed by Parlange et al. (1982), https://doi.org/10.1097/00010694-198206000-00001 valid for all times and related TSE. Our derived gravity times ensure a given accuracy of the approximations describing transient states, while also providing insight about the times needed to reach steady state. In addition to the roles of soil sorptivity (S) and the saturated (Ks) and initial (Ki) hydraulic conductivities, we explored the effects of a soil specific shape parameter β, involved in Parlange's model and related to the type of soil, on the behavior of tgrav. We show that the reformulated tgrav (notably (Formula presented.) where F(β) is a β-dependent function) is about three times larger than the classical tgrav given by (Formula presented.). The differences between the classical tgrav,Philip and the reformulated tgrav increase for fine-textured soils, attributed to the time needed to attain steady-state infiltration and thus i + nfiltration for inferring soil hydraulic properties. Results show that the proposed tgrav is a better indicator of time domain validity than tgrav,Philip. For the attainment of steady-state infiltration, the reformulated tgrav is suitable for coarse-textured soils. Still neither the reformulated tgrav nor the classical tgrav,Philip are suitable for fine-textured soils for which tgrav is too conservative and tgrav,Philip too short. Using tgrav will improve predictions of the soil hydraulic parameters (particularly Ks) from infiltration data compared to tgrav,Philip., Water Resources Research, 58 (5), ISSN:0043-1397, ISSN:1944-7973

Many different equations have been proposed to describe quantitatively one-dimensional soil water infiltration. The unknown coefficients of these equations characterize soil hydraulic properties and may be estimated from a n record, (Formula presented.), of cumulative infiltration measurements using curve fitting techniques. The two-term infiltration equation, (Formula presented.), of Philip has been widely used to describe measured infiltration data. This function enjoys a solid mathematical–physical underpinning and admits a closed-form solution for the soil sorptivity, S [L T−1/2], and multiple, c [−], of the saturated hydraulic conductivity, Ks [L T−1]. However, Philip's two-term equation has a limited time validity, tvalid [T], and thus cumulative infiltration data, (Formula presented.), beyond (Formula presented.) will corrupt the estimates of S and Ks. This paper introduces a novel method for estimating S, c, Ks, and tvalid of Philip's two-term infiltration equation. This method, coined parasite inversion, use as vehicle Parlange's three-parameter infiltration equation. As prerequisite to our method, we present as secondary contribution an exact, robust and efficient numerical solution of Parlange's infiltration equation. This solution admits Bayesian parameter estimation with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm and yields as byproduct the marginal distribution of Parlange's β parameter. We evaluate our method for 12 USDA soil types using synthetic infiltration data simulated with HYDRUS-1D. An excellent match is observed between the inferred values of S and Ks and their “true” values known beforehand. Furthermore, our estimates of c and tvalid correlate well with soil texture, corroborate linearity of the (Formula presented.) relationship for (Formula presented.), and fall within reported ranges. A cumulative vertical infiltration of about 2.5cm may serve as guideline for the time-validity of Philip's two-term infiltration equation.

Purpose: Pesticide contamination of river waters is a global problem, and therefore, authorities regularly monitor the water quality status. Especially, flood events might transport large pesticide loads downstream and impact adjacent areas such as sensible floodplain environments by deposing particle bound pesticides or by contaminating the environments by dissolved substances directly. Unfortunately, only little attempts were made to quantify the pesticide pollution of such environments, as the monitoring of soil and sediment contamination is by far more time consuming and complicated compared to the analysis of water samples., Materials and methods: In the study presented, we therefore used a holistic approach starting with the reconstruction of the inundation characteristics of a floodplain located in the upper part of the river Elbe, Germany, by using nearby gauging data, screened databases for pesticide concentrations and calculated pesticide loads, and finally, sampled the floodplain soils along an elevation (inundation) gradient., Results: As expected, the reconstructed inundation characteristics showed that the low-lying areas of the backwater inflow of the floodplain were flooded more frequently compared to the areas at higher elevation, whereby even the highest elevations sampled were at least flooded during each decade. Furthermore, pesticide concentrations of the river waters and calculated pesticide loads revealed that 13 pesticides can be found regularly, whereby atrazine, terbuthylazine, metazachlor, metolachlor, isoproturon, and chlorotoluron are the main contaminants., Conclusion: Concluding, a spatial pattern in the contamination could be detected. High residues of simazine and ethofumesate were associated with areas of less and more frequent inundations, respectively. The transformation products of atrazine and terbuthylazine (2-hydroxy-atrazine and 2-hydroxy-terbuthylazine) were detected, whereby the quantity could be well explained by the inundation characteristics and pesticide loads of the river water., Forschungszentrum Jülich GmbH (4205)

With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Ob-serving System for Europe L-band SAR (ROSE-L) and its integration into existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. The SARSense campaign was conducted between June and August 2019 to investigate the potential for estimating soil and plant parameters at the agricultural test site in Selhausen (Germany). It included C- and L-band air- and space-borne observations accompanied by extensive in situ soil and plant sampling as well as unmanned aerial system (UAS) based multi-spectral and thermal infrared measurements. In this regard, we introduce a new publicly available SAR data set and present the first analysis of C- and L-band co- and cross-polarized backscattering signals regarding their sensitivity to soil and plant parameters. Results indicate that a multi-fre-quency approach is relevant to disentangle soil and plant contributions to the SAR signal and to identify specific scattering mechanisms associated with the characteristics of different crop type, especially for root crops and cereals.

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.

Soil salinization in irrigated croplands is a key factor in soil degradation and directly affects plant growth and soil hydrological processes such as evaporation and infiltration. In order to support the development of appropriate irrigation strategies, it is important to understand the impact of salt crusts that form during evaporation from saline soils on water flow. The determination of the effective hydraulic properties of salt crusts that control evaporation is still a challenge due to the lack of suitable measurement techniques. In this study, we propose an approach using gas flow to determine the permeability of salt crusts obtained from evaporation of unsaturated saline solutions of three different salt types and investigate the impact of the crust permeability on evaporation. For this, sand columns saturated with initial solutions of sodium chloride (NaCl), magnesium sulfate (MgSO4), and sodium sulfate (Na2SO4) at concentrations corresponding to 33% of the solubility limit were prepared and allowed to evaporate in order to induce crust formation. The results demonstrated that the intrinsic permeability of the dry salt crusts was similar for the different types of salts (&asymp, 4&times, 10&minus, 12m2), whereas the evaporation of the prepared columns differed significantly. We conclude that the intrinsic crust permeability only partly explains the impact of the crust on evaporation. Other effective crust properties such as porosity or unsaturated hydraulic properties may provide additional information on how evaporation is affected by salt crust formation.

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

Terrestrial Essential Climate Variables, known as terrestrial ECVs, are key sources of information for both application- and scientific- oriented research. A large number of global terrestrial ECV products have been derived from satellite observations, and more are forthcoming. To unlock the full potential of these products, end-users need to know their uncertainties and error magnitudes. Due to the lack of conformity among validation strategies, a wide range of validation approaches have been employed to assess the quality of these products, and have resulted in reduced comparability even for the same terrestrial ECV. Addressing this challenge in validation practices requires the use of unified, standard, publicly available, traceable and objective validation procedures that are operational for all products of a specific terrestrial ECV, and preferably also applicable for all ECVs at the global scale. This can allow end-users to perform comparative assessments. To this end, the current study aims to investigate the readiness status of a selected group of seven global long-term satellite-based terrestrial ECVs for operational validation. Selected variables are Leaf Area Index (LAI), Land Surface Temperature (LST), Evapotranspiration (ET), Soil Moisture (SM), Albedo, the fraction of Absorbed Photosynthetically Active Radiation (fAPAR), and Land Cover (LC). For each of these terrestrial ECVs, we reviewed key prerequisites and primary tools [notably, long term global product availability, globally distributed in situ measurement availability, a validation good practice protocol, and an online validation platform] required for developing an operational validation system. With respect to the “readiness level”, the investigation results demonstrate that LAI, SM, and LC are at the highest level of readiness for moving toward a full operational validation at the global scale. However, ET is at the lowest level of readiness, mainly due to the lack of standard validation good practice protocol and lack of a pilot online validation platform. The remainder of the selected terrestrial ECVs are identified to be at mid-level readiness, mainly because either a validation platform (i.e., LST and albedo) or good practice protocol (i.e., fAPAR) still needs to be developed. This review can pave the way for open-access, traceable, transparent, and operational validation procedures of satellite-based global terrestrial ECVs.

How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are important questions that need to be answered to describe water fluxes in the soil–plant–atmosphere system. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU of winter wheat using the empirical Feddes–Jarvis (FJ) model and the physically based Couvreur (C) model for different soil water conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities, and root distributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and treatments which are accounted for by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWU could be accounted for directly by the physically based RWU model but not by empirical models that use normalized root density functions.

© 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

Infiltration in soils is a key process that partitions precipitation at the land surface into surface runoff and water that enters the soil profile. We reviewed the basic principles of water infiltration in soils and we analyzed approaches commonly used in land surface models (LSMs) to quantify infiltration as well as its numerical implementation and sensitivity to model parameters. We reviewed methods to upscale infiltration from the point to the field, hillslope, and grid cell scales of LSMs. Despite the progress that has been made, upscaling of local-scale infiltration processes to the grid scale used in LSMs is still far from being treated rigorously. We still lack a consistent theoretical framework to predict effective fluxes and parameters that control infiltration in LSMs. Our analysis shows that there is a large variety of approaches used to estimate soil hydraulic properties. Novel, highly resolved soil information at higher resolutions than the grid scale of LSMs may help in better quantifying subgrid variability of key infiltration parameters. Currently, only a few LSMs consider the impact of soil structure on soil hydraulic properties. Finally, we identified several processes not yet considered in LSMs that are known to strongly influence infiltration. Especially, the impact of soil structure on infiltration requires further research. To tackle these challenges and integrate current knowledge on soil processes affecting infiltration processes into LSMs, we advocate a stronger exchange and scientific interaction between the soil and the land surface modeling communities., Vadose Zone Journal, 18 (1), ISSN:1539-1663

For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

[EN] Irrigation is essential for maintaining food production in water-scarce regions. The irrigation need depends on the water content of the soil, which we measured with the novel technique of cosmic-ray neutron sensing (CRNS). The potential of the CRNS technique for drip irrigation scheduling was explored in this study for the Picassent site near Valencia, Spain. To support the experimental evidence, the neutron transport simulation URANOS was used to simulate the effect of drip irrigation on the neutron counts. The overall soil water content (SWC) in the CRNS footprint was characterized with a root mean square error, Dazhi Li was funded by a stipend from the government of China (CSC scholarship). The research was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Project 414050972, Research Unit FOR 2694 "Cosmic Sense." We are also thankful to our colleagues at the Instituto Valenciano de Investigaciones Agrarias and Universitat Politecnica de Valencia for the installation of the soil moisture sensors and for conducting field measurements

Droughts and heat waves deeply interact with the exchange of energy and matter between land surface and atmosphere. The conditions associated with a combined heat wave and drought can have positive or negative effects on the sensible heat flux (H), latent heat flux (LE), and net flux of CO2 (NEE). In return, while each of these fluxes can exert different local feedbacks on temperature, atmospheric humidity and soil moisture, all of them result in bulk heating of the troposphere (H and LE through direct local and indirect non-local heat transfer, and NEE through radiative forcing). H is positively affected by increased solar irradiation, but can be supressed by advection of warm air diminishing the gradient between surface and air temperature. Potential LE is positively affected by irradiation, temperature and water vapour pressure deficit, but actual LE can be suppressed by stomatal closure of plants and by reduced soil moisture from low rainfall and high past LE. NEE is the result of plant photosynthesis (GPP) and plant and soil respiration (R), both of which can be enhanced by high temperatures or irradiation, and suppressed by drought. Focusing on direct measurements mostly by a network of Eddy-Covariance (EC) stations of the ICOS (www.icosri.eu), TERENO (www.tereno.net) and other networks, we hypothesize that the net effect of the 2018 event at a site, and thus its feedback on global warming, depends on the balance between co-existing positive and negative effects of the combined heat wave and drought on the respective fluxes. Variables such as albedo, growing degreedays (GDD), soil moisture and ecosystem-level water use efficiency help to separate these co-existing positive and negative effects from each other. Preliminary results indicate different degrees of heterogeneity between sites fordifferent variables. As expected, reduced precipitation and soil moisture, as well as increased GDD, could be found at almost all sites in the affected region. NEE was mostly less negative, indicating a weaker sink or even a source forCO2, as expected from past studies on earlier events. The network density and number of site-years available now confirms that this was true for all major ecosystem types - forest, grassland and (rainfed) cropland, and resultedin increased atmospheric CO2 concentrations. However, notable exceptions occurred at elevated low mountain range sites and during early stages of the event, supporting the hypothesis of a balance between positive andnegative effects, where the former may prevail at strongly energy-limited sites with a usually large water surplus. H was mostly above-average, indicating that local heat production contributed to the event and was typically notsuppressed by warm air advection. LE as well as inferred GPP and R reacted most heterogeneously across sites, demonstrating the large discrepancy between potentially high fluxes due to high irradiation and temperature on theone hand, and suppression by water shortage on the other hand. Despite the variability in LE, its relation to NEE was such that ecosystem-level water use was less efficient than usual at the majority of sites through reduced CO2uptake.

There has been much effort to improve the performance of pedotransfer functions (PTFs) using intelligent algorithms, but the issue of covariate shift, i.e., different probability distributions in training and testing datasets, and its impact on prediction uncertainty of PTFs has been rarely addressed. The common practice in PTF generation is to randomly separate the dataset into training and testing subsets, and the outcomes of this random selection may be different if the process is subject to covariate shift. We evaluated the impact of covariate shift generated by data shuffling and detected by Kolmogorov–Smirnov test for the prediction of water contents using soil databases from Denmark and Brazil. The soil water contents at different pressure heads were predicted by developing linear and stepwise regression besides machine learning based PTFs including Gaussian process regression and ensemble method. Regression based PTFs for the Brazilian dataset resulted in better predictions compared with machine learning methods, which in their turn estimated high water contents in Danish soils more accurately. One hundred PTFs were developed for water content at specific pressure heads by data shuffling. From these, 100 sets of fitted van Genuchten parameters were obtained representing the generated uncertainty. Data shuffling led to covariate shift, resulting in uncertainty in water content prediction by the PTFs. Inherent variability of data may lead to increased prediction uncertainty. For correlated data, simple regression models performed as good as sophisticated machine learning methods. Using PTF‐predicted water contents for van Genuchten retention parameter fitting may lead to a high uncertainty.

Ground penetrating radar (GPR) has shown a high potential to derive soil water content (SWC) at different scales. In this study, we combined multiple horizontal GPR measurements at different depths to investigate the spatial and temporal variability of the SWC under cropped plots. The SWC data were analyzed for four growing seasons between 2014 and 2017, two soil types (gravelly and clayey–silty), two crops (wheat [Triticum aestivum L.] and maize [Zea mays L.]), and three different water treatments. We acquired more than 150 time-lapse GPR datasets along 6-m-long horizontal crossholes at six depths. The GPR SWC distributions are distinct both horizontally and vertically for both soil types. A clear change in SWC can be observed at both sites between the surface layer (>0.3 m) and subsoil. Alternating patches of higher and lower SWC, probably caused by the soil heterogeneity, were observed along the horizontal SWC profiles. To investigate the changes in SWC with time, GPR and time-domain reflectometry (TDR) data were averaged for each depth and compared with changes in precipitation, treatment, and soil type. The high-temporal-resolution TDR and the large-sampling-volume GPR show similar trends in SWC for both sites, but because of the different sensing volumes, different responses were obtained due to the spatial heterogeneity. A difference in spatial variation of the crosshole GPR SWC data was detected between maize and wheat. The results for this 4-yr period indicate the potential of this novel experimental setup to monitor spatial and temporal SWC changes that can be used to study soil–plant–atmosphere interactions.

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.

Accurate estimates of soil hydraulic parameters and dispersivities are crucial to simulate water flow and solute transport in terrestrial systems, particularly in the vadose zone. However, parameters obtained from inverse modeling can be ambiguous when identifying multiple parameters simultaneously and when boundary conditions are not well known. Here, we performed an inverse modeling study in which we estimated soil hydraulic parameters and dispersivities of layered soils from soil water content, matric potential, and stable water isotope ( d 18O) measurements in weighable lysimeter systems. We used different optimization strategies to investigate which observation types are necessary for simultaneously estimating soil hydraulic and solute transport parameters. Combining water content, matric potential, and tracer (e.g., d 18O) data in one objective function (OF) was found to be the best strategy for estimating parameters that can simulate all observed water flow and solute transport variables. A sequential optimization, in which first an OF with only water flow variables and subsequently an OF with transport variables was optimized, performed slightly worse indicating that transport variables contained additional information for estimating soil hydraulic parameters. Hydraulic parameters that were obtained from optimizing OFs that used either water contents or matric potential could not predict non-measured water flow variables. When a bromide (Br−) tracer experiment was simulated using the optimized parameters, the arrival time of the bromide pulse was underestimated. This suggested that Br− sorbed onto clay minerals and amorphous oxides under the prevailing geochemical conditions with low pH values. When accounting for anion adsorption in the simulation, Br− concentrations were well predicted, which validated the dispersivity parameterization.

Ray-based radius estimations of subsurface cylindrical objects such as rebars and pipes from ground-penetrating-radar (GPR) measurements are not accurate because of their approximations. We have developed a novel full-waveform inversion (FWI) approach that uses a full-waveform 3D finite-difference time-domain (FDTD) forward-modeling program to estimate the radius including other object parameters. By using the full waveform of the common-offset GPR data, the shuffled complex evolution (SCE) approach is able to reliably extract the radius of the subsurface cylindrical objects. A combined optimization of radius, medium properties, and the effective source wavelet is necessary. Synthetic and experimental data inversion returns an accurate reconstruction of the cylinder properties, medium properties, and the effective source wavelet. Combining FWI of GPR data using SCE and a 3D FDTD forward model makes the approach easily adaptable for a wide range of other GPR FWI approaches.

Advancing our understanding of Earth system dynamics (ESD) depends on the development of models and other analytical tools that apply physical, biological, and chemical data. This ambition to increase understanding and develop models of ESD based on site observations was the stimulus for creating the networks of Long-Term Ecological Research (LTER), Critical Zone Observatories (CZOs), and others. We organized a survey, the results of which identified pressing gaps in data availability from these networks, in particular for the future development and evaluation of models that represent ESD processes, and provide insights for improvement in both data collection and model integration.From this survey overview of data applications in the context of LTER and CZO research, we identified three challenges: (1) widen application of terrestrial observation network data in Earth system modelling, (2) develop integrated Earth system models that incorporate process representation and data of multiple disciplines, and (3) identify complementarity in measured variables and spatial extent, and promoting synergies in the existing observational networks. These challenges lead to perspectives and recommendations for an improved dialogue between the observation networks and the ESD modelling community, including co-location of sites in the existing networks and further formalizing these recommendations among these communities. Developing these synergies will enable cross-site and cross-network comparison and synthesis studies, which will help produce insights around organizing principles, classifications, and general rules of coupling processes with environmental conditions.

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.

©2017. American Geophysical Union. All Rights Reserved. The Community Land Model (CLM) contains many parameters whose values are uncertain and thus require careful estimation for model application at individual sites. Here we used Bayesian inference with the DiffeRential Evolution Adaptive Metropolis (DREAM(zs)) algorithm to estimate eight CLM v.4.5 ecosystem parameters using 1 year records of half-hourly net ecosystem CO2exchange (NEE) observations of four central European sites with different plant functional types (PFTs). The posterior CLM parameter distributions of each site were estimated per individual season and on a yearly basis. These estimates were then evaluated using NEE data from an independent evaluation period and data from “nearby” FLUXNET sites at ~600 km distance to the original sites. Latent variables (multipliers) were used to treat explicitly uncertainty in the initial carbon-nitrogen pools. The posterior parameter estimates were superior to their default values in their ability to track and explain the measured NEE data of each site. The seasonal parameter values reduced with more than 50% (averaged over all sites) the bias in the simulated NEE values. The most consistent performance of CLM during the evaluation period was found for the posterior parameter values of the forest PFTs, and contrary to the C3-grass and C3-crop sites, the latent variables of the initial pools further enhanced the quality-of-fit. The carbon sink function of the forest PFTs significantly increased with the posterior parameter estimates. We thus conclude that land surface model predictions of carbon stocks and fluxes require careful consideration of uncertain ecological parameters and initial states.

Elemental contents in catchment headwaters are indicative of the load of nutrients and minerals cycled or released from ecosystems, yet little is known about natural colloids (1–1000 nm) and especially natural nanoparticles (NNP, 1–100 nm) as nutrient carriers in forested headwater streams. We hypothesize that the majority of P is bound to NNP in forest streams but that their size and composition varies for different forested headwater systems. Four forested sites in Germany and one in Norway, which differ in total P content, were sampled for stream water and analyzed for colloids. The samples were fractionated using field flow fractionation coupled to inductively coupled plasma–mass spectrometry and an organic C detector. The results showed that NNP and colloids from all sites could be separated into three distinct fractions (approximately 1–20 nm, >20–60 nm, and >60 nm). The elemental concentrations of P, organic C, Al, Si, Fe, and Mn in the fractions differed among the five sites. However, cluster analysis showed that each fraction had unique elemental signatures with different preferential P binding partners. Phosphorus was preferentially associated with Fe in the smallest size fraction, with an increasing contribution of organic-C-associated P as the fraction size increased. The largest fraction was dominated by clay minerals. Also, the data indicated that the relative contribution of the NNP and colloidal fractions for ecosystem nutrient supply rises as total P concentrations decline. The study highlighted the still underestimated importance of NNP for matter transport in forest streams and thus P cycling. This is an open access article under the CC BY-NC-ND license. Proper attribution is required for reuse. No permissions are needed for reuse unless it is derivative or for commercial purposes.

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.

In-situ soil moisture sensors provide highly accurate but very local soil moisture measurements while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, Cosmic-Ray Neutron Sensors (CRNS) allow highly accurate soil moisture estimation at the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNS installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNS were assimilated with the local ensemble transform Kalman filter in the Community Land Model v. 4.5. Data of four, eight and nine CRNS were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map soil moisture predictions improved strongly to a root mean square error of 0.03 cm3/cm3 for the assimilation period and 0.05 cm3/cm3 for the evaluation period. Improvements were limited by the measurement error of CRNS (0.03 cm3/cm3). The positive results obtained with data assimilation of nine CRNS were confirmed by the jackknife experiments with four and eight CRNS used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content at the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

A dynamic tension-controlled bottom boundary of lysimeters allows observing water and matter fluxes in lysimeters that are close to natural field conditions, as pressure heads at the lysimeter bottom are adjusted to measured pressure heads at the same depth in the surrounding field. However lysimeters are often transferred from their sampling location for practical reasons or to study, for example, the effect of climate change on soil functions. This transfer can be accompanied by a change aboveground but also in subsurface conditions that are used to control the bottom boundary and that may affect the soil water balance of lysimeters. This issue is also relevant for lysimeter stations which use a tension-controlled bottom boundary and are not directly installed near the site of excavation. The potential impact of different bottom boundary conditions on the water balance of lysimeters that were transferred in a climate impact experiment (SOILCan) was investigated exemplarily by a numerical study. Results showed that by using nonappropriate pressure heads, which were measured in soil profiles with a different texture and water table depth than the profile where the lysimeter was taken from, had partially large impacts on soil water fluxes, especially when the water table was located within a specific critical range. Different climate conditions between sampling and installation site were buffered by the soil and did not show a strong influence on the bottom boundary control of lysimeters when the groundwater table depth was assumed to remain constant. Considering a change in groundwater table depths due to changing climate tempered the effects of climate change on the soil water balance terms. In general, results demonstrate the importance of a proper control of the lysimeters bottom boundary conditions in studies that investigate the influence of climate change on soil functions and ecosystem variables by transferring lysimeter along climate gradients.

Minimally invasive monitoring of root development and soil states (soil moisture, temperature) in undisturbed soils during a crop growing cycle is a challenging task. Minirhizotron (MR) tubes offer the possibility to view root development in situ with time. Two MR facilities were constructed in two different soils, stony vs. silty, to monitor root growth, root zone processes, and their dependence on soil water availability. To obtain a representative image of the root distribution, 7-m-long tubes were installed horizontally at 10-, 20-, 40-, 60-, 80-, and 120-cm depths. A homemade system was developed to install MR tubes in the silty soil in horizontally drilled straight holes. For the stony soil, the soil rhizotubes were installed in an excavated and subsequently backfilled pit. In both facilities, three subplots were established with different water treatments: rain sheltered, rainfed, and irrigated. To monitor soil moisture, water potential, and soil temperature, time domain reflectometer probes, tensiometers, and matrix water potential sensors were installed. Soil water content profiles in space and time were obtained between two MR tubes using cross-hole ground-penetrating radar along the tubes at different depths. Results from the first growing season of winter wheat (Triticum aestivum L.) after installation demonstrate that differences in root development, soil water, and temperature dynamics can be observed among the different soil types and water treatments. When combined with additional measurements of crop development and transpiration, these data provide key information that is essential to validate and parameterize root development and water uptake models in soil–vegetation–atmosphere transfer models.

Letter from the Editor

NMR relaxometry has developed into a method for rapid pore-size determination of natural porous media. Nevertheless, it is prone to uncertainties because of unknown surface relaxivities which depend mainly on the chemical composition of the pore walls as well as on the interfacial dynamics of the pore fluid. The classical approach for the determination of surface relaxivities is the scaling of NMR relaxation times by surface to volume ratios measured by gas adsorption or mercury intrusion. However, it is preferable that a method for the determination of average pore sizes uses the same substance, water, as probe molecule for both relaxometry and surface to volume measurements. One should also ensure that in both experiments the dynamics of the probe molecule takes place on similar length scales, which are in the order of some microns. Therefore, we employed NMR diffusion measurements with different observation times using bipolar pulsed field gradients and applied them to unconsolidated sediments (two purified sands, two natural sands, and one soil). The evaluation by Mitra's short-time model for diffusion in restricted environments yielded information about the surface to volume ratios which is independent of relaxation mechanisms. We point out that methods based on NMR diffusometry yield pore dimensions and surface relaxivities consistent with a pore space as sampled by native pore fluids via the diffusion process. This opens a way to calibrate NMR relaxation measurements with other NMR techniques, providing information about the pore-size distribution of natural porous media directly from relaxometry.

Previous studies of streamwater transit time distributions (TTD) used isotope tracer information from open precipitation (OP) as inputs to lumped watershed models that simulate the discharge and isotopic composition time-series from convolutions of the effective precipitation, response time distribution, and TTDs. However, in forested catchments passage of rainfall through the forest canopy will alter the tracer signature of throughfall (TF) via interception. Here we test the effect of using TF instead of OP on TTD estimates. We sampled a 0.39 km2 catchment (Wüstebach, Germany) for a 19 month period using weekly precipitation and stream isotope data to evaluate changes in stream isotope simulation and TTDs. We found that TF had different effects on TTDs for δ18O and δ2H, with TF leading to up to four months shorter transit times. TTDs converged for both isotopes only when using TF. TF improved the stream isotope simulations. These results demonstratethe importance of canopy-induced isotope tracer changes in estimating streamwater TTDs in forested catchments.

Radiocesium and radiostrontium are among the most problematic soil contaminants following nuclear fallout dueto their long half-lives and high fission yields. Their chemical resemblance to potassium, ammonium and calciumfacilitates their plant uptake and thus enhances their chance to reach humans through the food-chain dramatically.The plant uptake of both radionuclides is affected by the type of soil, the amount of organic matter and theconcentration of competitive ions.In the present lysimeter scale experiment, soil-plant transfer of Cs-137 and Sr-90 was investigated in anagricultural silty soil amended with digestate, a residue from a biogas plant. The liquid fraction of the digestate,liquor, was used to have higher nutrient competition. Digestate application was done in accordance with thefield practice with an application rate of 34 Mg/ha and mixing it in top 5 cm soil, yielding a final concentrationof 38 g digestate/Kg soil. The top 5 cm soil of the non-amended reference soil was also submitted to the samemixing procedure to account for the physical disturbance of the top soil layer. Six months after the amendmentof the soil, the soil contamination was done with water-soluble chloride salts of both radionuclides, resulting in acontamination density of 66 MBq/m2 for Cs-137 and 18 MBq/m2 for Sr-90 in separate experiments.Our results show that digestate application led to a detectable difference in soil-plant transfer of the investigatedradionuclides, effect was more pronounced for Cs-137. A clear difference was observed in plant uptake ofdifferent plants. Pest plants displayed higher uptake of both radionuclides compared to wheat. Furthermore, loweractivity values were recorded in ears compared to stems for both radionuclides.

Biogas digestates and biochar are emerging soil amendments. Biochar is a byproduct of pyrolysis process which isthermal decomposition of biomass to produce syngas and bio-oil. The use of biochar for soil amendment is beingpromoted for higher crop yields and carbon sequestration. Currently, the numbers of biogas plants in Germany areincreasing to meet the new energy scenarios. The sustainability of biogas industry requires proper disposal optionsfor digestate. Biogas digestates being rich in nutrients are beneficial to enhance agricultural productions. Contraryto the agronomical benefits of these organic amendments, their use can influence the mobility and bioavailabilityof soil contaminants due to nutrients competition and high organic matter content. So far, the impact of suchamendments on highly problematic contaminants like radionuclides is not truly accounted for.In the present study, sorption-desorption behavior of cesium and strontium was investigated in three soilsof different origin and texture. Two agricultural soils, a loamy sand and a silty soil, were amended with biocharand digestate in separate experiments, with field application rates of 25 Mg/ha and 34 Mg/ha, respectively. Forcomparison a third soil, a forest soil, was incubated without any amendment. The amendments were mixed intothe top 20 cm of the field soils, resulting in final concentrations of 8-9 g biochar/Kg soil and 11-12 g digestate/Kgsoil. The soils were incubated for about six months at room temperature. Sorption-desorption experiments wereperformed with CsCl and SrCl2 after pre-equilibrating the soils with CaCl2 solutions.The amendments with field application rates did not have a significant effect on the relevant soil parametersresponsible for the sorption behavior of the two radionuclides. Comparatively, the soil type lead to distinctivedifferences in sorption-desorption dynamics of the two radionuclides. Cesium showed a higher affinity for siltysoil followed by forest soil and lowest for sandy soil. Comparatively, strontium displayed a lower adsorption forall three soils, with a slightly higher adsorption in silty soil and almost similar sorption for both forest and sandysoils.We conclude that the applied organic amendments with field application rates will not deplete the FES(Frayed Edge Sites) responsible for cesium sorption in mineral soils. Furthermore, with the present applicationrates the increase in amount of organic matter is not high enough to significantly affect the strontium sorption inmineral soils. The desorption experiments showed that about 1/3 of the adsorbed cesium was extractable in siltysoil and almost half was extractable in forest and sandy soils. In case of strontium, about half was extractable inthe three soils. Similar to sorption, the effect of amendments was negligible compared to the soil type.

To overcome the problem of on farm point sources of pollution stemming from improper handling, spillages,and leakages of pesticides during filling and cleaning of spraying equipment, environmental friendly and lowcost technology filter systems are currently under development. Based on a laboratory screening approach, wheredifferent biomixtures (soil, with biochar and/or digestate) are tested a full scale outdoor system will be developed.Therefore, different fundamental processes like pesticide mineralization, metabolization, sorption-desorption, andtransport behavior of three radiolabelled pesticides (Bentazone, Boscalid and Pyrimethanil) will be investigated.Biochar and digestate mixtures with two contrasting soils (sandy and silt loam) had been used as a novel biofiltermaterial for respiration study instead of conventional soil and straw mixtures. To analyze the pesticide degradationpotential and to gain information about the temporal evolution of the degradation process of the biochar anddigestate soil mixtures microbial respiration was measured over the course of three month. As expected, digestateacts as an easily available C-source leading to highest release of CO2 compared to other biomixtures used. Incontrast, the addition of even small amounts (1 %) of biochar caused a profound suppression in the CO2 releasefrom digestate based mixtures. The exact driving mechanism for this suppression can be manifold likes negativepriming or chemisorption of CO2 on biochar or NH3 toxicity induced by the large amount of digestate appliedin the experiment (30 %) or can be combination of all effects. Surprisingly, a repeated experiment with same butaged digestate did not show such negative priming.On the other hand, the fate of applied organic contaminants to biomixtures depends on several factors likesoil properties and climatic conditions as well as biological degradation. To analyze the degradation potentialof the different soil/amendment mixtures a degradation study was performed to determine the effects of biocharand digestate in different mixing rates on the metabolization behavior of the studied pesticides, and to identifyand quantify the metabolites derived during the degradation process. The results from the 14C Bentazone studyindicate that 5 % digestate and 5 % biochar mixture showed highest (nearly 15 %) and 1 % biochar lowest rateof mineralization (1 %), whereby highest microbial activity was measured in the soil/digestate mixture.

A major challenge in vadose zone hydrology is to obtain accurate information on thetemporal changes of the vertical soil water distribution and its feedback with theatmosphere and groundwater. A state of the art coupled hydrogeophysical inversion schemeis applied to evaluate soil hydraulic properties of a synthetic model and a field soil insouthern Ontario based on time-lapse monitoring of soil dynamics with surface groundpenetratingradar (GPR). Film flow was included in the hydrological model to account fornoncapillary water flow in a sandy medium during dry conditions. The synthetic studyillustrated that GPR data contain sufficient information to accurately constrain soilhydraulic parameters within a coupled inversion framework and led to an accurateestimation of the soil hydraulic properties. When film flow was not accounted for within theinversion, an equally good fit could still be achieved. In this case, errors introduced byneglecting film flow were compensated by different hydraulic parameters. For the field data,the coupled inversion reduced the overall misfit compared to an uncalibrated model usinghydraulic parameters obtained from laboratory data. Although the data fit improvedsignificantly for water content in the deeper soil layers, accounting for film flow in theuppermost subsurface layer did not lead to a better fit of the GPR data. Further research isneeded to describe the processes controlling water content in the dry range, in particularcoupled heat and vapor transport. This study illustrates the suitability of surface GPRmeasurements combined with coupled inversion for near-surface characterization of soilhydraulic parameters.

Integrated terrestrial system models predict the coupled water, energy and biogeochemical cycles. Simulations with these models are affected by uncertainties of model parameters, initial and boundary conditions, atmospheric forcings and the biophysical processes. Data assimilation (DA) can quantify and reduce the uncertainty. This has been tested intensively for single compartment models, but far less for integrated models with multiple compartments. We constructed a virtual reality (VR) with a coupled land surface-subsurface model under the Terrestrial Systems Modeling Platform, which mimics the Neckar catchment in southern Germany. Soil moisture and groundwater level (GWL) data extracted from the simulated VR are used as measurements to be assimilated with state-only/state-hydraulic parameter estimation. Soil moisture DA improves soil moisture characterization in the vertical profile and the neighboring grid cells, with a 40 ∼ 60% reduction of root mean square error (RMSE) over the observation points. In spite of a small ensemble size of 64 members, assimilating soil moisture data improved saturated hydraulic conductivity estimation around the measurement locations. The characterization of evapotranspiration and river discharge only show limited improvements (1% at observation points and less than 0.1% in RMSE at 3 selected gauge locations respectively). GWL DA not only improves the GWL characterization (76 ∼ 88% RMSE reduction at observation locations) but also soil moisture for some cases. In addition, a clear improvement in GWL characterization is observed up to 8 km from the observations, and updating the model states of the saturated zone only instead of the complete domain gives better performance.

Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled "Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors", is shared via Forschungszentrum Julich: https://doi.org/10.34731/x9s3-kr48 (Bogena and Ney, 2021)., Earth System Science Data, 14 (3), ISSN:1866-3516, ISSN:1866-3508

Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2022; Aachen 1 Online-Ressource : Illustrationen (2022). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2022, High-resolution imaging of the subsurface improves our understanding of the subsurface flow and solute transportation that can directly help us protect groundwater resources and remediate contaminated sites. The ground penetrating radar (GPR) is a useful non/minimal invasive method that consists of a transmitter (Tx) unit that emits electromagnetic (EM) waves and a receiver (Rx) that measures the arriving electromagnetic waves and can provide high-resolution tomograms of the subsurface properties. In specific, the crosshole GPR setup in which two-neighbouring boreholes are placed in the earth can provide much more in-depth access to the target area. However, the interpretation of the GPR data remains challenging. The simpler ray-based inversion (RBI) is computationally attractive while fail to provide high-resolution tomograms as the results always smoothed over the target area. The full-waveform inversion (FWI) can provide detailed subsurface tomograms that can carry up to more than an order of the magnitude resolution compared to RBI from the same data set. A sophisticated method such as FWI requires detailed modelling tools and powerful inversion algorithm that needs significant computational resources. In last decades, by exponential increase in computing power and the memory, alongside to wider usage of high performance computing resources; FWI application in GPR data gain popularity. All these computational advances such as FWI method. could be very demanding to be modelled in 3D domain. Thus, some fundamentals assumptions are made to reduce the computational requirements, especially computational time and required memory by using 2D modeling domain. Despite the usefulness of these simplifications, these assumptions led to introducing inaccuracy that compromises the performance of the FWI in complex structures. We investigated the effect of the assumption that enables us to use a 2D model instead of a computationally expensive 3D modelling to simulate the EM propagation. These assumptions are made for specific state that not necessary is always valid, and therefore it can introduce inaccuracies in transferred data. Study of several synthetic cases revealed that the performance of the 3D to 2D transformation in complex structures such as high contrast layer is much lower than what is anticipated. Therefore, in the complex subsurface system; 2D transferred data inherently carry inaccuracy that jeopardises the accuracy of any further analysis such as FWI. Thus, we introduced a FWI that utilise a native 3D forward model to use the original measured 3D data. The novel method is called 2.5D FWI, and it showed improvements compared to 2D FWI for synthetic and measured data.A better modelling tool such as the 3D forward model provides a useful platform for simulating the subsurface and measuring devices involved to a higher degree of accuracy. We used previously introduced 3D forward model to build a realistic model of the GPR Tx and Rx antenna that called finite-length antennas and the boreholes that these antenna are placed to carry out the measurements. Our studies showed that realistic antenna and borehole-fluid representation provides more realistic travel-time and wave-form shape for GPR data. These more accurate simulated data increases the accuracy of the FWI results as reducing the uncertainty in the inversion system.It is a known issue for GPR community that EM waves that travelled with a high-angle between the Tx and Rx shows inconsistency in their travel-time and therefore could jeopardise travel-time inversion results. Even though this effect is almost consistent, there was no concerts reason for this issue except systematic erroneous measurements. Thus, it is common pre-processing standard to discard these high-angle data (usually above 50°). Our findings regarding the contribution of the borehole-fluid to changes in travel-time of the EM waves showed the high-angle travel-time is not an error rather than consistent effect the borehole-fluid in travel times. We laid the mathematical explanation of this phenomena and introduced a correction method that could predict this issue and compensate for it. Lastly, we applied this correction method on the realistic synthetic data and showed that RBI results improved when the correction method is used., Published by Aachen

In the last decade, time‐domain crosshole ground‐penetrating radar full‐waveform inversion has been applied to several different test sites and has improved the resolution and reconstruction of subsurface properties. The full‐waveform inversion requires several diligent executed pre‐processing steps to guarantee a successful inversion and to minimize the risk of being trapped in a local minimum. Thereby, one important aspect is the starting models of the full‐waveform inversion. Generally, adequate starting models need to fulfil the half‐wavelength criterion, which means that the modelled data based on the starting models need to be within half of the wavelength of the measured data in the entire investigation area. Ray‐based approaches can provide such starting models, but in the presence of high contrast layers, such results do not always fulfil this criterion and need to be improved and updated. Therefore, precise and detailed data processing and a good understanding of experimental ground‐penetrating radar data are necessary to avoid erroneous full‐waveform inversion results. Here, we introduce a new approach, which improves the starting model problem and is able to enhance the reconstruction of the subsurface medium properties. The new approach tames the non‐linearity issue caused by high contrast complex media, by applying bandpass filters with different passband ranges during the inversion to the modelled and measured ground‐penetrating radar data. Thereby, these bandpass filters are considered for a certain number of iterations and are progressively expanded to the selected maximum frequency bandwidth. The resulting permittivity full‐waveform inversion model is applied to update the effective source wavelet and is used as an updated starting model in the full‐waveform inversion with the full bandwidth data. This full‐waveform inversion is able to enhance the reconstruction of the permittivity and electrical conductivity results in contrast to the standard full‐waveform inversion results. The new approach has been applied and tested on two synthetic case studies and an experimental data set. The field data were additionally compared with cone penetration test data for validation.

Coupled numerical models, which simulate water and energy fluxes in the subsurface–land-surface–atmosphere system in a physically consistent way, are a prerequisite for the analysis and a better understanding of heat and matter exchange fluxes at compartmental boundaries and interdependencies of states across these boundaries. Complete state evolutions generated by such models may be regarded as a proxy of the real world, provided they are run at sufficiently high resolution and incorporate the most important processes. Such a simulated reality can be used to test hypotheses on the functioning of the coupled terrestrial system. Coupled simulation systems, however, face severe problems caused by the vastly different scales of the processes acting in and between the compartments of the terrestrial system, which also hinders comprehensive tests of their realism. We used the Terrestrial Systems Modeling Platform (TerrSysMP), which couples the meteorological Consortium for Small-scale Modeling (COSMO) model, the land-surface Community Land Model (CLM), and the subsurface ParFlow model, to generate a simulated catchment for a regional terrestrial system mimicking the Neckar catchment in southwest Germany, the virtual Neckar catchment. Simulations for this catchment are made for the period 2007–2015 and at a spatial resolution of 400 m for the land surface and subsurface and 1.1 km for the atmosphere. Among a discussion of modeling challenges, the model performance is evaluated based on observations covering several variables of the water cycle. We find that the simulated catchment behaves in many aspects quite close to observations of the real Neckar catchment, e.g., concerning atmospheric boundary-layer height, precipitation, and runoff. But also discrepancies become apparent, both in the ability of the model to correctly simulate some processes which still need improvement, such as overland flow, and in the realism of some observation operators like the satellite-based soil moisture sensors. The whole raw dataset is available for interested users. The dataset described here is available via the CERA database (Schalge et al., 2020): https://doi.org/10.26050/WDCC/Neckar_VCS_v1.

Modeling of the land surface water‐, energy‐, and carbon balance provides insight into the behavior of the Earth System, under current and future conditions. Currently, there exists a substantial variability between model outputs, for a range of model types, whereby differences between model input parameters could be an important reason. For large‐scale land surface, hydrological, and crop models, soil hydraulic properties (SHP) are required as inputs, which are estimated from pedotransfer functions (PTFs). To analyze the functional sensitivity of widely used PTFs, the water fluxes for different scenarios using HYDRUS‐1D were simulated and predictions compared. The results showed that using different PTFs causes substantial variability in predicted fluxes. In addition, an in‐depth analysis of the soil SHPs and derived soil characteristics was performed to analyze why the SHPs estimated from the different PTFs cause the model to behave differently. The results obtained provide guidelines for the selection of PTFs in large scale models. The model performance in terms of numerical stability, time‐integrated behavior of cumulative fluxes, as well as instantaneous fluxes was evaluated, in order to compare the suitability of the PTFs. Based on this, the Rosetta, Wösten, and Tóth PTF seem to be the most robust PTFs for the Mualem van Genuchten SHPs and the PTF of Cosby for the Brooks Corey functions. Based on our findings, we strongly recommend to harmonize the PTFs used in model inter‐comparison studies to avoid artifacts originating from the choice of PTF rather from different model structures., Journal of Advances in Modeling Earth Systems, 13 (3), ISSN:1942-2466

Modeling soil hydraulic properties requires an effective representation of capillary and noncapillary storage and conductivity. This is made possible by using physically comprehensive yet flexible soil hydraulic property models. Such a model (Brunswick [BW] model) was introduced by Weber et al. (2019, https://doi.org/10.1029/2018WR024584), and it overcomes some core deficiencies present in the widely used van Genuchten‐Mualem (VGM) model. We first compared the performance of the BW model to that of the VGM model in its ability to describe water retention and hydraulic conductivity data on a set of measurements of 402 soil samples with textures covering the entire range of classes. Second, we developed a simple transfer function to predict BW parameters based on VGM parameters. Combined with our new function, any existing pedotransfer function for the prediction of the VGM parameters can be extended to predict BW model parameters. Based on information criteria, the smaller variance of the residuals, and a 40% reduction in mean absolute error in the hydraulic conductivity over all samples, the BW model clearly outperforms VGM. This is possible as the BW model explicitly accounts for hydraulic properties of dry soils. With the new pedotransfer function developed in this study, better descriptions of water retention and hydraulic conductivities are possible. We are convinced that this will strengthen the utility of the new model and enable improved field‐scale simulations, climate change impact assessments on water, energy and nutrient fluxes, as well as crop productivity in agroecosystems by soil‐crop and land‐surface modeling. The models and the pedotransfer function are included in an R package spsh (https://cran.r‐project.org/package=spsh)., Plain Language Summary: Soil hydraulic property models are mathematical functions, which describe the relationship between the soil water pressure head and the state of soil water saturation, on the one hand, and the soil water pressure head and the unsaturated soil hydraulic conductivity, on the other. These types of mathematical functions are flexible by adjustable parameters. With one set of model equations, the hydraulic properties of soils which may have very different properties due to their vast natural variability can be described. The models treated in this work are (i) the van Genuchten‐Mualem model, a model with well‐known problems, but still frequently applied, and (ii) a relatively new physical comprehensive model, named the Brunswick model. First of all, in a data‐based comparison of model performance, we demonstrate that the Brunswick model has systematic advantages. Second, knowledge about these above‐mentioned parameters can be determined through other mathematical functions, so‐called hydro‐pedotransfer functions, which empirically relate these parameters to observed soil properties. The information about these soil properties can be measured in the laboratory and is also recorded in soil maps. We created a new pedotransfer function to facilitate the prediction of model parameters for the new Brunswick model., Key Points: A pedotransfer function is established to relate van Genuchten‐Mualem (VGM) to Brunswick (BW) soil hydraulic property model parameters. The BW model overcomes the structural deficiencies in VGM and leads to considerably better descriptions of retention and conductivity data. With the new pedotransfer function, soil properties and information in soil maps can be used to predicted BW model parameters., German Research Foundation http://dx.doi.org/10.13039/501100007450, Collaborative Research Center 1253 CAMPOS

Dissertation, RWTH Aachen University, 2020; Jülich : Forschungszentrum Jülich GmbH, Zentralbibliothek, Verlag, Schriften des Forschungszentrums Jülich. Reihe Energie & Umwelt/Energy & environment 512, VIII, 136 Seiten : Illustrationen, Diagramme, Karten (2020). = Dissertation, RWTH Aachen University, 2020, Published by Forschungszentrum Jülich GmbH, Zentralbibliothek, Verlag, Jülich

In recent years, the critical zone (CZ) of catchments across the Mediterranean region has been influenced by rapid changes in both climate seasonality and land use/land cover. Rural ecosystems in southern Europe are experiencing prolonged droughts, seriously compromising water resources availability and crop yields whilst increasing the risk of wildfire occurrence. Rainy seasons are likely to be characterized by intense storms that trigger floods resulting in increasing damage severity. The negative effects of anthropogenic disturbance on hydrological ecosystem services can be tempered by demand-side adaptation options and appropriate investments to ensure water supply under drought conditions. To shed light on some of the scientific challenges related to these issues, a Critical Zone Observatory (CZO) has being established in the Alento River catchment. Although sampling campaigns and monitoring investigations have been carried out in this area for more than twenty-five years, a more systematic research program was recently started to take comprehensive measurements in representative sub-catchments of the study area. These sites are instrumented with advanced ground-based sensor network platforms that provide hydro-meteorological variables and fluxes in the groundwater-soil-vegetation-atmosphere system. Hydrological models of different complexity exploit the gathered dense information to assess the impact of land use and climate changes on key functions and services of the CZO in the Alento River catchment.

To enable precise understanding and prediction of transport in porous media, physical, chemical and biological processes and the interaction between these processes have to be considered. This is an interdisciplinary problem. In the scope of this work the focus is on the physically mmpelling force of the transport, the groundwater flow velocity. A groundwater flow velocimeter (Fig. 1), using the point dilution technique, has been developed to measure in situ the groundwater flow velocity. The resolution of the groundwater flow velocimeter in the vertical direction is 25 cm. The in situ dilution measurement of the tracer uranin is carried out by laser-induced fluorimetry. The calibration of the groundwater flow velocimeter and subsequent field experiments at Krauthausen test site showed that the groundwater flow velocity inside a borehole can be measured with sufficient accuracy. The accuracy in deriving the Darcy velocity from the measurements inside a borehole is strongly dependent on the accuracy in determining the $\alpha$-factor, which corrects for the convergence of streamlines towards the borehole. The estimation of the $\alpha$-factor is difficult due to a general lack of knowledge of the state of the well. Measurements with the groundwater velocimeter showed that, the local Darcy velocity is strongly space and time dependent. For the strongly anisotropic structure of the hydraulic conductivity at the Krauthausen test site, statistics for a three dimensional heterogeneous flow velocity field have been estimated using stochastic theories and Monte Carlo analysis which is based on numerical calculations. It is shown that correlograms in the mean flow direction, estimated by 1st order approximation, are in agreement with the results from the Monte Carlo analysis. The variances for the Darcy velocity components, estimated by 1st order approximation, are clearly below the results of the Monte Carlo estimation. Estimation of the variance, based on 2nd order approximation, showed accordance only for the longitudinal component of the Darcy velocity, whereas the vertical transversal component is below and the horizontal transversal component is above the results from Monte Carlo analysis. The estimated mean Darcy velocity is similar for 1st and 2nd order approximation as well as for the Monte Carlo analysis. Estimation of the Darcy velocity statistics, both from numerical modelling and from stochastic theories, show smaller mean by factor 2, smaller variances by factor 4 and longer correlation length in the horizontal direction by factor 7 than the directly measured Darcy velocity using the groundwater flow velocimeter. The high discrepancies in mean, variance and horizontal autocorrelation length are due to the limited knowledge of the $\alpha$-factor and the time variability of the Darcy velocities. A comparison shows that the relative standard deviation is similar for modelling, 2nd order approximation and direct measurements with the groundwater flow velocimeter.