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Abstract: Atrazine was banned in Germany in 1991 due to findings of atrazine concentrations in ground- and drinking waters exceeding threshold values. Monitoring of atrazine concentrations in the groundwater since then provides information about the resilience of the groundwater quality to changing agricultural practices. In this study, we present results of a monitoring campaign of atrazine concentrations in the Zwischenscholle aquifer. This phreatic aquifer is exposed to intensive agricultural land use and susceptible to contaminants due to a shallow water table. In total 60 observation wells (OWs) have been monitored since 1991, of which 15 are sampled monthly today. Descriptive statistics of monitoring data were derived using the “regression on order statistics” (ROS) data censoring approach, estimating values for nondetects. The monitoring data shows that even 20 years after the ban of atrazine, the groundwater concentrations of sampled OWs remain on a level close to the threshold value of 0.1 μg l−1 without any considerable decrease. The spatial distribution of atrazine concentrations is highly heterogeneous with OWs exhibiting permanently concentrations above the regulatory threshold on the one hand and OWs were concentrations are mostly below the limit of quantification (LOQ) on the other hand. A deethylatrazine-to-atrazine ratio (DAR) was used to distinguish between diffuse – and point-source contamination, with a global mean value of 0.84 indicating mainly diffuse contamination. Principle Component Analysis (PCA) of the monitoring dataset demonstrated relationships between the metabolite desisopropylatrazine, which was found to be exclusively associated with the parent compound simazine but not with atrazine, and between deethylatrazine, atrazine, nitrate, and the specific electrical conductivity. These parameters indicate agricultural impacts on groundwater quality. The findings presented in this study point at the difficulty to estimate mean concentrations of contamination for entire aquifers and to evaluate groundwater quality based on average parameters. However, analytical data of monthly sampled single observation wells provide adequate information to characterize local contamination and evolutionary trends of pollutant concentration. [Copyright &y& Elsevier]

Abstract: Water infiltration into heterogeneous, structured soil leads to hydraulic non-equilibrium across the infiltration front. That is, the water content and pressure head are not in equilibrium according to some static water retention curve. The water content increases more rapidly in more conductive regions followed by a slow relaxation towards an equilibrium state behind the front. An extreme case is preferential infiltration into macropores. Since flow paths adapt to the structural heterogeneity of the porous medium, there is a direct link between structure and non-equilibrium. The aim of our study is to develop an upscaled description of water dynamics which conserves the macroscopic effects of non-equilibrium and which can be directly linked to structural properties of the material. A critical question is how to define averaged state variables at the larger scale. We propose a novel approach based on flux-weighted averaging of pressure head, and compare its performance to alternative methods for averaging. Further, we suggest some meaningful indicators of hydraulic non-equilibrium that can be related to morphological characteristics of infiltration fronts in quantitative terms. These methods provide a sound basis to assess the impact of structural connectivity on hydraulic non-equilibrium. We demonstrate our approach using numerical case studies for infiltration into two-dimensional heterogeneous media using three different structure models with distinct differences in connectivity. Our results indicate that an increased isotropic, short-range connectivity reduces non-equilibrium, whereas anisotropic structures that are elongated in the direction of flow enforce it. We observe a good agreement between front morphology and effective hydraulic non-equilibrium. A detailed comparison of averaged state variables with results from an upscaled model that includes hydraulic non-equilibrium outlines potential improvements in the description of non-equilibrium dynamics including preferential flow in simplified, upscaled models based on Richards equation. [Copyright &y& Elsevier]

In this manuscript, we propose a new method to calculate water flow and xylem water potential distribution in hydraulic architectures (such as root systems) of any complexity. It is based on the extension of the water flow equation analytical resolution of Landsberg and Fowkes for single roots. It consists in splitting the root systems in zones of homogeneous or homogeneously changing properties and deriving the xylem potential and water flow under any given boundary conditions (plant transpiration or collar potential, and potential at soil-root interfaces) without assuming a uniform xylem potential within each zone. The method combines analytical solutions of water flow within the segmented zones with the numerical solution of flow connectivity for the whole root system. We demonstrate that the proposed solution is the asymptote of the exclusively numerical solution for infinitesimal root segment lengths (and infinite segment number). As water uptake locations and magnitudes predicted by the latter solution for finite segmentation lengths deviate from the exact solution, and are computationally more intensive, we conclude that the new methodology should always be privileged for future applications. The proposed solution can be easily coupled to soil modules (as already done with existing solutions) and further implemented in functional-structural plant models to predict water flow in the soil-plant atmosphere continuum with a better accuracy than current models. Finally the new solution may be used to calculate more accurately plant scale macroscopic parameters for crop models. [ABSTRACT FROM AUTHOR]

Bare soils are natural porous media where moisture and transport properties may change considerably. Under very dry conditions, it is predicted that capillary continuity from deeper soil layers to the surface ceases and evaporation decreases drastically because it is only sustained by vapor transport through an increasing dry surface layer (stage II). In this study, we firstly confirm this effect by investigating the drying of a lab-scale sand column using various MRI sequences as well as a unilateral NMR sensor (NMR-MOUSE). Proofing the convenience of the unilateral sensor, we take a step forward by monitoring moisture development of a natural soil under controlled ambient conditions. Finally, the experimental results clearly validate the prediction of a coupled water, vapor and heat flow model regarding the onset of stage II evaporation and the subsequent receding secondary evaporation front. [ABSTRACT FROM AUTHOR]

Abstract: In arable farming systems, the term ‘subsoil’ refers to the soil beneath the tilled or formerly tilled soil horizon whereas the latter one is denoted as ‘topsoil’. To date, most agronomic and plant nutrition studies have widely neglected subsoil processes involved in nutrient acquisition by crop roots. Based on our current knowledge it can be assumed that subsoil properties such as comparatively high bulk density, low air permeability, and poverty of organic matter, nutrients and microbial biomass are obviously adverse for nutrient acquisition, and sometimes subsoils provide as little as less than 10% of annual nutrient uptake in fertilised arable fields. Nevertheless, there is also strong evidence indicating that subsoil can contribute to more than two-thirds of the plant nutrition of N, P and K, especially when the topsoil is dry or nutrient-depleted. Based on the existing literature, nutrient acquisition from arable subsoils may be conceptualised into three major process components: (I) mobilisation from the subsoil, (II) translocation to the shoot and long-term accumulation in the Ap horizon and (III) re-allocation to the subsoil. The quantitative estimation of nutrient acquisition from the subsoil requires the linking of field experiments with mathematical modelling approaches on different spatial scales including Process Based Models for the field scale and Functional–Structural Plant Models for the plant scale. Possibilities to modify subsoil properties by means of agronomic management are limited, but ‘subsoiling’ – i.e. deep mechanical loosening – as well as the promotion of biopore formation are two potential strategies for increasing access to subsoil resources for crop roots in arable soils. The quantitative role of biopores in the nutrient acquisition from the subsoil is still unclear, and more research is needed to determine the bioaccessibility of nutrients in subsoil horizons. [Copyright &y& Elsevier]

• Successful prediction of weathering indices with MIR spectroscopy. • Land use explains minor part of variations in soil thickness and weathering degree. • Soil thickness and weathering degree mainly determined by slope gradient. • Locally high erosion does not necessarily result in changes at landscape-scale. Land use and land cover changes (LUCC) can drastically alter various components of the critical zone, including soil thickness and soil chemical weathering processes. Often these studies, however, tend to focus on extreme cases, not representing what actually happens on average at larger, regional scales. Here, we evaluate the impact of LUCC on soil thickness and soil weathering degree at the regional scale, where we use soil spectroscopy to derive weathering indices. In a subtropical region in Southern Brazil, we collected calibration/validation soil samples (n = 49) from 4 different locations for which we measured the mid-infrared (MIR) spectral reflectance and 3 soil chemical weathering indices: chemical index of alteration (CIA), the total reserve in bases (TRB), and the iron ratio (Fe d /Fe t). We used partial least square regressions on this calibration/validation dataset to relate the MIR spectra of the soil samples to these weathering indices, resulting in good calibration relationships with R2 values of 0.97, 0.91 and 0.84 for CIA, TRB and Fe d /Fe t , respectively. Applying these relations to MIR spectra of regionally collected soil samples allowed us to calculate soil weathering degrees for a large number of soil samples (n = 229), without requiring costly and time-consuming chemical analyses. We collected these soil samples at 100 mid-slope positions: 50 under forest and 50 under agricultural land use. Land use explained only a minor part of the variation in soil thickness and weathering degree. Thus, while local water and tillage erosion rates might be considerable after deforestation, this has not led to significant reductions in average soil thickness and has not affected soil weathering degree. Slope gradient is the main factor influencing the spatial variability in soil thickness and weathering degree on mid-slope sections in our study area. Human activities over the last century did not fundamentally alter these patterns. [ABSTRACT FROM AUTHOR]

In this paper, we present a class of preconditioning methods for a parallel solution of the three-dimensional Richards equation. The preconditioning methods Jacobi scaling, block-Jacobi, incomplete lower–upper, incomplete Cholesky and algebraic multigrid were applied in combination with a parallel conjugate gradient solver and tested for robustness and convergence using two model scenarios. The first scenario was an infiltration into initially dry, sandy soil discretised in 500,000 nodes. The second scenario comprised spatially distributed soil properties using 275,706 numerical nodes and atmospheric boundary conditions. Computational results showed a high efficiency of the nonlinear parallel solution procedure for both scenarios using up to 64 processors. Using 32 processors for the first scenario reduced the wall clock time to slightly more than 1% of the single processor run. For scenario 2 the use of 64 processors reduces the wall clock time to slightly more than 20% of the 8 processors wall clock time. The difference in the efficiency of the various preconditioning methods is moderate but not negligible. The use of the multigrid preconditioning algorithm is recommended, since on average it performed best for both scenarios. [Copyright &y& Elsevier]