Sjoerd E. A. T. M. van der Zee

Effects of Soil Heterogeneity on Pesticide Leaching to Groundwater

Pesticide leaching was simulated numerically assuming Freundlich adsorption, first-order transformation and passive plant uptake, taking transient flow, hydrodynamic dispersion, and depth as well as temperature dependence of (bio)chemical parameters into account. The dependency of the leached fraction on sorption and transformation parameters appeared to be in good general agreement with the model developed by Jury et al. (1987). We incorporated spatial variability of )bio)chemical parameters into the piston flow model and showed how spatial variability may be accounted for without having to resort to demanding Monte Carlo techniques. Such spatial variability affects the leached fraction significantly. The data requirement of the simple stochastic model is small and the versatility relatively high. For parameter values often not of prime practical interest for pesticide screening this model fails. Considering transport by convection and dispersion in the semi-infinite domain, this spatial variability can be easily accounted for using parameter ranges for which our original analytical model for spatially variable piston transport failed. In this revised model, hydrodynamic dispersion, preferential flow, and spatial variability of transformation, sorption and soil thickness are dealt with in a similar fashion, while both correlation or the absence of correlation of parameters can be incorporated through an approximation of apparent residence time variance.

Transport of reacting solute in a one‐dimensional, chemically heterogeneous porous medium

Reacting, nonlinearly adsorbing solute transport in chemically heterogeneous soils is studied. Assuming adsorption is adequately described with the Freundlich equation, random variation of the adsorption coefficient is assumed to describe the heterogeneity. In a homogeneous case, traveling wave fronts develop, characterized by a constant velocity and a constant front shape. Using the method of moments, an analytical expression is derived to describe the constant variance of the traveling wave front. Deviations from the analytical variance and velocity, both calculated with an average adsorption coefficient, show that column scale heterogeneity has significant effects on front spreading and front movement. Expected values of front velocity and variance are computed as averages of values of 600 randomly generated columns. The nonlinear process causes small deviations from the case with average parameters. The ensemble average concentration front, representing an average front for the flow domain, shows that three mechanisms are responsible for the front spreading. At early displacement times the front spreading is caused by the thickness of the individual traveling waves. Subsequently, the effect of the internal variation of the adsorption coefficient (column scale heterogeneity) increases, whereas at large displacement times the front spreading is dominated by the different retardation coefficients of the different columns. The latter effect causes the variance to increase in proportion to t2. An analytical approximation is derived for the ensemble average front, ignoring column scale heterogeneity.

Conceptual approach to estimating the effect of home-range size on the exposure of organisms to spatially variable soil contamination

Abstract Spatial variability of soil properties leads to uncertainties in the ecotoxicological risk assessment of polluted soil in situ. Mobility of organisms causes that they are not exposed chronically to pollutants in soil, which is in contrast with laboratory experiments. Moreover, only a fraction of the total amount of contaminants is available for organisms. Developing a conceptual model, we identify the information that is required for an ecotoxicologically based risk assessment. Field data of Cd-polluted soil are used in a Monte Carlo simulation for the illustration of the concept. The data are analysed geostatistically and predictions at unsampled locations are made using Ordinary Block Kriging. The accumulation of the pollutant in fictitious organisms is estimated with the one-compartment toxicokinetic model. Both the home-range size of the organism and the spatial pattern of cadmium content affect the extent of the area where exposure to the pollution leads to exceeding of a specific Cd concentration in the organisms. On average, larger home-range sizes lead to lower Cd concentrations in organisms. However, larger home-range sizes lead to an increase of the probability that a specific exposure level is exceeded. Research in uptake-and assimilation coefficients, excretion activities, and the behaviour of organisms in a polluted area is needed.

Stochastic analysis of nonlinear biodegradation in regimes controlled by both chromatographic and dispersive mixing

Nonlinear biodegradation in natural porous media is affected by the heterogeneity of the formation and dispersive mixing processes. We analyze these coupled effects by combining recent advances in analytical one-dimensional modeling of bioreactive transport with stochastic concepts of dispersive mixing in heterogeneous domains. Specifically, we model bioremediation of a sorbing contaminant undergoing nonlinear biodegradation in heterogeneous aquifers applying the stochastic-convective and the advective-dispersive stream tube approaches, in which we use a semianalytical traveling wave solution for one-dimensional reactive transport. The results of numerical simulations agree excellently with both models, which establishes that the traveling wave solution is an efficient and accurate way to evaluate the development of intrastream tube concentration distributions and that the advective-dispersive stream tube approach is suitable to describe nonlinear bioreactive transport in systems controlled by local-scale dispersion. In contrast with conservative transport the mean contaminant flux is shown to be significantly influenced by transverse dispersion, even for realistic Peclet values. Furthermore, asymptotic front shapes are shown to be neither Fickian nor constant (traveling wave behavior), which raises questions about the current practice of upscaling bioreactive transport. The error caused by neglecting local dispersion was found to increase with time and to remain significant even for large retardation differences between electron acceptor and contaminant. This implies that, even if reaction rates are dominated by chromatographic mixing, the dispersive mixing process cannot be disregarded when predicting bioreactive transport.

Pesticide biotransformation in surface waters: multivariate analyses of environmental factors at field sites.

Abstract Transformation rates of four widely used pesticides were determined in surface waters that were characterised on the basis of hydrological status and physico-chemical, biochemical and chemical composition. Large variations in transformation rates were observed, ranging from 0.004 to 0.01 day −1 (half-life = 70–173 days) for aldicarb, 0.005 to 0.57 day −1 (half-life = 1–139 days) for simazine, 0.002 to 0.43 day −1 for MCPA (half-life = 2–347 days) and 0.0005 to 0.24 day −1 (half-life = 3–1400 days) for mecoprop. Principal component analyses and step-wise multiple regression analyses were carried out, combining field data and laboratory observations, to reveal the discriminating environmental variables that determine the transformation rates of aldicarb, simazine, MCPA and mecoprop in various aqueous systems. A large set of environmental variables (286 observations) was reduced to three underlying components, explaining 84% of the total variance in the data set. The first component contains variables that promote biorespiratory processes, in which a relationship appears between sorption potential, N sources and microbial activity. The second component is the macro/miconutrient group. The third component is the phosphorus group. Rapid transformation of these pesticides generally occurs in small hydrological systems such as field ditches and channels. Large water bodies such as main discharge channels or lakes seem to enhance the persistence of all four pesticides. Besides the hydrological status of the water course, historical application of the pesticide and subsequent adaptation of biorespiratory processes appear to be the most discriminating environmental factors that determine transformation rates of the pesticides studied.

Some physicochemical and environmental factors affecting transformation rates and sorption of the herbicide metamitron in soil

In addition to the molecular structure of a pesticide, environmental conditions may influence its persistence through their effect on the growth and activity of pesticide-degrading micro-organisms. As a result, transformation rates may decrease rapidly when a compound is leached into subsoil. Metamitron sorption isotherms were determined and incubation series were set up for a sandy loam soil, simulating single and combination effects that occur during transport of metamitron into subsoils. K OC values increased with increasing depth from 185 to 700 litre kg -1 . A combination of conditions that are unfavourable for microbial activity, such as low temperature (5°C), low concentrations (0.5 mg kg -1 ) and a large sorbed fraction (K OC = 700) resulted in half-lives of over one year. Oxygen inhibition decreased the transformation rate of metamitron from 0.058 to 0.019 day -1 . In order of significance, the transformation of metamitron appears to be a function of temperature, oxygen availability and sorption to organic carbon. Increasing doses did not change transformation rates significantly, although different transformation pathways were observed.

Can frequent precipitation moderate the impact of drought on peatmoss carbon uptake in northern peatlands

Northern peatlands represent a large global carbon store that can potentially be destabilized by summer water table drawdown. Precipitation can moderate the negative impacts of water table drawdown by rewetting peatmoss (Sphagnum spp.), the ecosystems key species. Yet, the frequency of such rewetting required for it to be effective remains unknown. We experimentally assessed the importance of precipitation frequency for Sphagnum water supply and carbon uptake during a stepwise decrease in water tables in a growth chamber. CO2 exchange and the water balance were measured for intact cores of three peatmoss species (Sphagnum majus, Sphagnum balticum and Sphagnum fuscum) representative of three hydrologically distinct peatland microhabitats (hollow, lawn and hummock) and expected to differ in their water table-precipitation relationships. Precipitation contributed significantly to peatmoss water supply when the water table was deep, demonstrating the importance of precipitation during drought. The ability to exploit transient resources was species-specific; S. fuscum carbon uptake increased linearly with precipitation frequency for deep water tables, whereas carbon uptake by S. balticum and S. majus was depressed at intermediate precipitation frequencies. Our results highlight an important role for precipitation in carbon uptake by peatmosses. Yet, the potential to moderate the impact of drought is species-specific and dependent on the temporal distribution of precipitation.

Measurement network design including traveltime determinations to minimize model prediction uncertainty

Traveltime determinations have found increasing application in the characterization of groundwater systems. No algorithms are available, however, to optimally design sampling strategies including this information type. We propose a first-order methodology to include groundwater age or tracer arrival time determinations in measurement network design and apply the methodology in an illustrative example in which the network design is directed at contaminant breakthrough uncertainty minimization. We calculate linearized covariances between potential measurements and the goal variables of which we want to reduce the uncertainty: the groundwater age at the control plane and the breakthrough locations of the contaminant. We assume the traveltime to be lognormally distributed and therefore logtransform the age determinations in compliance with the adopted Bayesian framework. Accordingly, we derive expressions for the linearized covariances between the transformed age determinations and the parameters and states. In our synthetic numerical example, the derived expressions are shown to provide good first-order predictions of the variance of the natural logarithm of groundwater age if the variance of the natural logarithm of the conductivity is less than 3.0. The calculated covariances can be used to predict the posterior breakthrough variance belonging to a candidate network before samples are taken. A Genetic Algorithm is used to efficiently search, among all candidate networks, for a near-optimal one. We show that, in our numerical example, an age estimation network outperforms (in terms of breakthrough uncertainty reduction) equally sized head measurement networks and conductivity measurement networks even if the age estimations are highly uncertain. Copyright 2008 by the American Geophysical Union.

How Does Tree Density Affect Water Loss of Peatlands? A Mesocosm Experiment

Raised bogs have accumulated more atmospheric carbon than any other terrestrial ecosystem on Earth. Climate-induced expansion of trees and shrubs may turn these ecosystems from net carbon sinks into sources when associated with reduced water tables. Increasing water loss through tree evapotranspiration could potentially deepen water tables, thus stimulating peat decomposition and carbon release. Bridging the gap between modelling and field studies, we conducted a three-year mesocosm experiment subjecting natural bog vegetation to three birch tree densities, and studied the changes in subsurface temperature, water balance components, leaf area index and vegetation composition. We found the deepest water table in mesocosms with low tree density. Mesocosms with high tree density remained wettest (i.e. highest water tables) whereas the control treatment without trees had intermediate water tables. These differences are attributed mostly to differences in evapotranspiration. Although our mesocosm results cannot be directly scaled up to ecosystem level, the systematic effect of tree density suggests that as bogs become colonized by trees, the effect of trees on ecosystem water loss changes with time, with tree transpiration effects of drying becoming increasingly offset by shading effects during the later phases of tree encroachment. These density-dependent effects of trees on water loss have important implications for the structure and functioning of peatbogs.

New approaches for low-invasive contaminated site characterization, monitoring and modelling

Previously, conventional techniques for characterizing contaminated sites were often applied with limited strategic planning, resulting in time-consuming and costintensive investigation campaigns, which did not effectively support decision-making. The need for remediation, and the optimal way of doing so in terms of environmental beneficial effect and cost effectiveness, involves problem owners, the authorities, and consultants. Each of these stakeholders has to deal with lack of knowledge and broad-bands of uncertainty regarding subsurface contaminant distribution and processes. The primary cause is the spatiotemporal variability both of the subsurface, its structure and processes such as flow, transport, and biodegradation, and the pollution event. This variability leads to highly erratic patterns of contaminant concentrations, which cannot be captured experimentally with conventional techniques that provide point measurements. An obvious solution to deal with the ‘invisible subsoil’ is to develop new ways of monitoring. The need for this innovation was identified by the US EPA and by the European Commission, to be based on step-by-step site characterization strategies, allowing for smart feedback loops (Fig. 1). The identified needs were laid down in a call in the FP 7 program which then acted as the starting point for the overall project approaches. The research presented in this special issue is centred around two European Commission 7 Framework program projects: ‘ModelPROBE Model-driven Soil Probing, Site Assessment and Evaluation’ (Grant agreement No. 213161; www.modelprobe.eu ) and to a much higher extent, ‘SoilCAM – Soil Contamination: Advanced Integrated Characterisation and Time Lapse Monitoring’ (Grant agreement No. 212663; www.soilcam.eu ). The research activities were dedicated to both the primary development of emerging methods and, equally important, the improvement and combination of previously developed methods, interdisciplinary efforts for the investigation, and assessment of contaminated sites. Negotiations with the European Commission started in 2008, and led to the establishment of collaboration links between the two projects selected in the competitive call for proposals within Soil Technology topic, in order to make use of the possibly synergistic approaches and to ensure the transfer of knowledge between the projects. The overlap of personnel within the partners of both consortia facilitated the collaboration. The cluster of Soil Technology Research, which is a coalition of research projects funded by the European Commission, Responsible editor: Philippe Garrigues