Influence of temporally variable groundwater flow conditions on point measurements and contaminant mass flux estimations

Monitoring of contaminant concentrations, e.g., for the estimation of mass discharge or contaminant degradation rates, often is based on point measurements at observation wells. In addition to the problem, that point measurements may not be spatially representative, a further complication may arise due to the temporal dynamics of groundwater flow, which may cause a concentration measurement to be not temporally representative. This paper presents results from a numerical modeling study focusing on temporal variations of the groundwater flow direction. “Measurements” are obtained from point information representing observation wells installed along control planes using different well frequencies and configurations. Results of the scenario simulations show that temporally variable flow conditions can lead to significant temporal fluctuations of the concentration and thus are a substantial source of uncertainty for point measurements. Temporal variation of point concentration measurements may be as high as the average concentration determined, especially near the plume fringe, even when assuming a homogeneous distribution of the hydraulic conductivity. If a heterogeneous hydraulic conductivity field is present, the concentration variability due to a fluctuating groundwater flow direction varies significantly within the control plane and between the different realizations. Determination of contaminant mass fluxes is also influenced by the temporal variability of the concentration measurement, especially for large spacings of the observation wells. Passive dosimeter sampling is found to be appropriate for evaluating the stationarity of contaminant plumes as well as for estimating average concentrations over time when the plume has fully developed. Representative sampling has to be performed over several periods of groundwater flow fluctuation. For the determination of mass fluxes at heterogeneous sites, however, local fluxes, which may vary considerably along a control plane, have to be accounted for. Here, dosimeter sampling in combination with time integrated local water flux measurements can improve mass flux estimates under dynamic flow conditions.     

Assessing the long-term supply risks for mineral raw materials—a combined evaluation of past and future trends

This paper develops a method for identifying and assessing long-term supply risks for mineral raw materials. The method is based on a combined evaluation of past and future supply and demand trends. By analysing raw material boom and bust cycles over the past 50 years, we have quantified indicators and defined benchmarks for identifying critical market situations. By applying the method, risks for supply shortage may be identified at an early stage. In addition, a numerical evaluation model has been developed for better comparison between various mineral raw materials. Compared to other assessment methods this method uses specific benchmarks for each raw material to better assess supply risks. The method is embedded within a systematic and comprehensive analytical approach.     

Modeling potential herbicide loss to surface waters on the Swiss plateau

Lack of sufficiently detailed data often limits the applicability of complex transport-reaction models for estimating potential herbicide loss to surface waters. Therefore, there is also a need for simple models that are easy to apply but still capture the main features of the underlying processes.In this study, a simple regression model was developed to assess the vulnerability of catchments in the Swiss Plateau to diffuse herbicide loss to surface waters. The model is designed as a screening tool to rank the catchments in a relative sense and not to calculate Predicted Environmental Concentrations (PEC) of pesticides. The main goal is to capture two dominating factors controlling diffuse herbicide transport into streams and rivers. These factors are herbicide application and fast flow processes that are mainly responsible for herbicide transport. In a first step vulnerability of sites to herbicide loss is estimated based on site-specific conditions irrespective of actual herbicide application. In the second step, this vulnerability assessment is combined with actual herbicide application data to estimate the potential herbicide loss.The fast flow index (FFI), derived from discharge data using a base flow separation method, was applied as a proxy for the amount of fast flow occurring. The influence of catchment attributes (including topographic, climatic and soil data) on the FFI was analyzed using a multiple regression approach based on data from 57 catchments of the Swiss Plateau. By combining regression analysis with mechanistic knowledge, a two factor non-linear model based on river density and soil permeability as dominant input factors was selected as the best model for FFI prediction given the available data. Higher dimensional models had to be excluded because the strong correlation between the potential input factors led to unrealistic dependences while only minimally improving the quality of the fit.The spatial pattern of the predicted FFI as a measure for the vulnerability to diffuse herbicide losses shows a clearly increasing trend from the western to the eastern part of the Swiss Plateau and towards the pre-alpine/alpine regions in the south.In general the pattern of herbicide use corresponds to site conditions typical of a low FFI. However, the spatial analysis revealed exceptions, namely areas in which high actual herbicide use coincides with a high FFI.Despite the uncertainties in the model, this simple approach seems to be useful for supporting site-adapted agricultural practice whenever the higher accuracy of more detailed models is not required or too expensive to achieve. In addition, in combination with data on actual herbicide application, it can support the design of monitoring strategies by identifying critical areas of actual herbicide loss.     

From land cover change to land function dynamics: a major challenge to improve land characterization

Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and linkages between these. Consideration of land functions that provide a wide range of goods and services makes more integrated assessments of land change possible. The increasing attention to multifunctional land use is another incentive to develop methods to assess changes in land functions. A number of methods to quantify and map the spatial extent of land use and land functions are discussed and the implications for modeling are identified based on recent model approaches in land change science. The mixed use of land cover, land use and land function in maps and models leads to inconsistencies in land change assessments. Explicit attention to the non-linear relations between land cover, land use and land function is essential to consistently address land change. New methods to map and quantify land function dynamics will enhance our ability to understand and model land system change and adequately inform policies and planning.     

Field Evaluation of DRAINMOD 5.1 Under a Cold Climate: Simulation of Daily Midspan Water Table Depths and Drain Outflows1

Abstract: The hydrologic performance of DRAINMOD 5.1 was assessed for the southern Quebec region considering freezing/thawing conditions. A tile drained agricultural field in the Pike River watershed was instrumented to measure tile drainage volumes. The model was calibrated using water table depth and subsurface flow data over a two‐year period, while another two‐year dataset served to validate the model. DRAINMOD 5.1 accurately simulated the timing and magnitude of subsurface drainage events. The model also simulated the pattern of water table fluctuations with a good degree of accuracy. The R² between the observed and simulated daily WTD for calibration was >0.78, and that for validation was 0.93. The corresponding coefficients of efficiency (E) were >0.74 and 0.31. The R² and E values for calibration/validation of subsurface flow were 0.73/0.48 and 0.72/0.40, respectively. DRAINMOD simulated monthly subsurface flow quite accurately (E > 0.82 and R² > 0.84). The model precisely simulated daily/monthly drain flow over the entire year, including the winter months. Thus DRAINMOD 5.1 performed well in simulating the hydrology of a cold region.     

Model-based prediction of long-term leaching of contaminants from secondary materials in road constructions and noise protection dams

In this study, contaminant leaching from three different secondary materials (demolition waste, municipal solid waste incineration ash, and blast furnace slag) to groundwater is assessed by numerical modeling. Reactive transport simulations for a noise protection dam and a road dam (a typical German autobahn), in which secondary materials are reused as base layers, were performed to predict the breakthrough of a conservative tracer (i.e., a salt) and sorbing contaminants (e.g., PAHs like naphthalene and phenanthrene or heavy metals) at the groundwater table. The dam constructions have a composite architecture with soil covers in inclined layers and distinct contrasts in the unsaturated hydraulic properties of the used materials. Capillary barrier effects result in strong spatial variabilities of flow and transport velocities. Contaminant breakthrough curves at the groundwater table show significant tailing due to slow sorption kinetics and a wide distribution of travel times. While conservative tracer breakthrough depends primarily on subsoil hydraulic properties, equilibrium distribution coefficients and sorption kinetics represent additional controlling factors for contaminant spreading. Hence, the three secondary materials show pronounced differences in the temporal development of leached contaminant concentrations with consequences for breakthrough times and peak concentrations at the groundwater table. Significant concentration reductions due to dispersion occur only if the source concentrations decrease significantly prior to the arrival of the contaminant at the groundwater table. Biodegradation causes significant reduction of breakthrough concentrations only if flow velocities are low.     

Compatible Blends of Zein and Polyvinylpyrrolidone

Blends of zein and polyvinylpyrrolidone (PVP) were compared based on their tensile properties, thermal properties and morphology. Zein was blended with polyvinylpyrrolidone of varying molecular weights (10, 55, and 1,300 kDa) and films were cast from ethanol solutions. Films cast using the higher molecular weight polymers showed an improvement in tensile strength, up to a 24% increase, compared to control. Differential scanning calorimetry data for the blends showed single T_m and T_g values of an intermediate value between those of zein and PVP control samples. Field emission scanning electron microscopy images show no obvious inhomogeneities, and confocal fluorescence microscopy showed no decreased uniformity in the PVP/zein films compared to control. Electrospun fibers of the zein/PVP blends were also obtained. These findings suggest that zein and polyvinylpyrrolidone combine to form a compatible blend, the first such blend of zein with a synthetic polymer.     

Implications of turnover and trust for safety attitudes and behaviour in work teams

Turnover potentially leads to a new individual being selected into a work team. This study investigated the safety-specific trust which team members place in their organisation’s selection and induction processes, and related this to the perceived risk from new employees. The research was conducted with teams working in forest harvesting, an occupation which has high-turnover, high risk and a high accident rate. Results indicate that trust in induction processes was negatively correlated with perceived risk from a new employee. Team members also engaged in a number of safety ensuring behaviours when a new individual joined the team, and these were related to the level of perceived risk, and how much they cared about their team members’ safety. It is argued that trust in the safety-specific characteristics of an organisation’s selection and induction process may have negative consequences for safety.     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.