Hans Kupfersberger

Numerical delineation of transient capture zones

Delineating capture zones plays an important role in the protection of drinking water wells. In the recent literature most of the related work has dealt with the uncertainty of location and extent of the capture zone due to the heterogeneity of the hydrogeologic parameters of the aquifer. This paper is about the impact of considering transient aquifer conditions when computing the capture zone of a well. The presented approach alternates for predefined time steps between the groundwater flow and a particle tracking module enabling the management of a vast number of individual particles. Thus, the development of the capture zone can be monitored more precisely and it can be differentiated between parts of it. Specific results are presented for an aquifer in South-East Austria in terms of the percentage of particles of any starting location that are terminated by a well and of the minimum travel time a particle needs from the same starting location to reach a well. The transient delineated capture zone is compared to those derived from steady state computations for specific groundwater flow conditions. Though the results are site specific the significance of considering the transient system boundary conditions is demonstrated since a superposition of the steady state case results clearly overestimates the area to be protected. Additionally, in order to address sensitivity and computational efficiency the effect of increasing the release interval and the starting pattern of particles on the development of the capture zone is analyzed.

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data

The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulation models provide excellent instruments for researchers to gain more insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessment was conducted by testing six detailed state-of-the-art models for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of the models: 1) a blind test for 2005-2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009-2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement, model efficiency, root relative squared error, Pearsons linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates.

Modeling coupled unsaturated and saturated nitrate distribution of the aquifer Westliches Leibnitzer Feld, Austria

The aquifer Westliches Leibnitzer Feld, Austria, is a significant resource for regional and supraregional drinking water supply for more than 100,000 inhabitants, but the region also provides excellent agricultural conditions. This dual use implicates conflicts (e.g., non-point source groundwater pollution by nitrogen leaching), which have to be harmonized for a sustainable coexistence. At the aquifer scale, numerical models are state-of-the-art tools to simulate the behavior of groundwater quantity and quality and serve as decision support system for implementing groundwater protecting measures. While fully and iteratively coupled simulation models consider feedback between the saturated and unsaturated zone, sandy soil conditions and groundwater depths beneath the root zone allow the use of a unidirectional sequential coupling of the unsaturated water flow and nitrate transport model SIMWASER/STOTRASIM with FEFLOW for the investigation area. Considering separated inputs of water and nitrogen into groundwater out of surface water bodies, agricultural, residential and forested areas, first simulation results match observed groundwater tables, but underestimate nitrate concentrations in general. Thus, multiple scenarios assuming higher nitrogen inputs at the surface are simulated to converge with measured nitrate concentrations. Preliminary results indicate that N-input into the groundwater is strongly dominated by contributions of agricultural land.

Ranking stochastic realizations for improved aquifer response uncertainty assessment

Abstract Incomplete sampling leads to uncertainty in the detailed 3-D distribution of conductivity in every subsurface formation. Stochastic/geostatistical techniques are being increasingly used to generate alternative fine scale 3-D realizations of subsurface parameters that are consistent with the available data. Ideally, an assessment of aquifer response uncertainty is provided by processing a large number of fine scale realizations through a groundwater modeling program. To avoid excessive CPU times the fine scale realizations are often averaged to a coarse resolution for fast flow and transport simulation. The problem with this approach is that the aquifer response is often sensitive to fine scale heterogeneities and such coarse flow models may lead to erroneous results. An alternative approach is proposed in this paper. The coarse scale responses are used to rank the realizations, i.e. identify low and high response realizations. A limited number of fine scale realizations are then processed through the flow and transport simulator. Thus, aquifer response uncertainty can be analyzed at the fine scale with less computational effort. The proposed method is applied to a hypothetical aquifer, which is characterized by variogram statistics derived for the Columbus aquifer, Mississippi. The value of ranking is shown by comparing the approximate uncertainty with the reference fine scale aquifer response.