http://hdl.handle.net/2328/25757 2013-06-19T10:05:55Z 2013-06-19T10:05:55Z Rojas, R Feyen, L Batelaan, Okke Dassargues, Alain http://hdl.handle.net/2328/26370 2013-05-13T02:09:29Z 2010-01-01T00:00:00Z

Title: On the value of conditioning data to reduce conceptual model uncertainty in groundwater modeling Authors: Rojas, R; Feyen, L; Batelaan, Okke; Dassargues, Alain Abstract: Recent applications of multimodel methods have demonstrated their potential in quantifying conceptual model uncertainty in groundwater modeling applications. To date, however, little is known about the value of conditioning to constrain the ensemble of conceptualizations, to differentiate among retained alternative conceptualizations, and to reduce conceptual model uncertainty. We address these questions by conditioning multimodel simulations on measurements of hydraulic conductivity and observations of system‐state variables and evaluating the effects on (1) the posterior multimodel statistics and (2) the contribution of conceptual model uncertainty to the predictive uncertainty. Multimodel aggregation and conditioning is performed by combining the Generalized Likelihood Uncertainty Estimation (GLUE) method and Bayesian Model Averaging (BMA). As an illustrative example we employ a 3‐dimensional hypothetical system under steady state conditions, for which uncertainty about the conceptualization is expressed by an ensemble (M) of seven models with varying complexity. Results show that conditioning on heads allowed for the exclusion of the two simplest models, but that their information content is limited to further differentiate among the retained conceptualizations. Conditioning on increasing numbers of conductivity measurements allowed for a further refinement of the ensemble M and resulted in an increased precision and accuracy of the multimodel predictions. For some groundwater flow components not included as conditioning data, however, the gain in accuracy and precision was partially offset by strongly deviating predictions of a single conceptualization. Identifying the conceptualization producing the most deviating predictions may guide data collection campaigns aimed at acquiring data to further eliminate such conceptualizations. Including groundwater flow and river discharge observations further allowed for a better differentiation among alternative conceptualizations and drastic reductions of the predictive variances. Results strongly advocate the use of observations less commonly available than groundwater heads to reduce conceptual model uncertainty in groundwater modeling.

2010-01-01T00:00:00Z Peeters, Luk Fasbender, Dominique Batelaan, Okke Dassargues, Alain http://hdl.handle.net/2328/26369 2013-05-13T02:09:22Z 2010-01-01T00:00:00Z

Title: Bayesian data fusion for watertable interpolation: incorporating a hydrogeological conceptual model in kriging Authors: Peeters, Luk; Fasbender, Dominique; Batelaan, Okke; Dassargues, Alain Abstract: The creation of a contour map of the water table in an unconfined aquifer based on head measurements is often the first step in any hydrogeological study. Geostatistical interpolation methods (e.g., kriging) may provide exact interpolated groundwater levels at the measurement locations but often fail to represent the hydrogeological flow system. A physically based, numerical groundwater model with spatially variable parameters and inputs is more adequate in representing a flow system. Because of the difficulty in parameterization and solving the inverse problem, however, a considerable difference between calculated and observed heads will often remain. In this study the water‐table interpolation methodology presented by Fasbender et al. (2008), in which the results of a kriging interpolation are combined with information from a drainage network and a digital elevation model (DEM), using the Bayesian data fusion framework, is extended to incorporate information from a tuned analytic element groundwater model. The resulting interpolation is exact at the measurement locations whereas the shape of the head contours is in accordance with the conceptual information incorporated in the groundwater‐flow model. The Bayesian data fusion methodology is applied to a regional, unconfined aquifer in central Belgium. A cross‐validation procedure shows that the predictive capability of the interpolation at unmeasured locations benefits from the Bayesian data fusion of the three data sources (kriging, DEM, and groundwater model), compared to the individual data sources or any combination of two data sources.

2010-01-01T00:00:00Z Ghilain, N Arboleda, A Sepulcre-Canto, G Batelaan, Okke Ardo, J Gellens-Meulenberghs, F http://hdl.handle.net/2328/26368 2013-05-13T02:09:21Z 2012-01-01T00:00:00Z

Title: Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite Authors: Ghilain, N; Arboleda, A; Sepulcre-Canto, G; Batelaan, Okke; Ardo, J; Gellens-Meulenberghs, F Abstract: Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG) and distributed by the Satellite Application Facility on Land Surface Analysis (LSA-SAF) are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I), showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual) variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI) and Fractional Vegetation Cover (FVC) products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSASAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model HTESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land surface temperature shows an improvement of the evapotranspiration simulations.

2012-01-01T00:00:00Z Possemiers, Mathias Huysmans, Marijke Peeters, Luk Batelaan, Okke Dassargues, Alain http://hdl.handle.net/2328/26367 2013-05-13T02:09:30Z 2012-01-01T00:00:00Z

Title: Relationship between sedimentary features and permeability at different scales in the Brussels Sands Authors: Possemiers, Mathias; Huysmans, Marijke; Peeters, Luk; Batelaan, Okke; Dassargues, Alain Abstract: The Brussels Sands display a complex three-dimensional subsurface architecture. This sedimentological heterogeneity induces a highly heterogeneous spatial distribution of hydrogeological parameters at different scales and may consequently influence subsurface fluid flow and solute migration. This study aims at characterizing spatial variability of permeability at different scales in the Brussels Sands. Firstly, a literature review on the permeability distribution of the Brussels Sands was performed. Secondly, a field campaign was carried out consisting of field observations of the small-scale sedimentary structures and in situ measurements of air permeability. A total of 6550 cm-scale air permeability measurements were carried out in situ in three Brussels Sands quarries in the central part of Belgium: Bierbeek, Mont‑Saint‑Guibert and Chaumont‑Gistoux. On the large basin scale, substantial differences in permeability are observed. A literature data analysis shows that there is no clear correlation between hydraulic conductivity and sedimentary facies. At the small scale, results show that permeability heterogeneity and anisotropy are strongly influenced by sedimentary heterogeneity in all three quarries. Clay-rich sedimentary features such as bottomsets and distinct mud drapes exhibit a different statistical and geostatistical permeability distribution compared to the cross-bedded lithofacies, where the permeability anisotropy is dominated by the foreset lamination orientation.

2012-01-01T00:00:00Z