Vignette d'image

Brunner, Philip

Nom
Brunner, Philip
Affiliation principale
Fonction
Professeur ordinaire
Email
philip.brunner@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/165
_
0000-0001-6304-6274

Résultat de la recherche

Filtres

2
2
2
Réinitialiser les filtres

Paramètres

Voici les éléments 1 - 2 sur 2
  • Publication
    Accès libre
    The influence of riverbed heterogeneity patterns on river-aquifer exchange fluxes under different connection regimes
    (2017-9)
    Tang, Qi
    ;
    Kurtz, W.
    ;
    Schilling, Oliver 
    ;
    Brunner, Philip 
    ;
    Vereecken, H.
    ;
    Hendricks Franssen, Harrie-Jan
    Riverbed hydraulic conductivity (K) is a critical parameter for the prediction of exchange fluxes between a river and an aquifer. In this study, the role of heterogeneity patterns was explored using the fully integrated hydrological model HydroGeoSphere simulating complex, variably saturated subsurface flow. A synthetic 3-D river-aquifer reference model was constructed with a heterogeneous riverbed using nonmulti-Gaussian patterns in the form of meandering channels. Data assimilation was used to test the ability of different riverbed K patterns to reproduce hydraulic heads, riverbed K and river-aquifer exchange fluxes. Both fully saturated as well as variably saturated conditions underneath the riverbed were tested. The data assimilation experiments with the ensemble Kalman filter (EnKF) were carried out for four types of geostatistical models of riverbed K fields: (i) spatially homogeneous, (ii) heterogeneous with multiGaussian distribution, (iii) heterogeneous with non-multi-Gaussian distribution (channelized structures) and (iv) heterogeneous with non-multi-Gaussian distribution (elliptic structures). For all data assimilation experiments, state variables and riverbed K were updated by assimilating hydraulic heads. For saturated conditions, heterogeneous geostatistical models allowed a better characterization of net exchange fluxes than a homogeneous approximation. Among the three heterogeneous models, the performance of non-multi-Gaussian models was superior to the performance of the multi-Gaussian model, but the two tested non-multi-Gaussian models showed only small differences in performance from one another. For the variably saturated conditions both the multi-Gaussian model and the homogeneous model performed clearly worse than the two non-multi-Gaussian models. The two non-multi-Gaussian models did not show much difference in performance. This clearly shows that characterizing heterogeneity of riverbed K is important. Moreover, particularly under variably saturated flow conditions the mean and the variance of riverbed K do not provide enough information for exchange flux characterization and additional histogram information of riverbed K provides crucial information for the reproduction of exchange fluxes.
  • Publication
    Accès libre
    Characterisation of river–aquifer exchange fluxes: The role of spatial patterns of riverbed hydraulic conductivities
    (2015-12)
    Tang, Qi
    ;
    Kurtz, W.
    ;
    Brunner, Philip 
    ;
    Vereecken, H.
    ;
    Hendricks Franssen, Harrie-Jan
    Interactions between surface water and groundwater play an essential role in hydrology, hydrogeology, ecology, and water resources management. A proper characterisation of riverbed structures might be important for estimating river–aquifer exchange fluxes. The ensemble Kalman filter (EnKF) is commonly used in subsurface flow and transport modelling for estimating states and parameters. However, EnKF only performs optimally for MultiGaussian distributed parameter fields, but the spatial distribution of streambed hydraulic conductivities often shows non-MultiGaussian patterns, which are related to flow velocity dependent sedimentation and erosion processes. In this synthetic study, we assumed a riverbed with non-MultiGaussian channel-distributed hydraulic parameters as a virtual reference. The synthetic study was carried out for a 3-D river–aquifer model with a river in hydraulic connection to a homogeneous aquifer. Next, in a series of data assimilation experiments three different groups of scenarios were studied. In the first and second group of scenarios, stochastic realisations of non-MultiGaussian distributed riverbeds were inversely conditioned to state information, using EnKF and the normal score ensemble Kalman filter (NS-EnKF). The riverbed hydraulic conductivity was oriented in the form of channels (first group of scenarios) or, with the same bimodal histogram, without channelling (second group of scenarios). In the third group of scenarios, the stochastic realisations of riverbeds have MultiGaussian distributed hydraulic parameters and are conditioned to state information with EnKF. It was found that the best results were achieved for channel-distributed non-MultiGaussian stochastic realisations and with parameter updating. However, differences between the simulations were small and non-MultiGaussian riverbed properties seem to be of less importance for subsurface flow than non-MultiGaussian aquifer properties. In addition, it was concluded that both EnKF and NS-EnKF improve the characterisation of non-MultiGaussian riverbed properties, hydraulic heads and exchange fluxes by piezometric head assimilation, and only NS-EnKF could preserve the initial distribution of riverbed hydraulic conductivities.