The influence of riverbed heterogeneity patterns on river-aquifer exchange fluxes under different connection regimes
Author(s)
Tang, Qi
Kurtz, W.
Vereecken, H.
Hendricks Franssen, Harrie-Jan
Date issued
September 2017
In
Journal of Hydrology
Vol
2017
No
554
From page
383
To page
396
Reviewed by peer
1
Subjects
Data assimilation Ensemble Kalman filter Riverbed characterization Patterns Fully-coupled physically-based flow modelling HydroGeoSphere
Abstract
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.
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 type
journal article
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