Book/Dissertation / PhD Thesis

FZJ-2018-04671

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Characterization of spatial-temporal varying riverbed hydraulic conductivity and its role on the estimation of river-aquifer exchangefluxes with data assimilation

Tang, Q. (Corresponding author)FZJ*

2018
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich
ISBN: 978-3-95806-339-6

Please use a persistent id in citations: http://hdl.handle.net/2128/19568  urn:nbn:de:0001-2018091906

Abstract: Interactions between surface water and groundwater play an essential role in hydrology, hydrogeology, ecology, and water resources management. When modelling the river-aquifer interactions, a proper characterization of riverbed properties such as the riverbed topography and the riverbed hydraulic conductivity (Krb) can be important for the prediction of exchange fluxes between a river and an aquifer. These riverbed properties are changing in time and space. Specifically, flood events may change the riverbed elevation as well as the riverbed texture and structure, which in turn can influence the Krb and river-aquifer exchange fluxes. One main objective of this PhD-work was to investigate the role of different Krb patterns on prediction of hydrologic states and river-aquifer exchange fluxes and to evaluate methodologies for improving the characterization of the spatial and temporal variability of Krb, in combination with different conceptualizations of the heterogeneity of the riverbed. In particular, it was evaluated whether variants of the Ensemble Kalman Filter (EnKF), an ensemble based data assimilation technique, can reproduce such interactions. EnKF is commonly used in subsurface flow and transport modelling for estimating states and parameters. However, EnKF only performs optimally for multi-Gaussian distributed parameter fields, but the spatial distribution of Krb often shows complex non-multi-Gaussian patterns, which are related to flow velocity dependent sedimentation and erosion processes. In this work, multiple types of heterogeneous Krb patterns, based on different geostatistical models, were evaluated and compared.

Note: RWTH Aachen, Diss., 2018

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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2018

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Database coverage:
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