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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

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  • Publication
    Accès libre
    Calibration of a groundwater model using pattern information from remote sensing data
    (2009-5-26)
    Li, H. T.
    ;
    Brunner, Philip 
    ;
    Kinzelbach, Wolfgang
    ;
    Li, W. P.
    ;
    Dong, X. G.
    Due to the chronic lack of verification data, hydrologic models are notoriously over-parameterized. If a large number of parameters are estimated, while few verification data are available, the calibrated model may have little predictive value. However, recent development in remote sensing (RS) techniques allows generation of spatially distributed data that can be used to construct and verify hydrological models. These additional data reduce the ambiguity of the calibration process and thus increase the predictive value of the model. An example for such remotely sensed data is the spatial distribution of phreatic evaporation. In this modeling approach, we use the spatial distribution of phreatic evaporation obtained by remote sensing images as verification data Compared to the usual limited amount of head data, the spatial distribution of evaporation data provides a complete areal coverage. However, the absolute values of the evaporation data are uncertain and therefore three ways of using the spatial distribution pattern of evaporation were tested and compared. The first way is to directly use the evaporation pattern defined in a relative manner by dividing the evaporation rate in a pixel by the total evaporation of a selected rectangular area of interest. Alternatively, the discrete fourier transform (DFT) or the discrete wavelet transform (DWT) are applied to the relative evaporation pattern in the space domain defined before. Seven different combinations of using hydraulic head data and/or evaporation pattern data as conditioning information have been tested. The code PEST, based on the least-squares method, was used as an automatic calibration tool. From the calibration results, we can conclude that the evaporation pattern can replace the head data in the model calibration process, independently of the way the evaporation pattern is introduced into the calibration procedure. (C) 2009 Elsevier B.V All rights reserved.
  • Publication
    Accès libre
    Using remote sensing to regionalize local precipitation recharge rates obtained from the Chloride Method
    (2004-5-28)
    Brunner, Philip 
    ;
    Bauer, Peter
    ;
    Eugster, Martin
    ;
    Kinzelbach, Wolfgang
    Water supply in semiarid Botswana is, to a large extent, based on groundwater. In the planning of a groundwater abstraction scheme, criteria for the sustainability of the abstraction with respect to both quantity and quality have to be satisfied. The most important parameter in the context of quantitative sustainability is the long-term average groundwater recharge together with its spatial distribution. A method is developed to calculate a recharge map that can be used in a groundwater model. The relative distribution of recharge is obtained from remotely sensed data and then calibrated with local values of recharge derived from the Chloride Method. The method was tested for two sites in Botswana, the Chobe Region and Ngamiland. (C) 2004 Elsevier B.V. All rights reserved.
  • Publication
    Accès libre
    Uncertainty assessment and implications for data acquisition in support of integrated hydrologic models
    Brunner, Philip 
    ;
    Doherty, J
    ;
    Simmons, Craig T
    The data set used for calibration of regional numerical models which simulate groundwater flow and vadose zone processes is often dominated by head observations. It is to be expected therefore, that parameters describing vadose zone processes are poorly constrained. A number of studies on small spatial scales explored how additional data types used in calibration constrain vadose zone parameters or reduce predictive uncertainty. However, available studies focused on subsets of observation types and did not jointly account for different measurement accuracies or different hydrologic conditions. In this study, parameter identifiability and predictive uncertainty are quantified in simulation of a 1-D vadose zone soil system driven by infiltration, evaporation and transpiration. The worth of different types of observation data (employed individually, in combination, and with different measurement accuracies) is evaluated by using a linear methodology and a nonlinear Pareto-based methodology under different hydrological conditions. Our main conclusions are (1) Linear analysis provides valuable information on comparative parameter and predictive uncertainty reduction accrued through acquisition of different data types. Its use can be supplemented by nonlinear methods. (2) Measurements of water table elevation can support future water table predictions, even if such measurements inform the individual parameters of vadose zone models to only a small degree. (3) The benefits of including ET and soil moisture observations in the calibration data set are heavily dependent on depth to groundwater. (4) Measurements of groundwater levels, measurements of vadose ET or soil moisture poorly constrain regional groundwater system forcing functions.