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Beyond Classical Observations in Hydrogeology: The Advantages of Including Exchange Flux, Temperature, Tracer Concentration, Residence Time, and Soil Moisture Observations in Groundwater Model Calibration
Date de parution
2019-2
In
Reviews of Geophysics
Vol.
1
No
57
De la page
146
A la page
182
Revu par les pairs
1
Résumé
Traditionally, groundwater and surface water flow models have been calibrated against two observation
types: hydraulic heads and surface water discharge. It has repeatedly been demonstrated, however, that
these classical observations do not contain sufficient information to calibrate flow models. To reduce the
predictive uncertainty of flow models, the consideration of other observation types constitutes a promising
way forward. Despite the ever‐increasing availability of other observation types, however, they are still
unconventional when it comes to flow model calibration. By reviewing studies that included nonclassical
observations in flow model calibration, benefits and challenges associated with their integration in flow
model calibration were identified, and their information content was analyzed. While explicit simulation
of mass transport processes in flow models poses challenges, even simplified approaches to integrate
tracer concentrations yield significantly better calibration results than using only classical observations.
For a majority of calibrated flow models, observations of tracer concentrations and of exchange fluxes
were beneficial. Temperature observations improved the simulation of heat transport but often worsened
all other model outcomes. Only when temperature observations were made within 2 m of the surface
water‐groundwater interface did they have the potential to also improve flow and mass transport
simulations. Surprisingly, many models were calibrated manually rather than with the widely available,
mathematically robust and automated tools. There is a clear need for more systematic implementation of
unconventional observations and automated flow model calibration as well as for more systematic quantification of the information content of unconventional observations.
types: hydraulic heads and surface water discharge. It has repeatedly been demonstrated, however, that
these classical observations do not contain sufficient information to calibrate flow models. To reduce the
predictive uncertainty of flow models, the consideration of other observation types constitutes a promising
way forward. Despite the ever‐increasing availability of other observation types, however, they are still
unconventional when it comes to flow model calibration. By reviewing studies that included nonclassical
observations in flow model calibration, benefits and challenges associated with their integration in flow
model calibration were identified, and their information content was analyzed. While explicit simulation
of mass transport processes in flow models poses challenges, even simplified approaches to integrate
tracer concentrations yield significantly better calibration results than using only classical observations.
For a majority of calibrated flow models, observations of tracer concentrations and of exchange fluxes
were beneficial. Temperature observations improved the simulation of heat transport but often worsened
all other model outcomes. Only when temperature observations were made within 2 m of the surface
water‐groundwater interface did they have the potential to also improve flow and mass transport
simulations. Surprisingly, many models were calibrated manually rather than with the widely available,
mathematically robust and automated tools. There is a clear need for more systematic implementation of
unconventional observations and automated flow model calibration as well as for more systematic quantification of the information content of unconventional observations.
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journal article
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