Beyond Classical Observations in Hydrogeology: The Advantages of Including Exchange Flux, Temperature, Tracer Concentration, Residence Time, and Soil Moisture Observations in Groundwater Model Calibration

Abstract

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. Plain Language Summary Traditionally, groundwater and surface water flow models, which are critical for water resources assessment, have been calibrated against only two classical observation types: groundwater levels and surface water discharge. In the past, it has repeatedly been demonstrated that these classical observations do not contain sufficient information to calibrate the parameters required for the simulation of groundwater and surface water flow systems. Owing to the rapid development of measurement techniques throughout the last three decades, however, many other observations of hydrological systems have become widely available. Despite this, observation types other than the classical ones are still unconventional when it comes to flow model calibration. The overall goal of this review is to identify optimal observation types and procedures for flow model calibration and hydrological predictions. We found that observations of tracer concentrations and exchange fluxes are beneficial for most flow models. Temperatures improve the simulation of heat transport but often worsen other flow model outcomes, unless temperatures are measured within 2 m of the surface water-groundwater interface. We identified a need for...

On the assimilation of environmental tracer observations for model-based decision support

“…This study explores the ramifications of assimilating tritium concentration and tritium-derived interpretation observations, specifically in the context of two examples of decision-support modeling. The benefit or otherwise of tritium data in other contexts such as site system characterization and understanding and conceptual-model development is therefore not the focus of the current study; this study is concerned with a model's ability to "predict" (in two decision-support contexts) rather than "explain" (observed system behavior), as contrasted by Shmueli (2010).…”

On the assimilation of environmental tracer observations for model-based decision support

“…They reported that, overall, tracer data were of considerable benefit in terms of forecast uncertainty reduction. In a recent review paper, Schilling et al (2019) state that assimilation of concentration observations through surface water/groundwater flow model history matching "harbors huge potential", based on the findings of previous studies, while assimilation of tracer-derived residence time observations in these models also often help significantly (where an appropriate approach is adopted, e.g., Sanford (2011); Zuber et al (2011)).…”

Investigations into the First Operational Aquifer Thermal Energy Storage System in Wallonia (Belgium): What Can Potentially Be Expected?

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“…A combined flow and transport calibration would have provided a more robust model but with a level of detail that would not likely be significant compared to the scale of the study area. Applying homogeneous transport parameters to the model domain based on local scale calibrated parameters between O1 and W2 imposes the unique character of these parameters and details on heterogeneous materials are lost [71,76,77]. Extensive datasets collected in all the wells by carrying out several heat and solute tracer tests would have helped to better characterize the aquifer [68].…”