Application of a multi-model approach to account for conceptual model and scenario uncertainties in groundwater modelling

Groundwater models are often used to predict the future behaviour of groundwater systems. These models may vary in complexity from simplified system conceptualizations to more intricate versions. It has been recently suggested that uncertainties in model predictions are largely dominated by uncertainties arising from the definition of alternative conceptual models. Different external factors such as climatic conditions or groundwater abstraction policies, on the other hand, may also play an important role. Rojas et al. (2008) proposed a multimodel approach to account for predictive uncertainty arising from forcing data (inputs), parameters and alternative conceptualizations. In this work we extend upon this approach to include uncertainties arising from the definition of alternative future scenarios and we apply the extended methodology to a real aquifer system underlying the Walenbos Nature Reserve area in Belgium. Three alternative conceptual models comprising different levels of geological knowledge are considered. Additionally, three recharge settings (scenarios) are proposed to evaluate recharge uncertainties. A joint estimation of the predictive uncertainty including parameter, conceptual model and scenario uncertainties is estimated for groundwater budget terms. Finally, results obtained using the improved approach are compared with the results obtained from methodologies that include a calibration step and which use a model selection criterion to discriminate between alternative conceptualizations. Results showed that conceptual model and scenario uncertainties significantly contribute to the predictive variance for some budget terms. Besides, conceptual model uncertainties played an important role even for the case when a model was preferred over the others. Predictive distributions showed to be considerably different in shape, central moment and spread among alternative conceptualizations and scenarios analysed. This reaffirms the idea that relying on a single conceptual model driven by a particular scenario, will likely produce bias and under-dispersive estimations of the predictive uncertainty. Multimodel methodologies based on the use of model selection criteria produced ambiguous results. In the frame of a multimodel approach, these inconsistencies are critical and can not be neglected. These results strongly advocate the idea of addressing conceptual model uncertainty in groundwater modelling practice. Additionally, considering alternative future recharge uncertainties will permit to obtain more realistic and, possibly, more reliable estimations of the predictive uncertainty.