|Reference : Assessment of conceptual model uncertainty for the regional aquifer Pampa del Tamarug...|
|Scientific journals : Article|
|Engineering, computing & technology : Geological, petroleum & mining engineering|
|Assessment of conceptual model uncertainty for the regional aquifer Pampa del Tamarugal – North Chile|
|Rojas, Rodrigo [Katholieke Universiteit Leuven - KUL > Department of Earth and Environmental Sciences > Applied Geology and Mineralogy > >]|
|Batelaan, Okke [Vrije Universiteit Brussel - VUB > Hydrology and Hydraulic Engineering > > >]|
|Feyen, Luk [DG-Joint Research Centre (JRC) > Institute of Environment and Sustainability > Land management and natural hazards unit > >]|
|Dassargues, Alain [Université de Liège - ULg > Département Argenco : Secteur GEO3 > Hydrogéologie & Géologie de l'environnement >]|
|Hydrology and Earth System Sciences|
|European Geosciences Union|
|Yes (verified by ORBi)|
|[en] uncertainty ; groundwater flow modelling ; Pampa del Tamarugal Aquifer ; Generalized Likelihood Uncertainty Estimation (GLUE) ; Bayesian Model Averaging (BMA) ; conceptual model uncertainty|
|[en] In this work we assess the uncertainty in modelling the groundwater flow for the Pampa del Tamarugal Aquifer (PTA) – North Chile using a novel and fully integrated multimodel approach aimed at explicitly accounting for uncertainties arising from the definition of alternative conceptual models. The approach integrates the Generalized Likelihood Uncertainty Estimation (GLUE) and Bayesian Model Averaging (BMA) methods.
For each member of an ensemble M of potential conceptualizations, model weights used in BMA for multi-model aggregation are obtained from GLUE-based likelihood values. These model weights are based on model performance, thus, reflecting how well a conceptualization reproduces an observed dataset D. GLUE-based cumulative predictive distributions for each member of M are then aggregated obtaining predictive distributions accounting for conceptual model uncertainties. For the PTA we propose an ensemble of eight alternative conceptualizations covering all major features of groundwater flow models independently developed in past studies and including two recharge mechanisms which have been source of debate for several years. Results showed that accounting for heterogeneities in the hydraulic conductivity field (a) reduced
the uncertainty in the estimations of parameters and state variables, and (b) increased the corresponding model weights used for multi-model aggregation. This was more noticeable when the hydraulic conductivity field was conditioned on available hydraulic conductivity measurements. Contribution of conceptual model uncertainty to the predictive uncertainty varied between 6% and 64% for ground water head estimations and between 16% and 79% for ground water flow estimations. These results clearly illustrate the relevance of conceptual model uncertainty.
|Researchers ; Professionals|
|The officila publication can be found on the web site of 'Hydrology and Earth System Sciences'
An Interactive Open Access Journal of the European Geosciences Union.
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