Assessment of conceptual model uncertainty for the regional aquifer Pampa del Tamarugal – North Chile

Abstract

Abstract. 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 multi-model 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. GLUEbased 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. ContriCorrespondence to: R. Rojas (rodrigo.rojas@jrc.ec.europa.eu) bution 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.

Assessing hydrological model predictive uncertainty using stochastically generated geological models

“…On the other hand, Rojas et al . () and Refsgaard et al . () conclude that geological model uncertainty is likely to dominate over parameter uncertainty for predictions of variables that have not been included in calibration, i.e.…”

The geomorphometry of endorheic drainage basins: implications for interpreting and modelling their evolution

“…We also added a map with the aquifer in the Pampa del Tamarugal, available from Rojas et al . (). A visual inspection shows a certain correlation between the occurrence of groundwater and drainage density in both basins.…”

“…(b) Occurrence of groundwater and delimitation of the aquifer from Rojas et al . () indicated by PTA. (c) Underlying geology classified according to the geological timescale.…”

Uncertainty of Hydrological Predictions

“…An example of application of GLUE with different modeling solutions is provided by Rojas et al (2009). An example of application of GLUE with different modeling solutions is provided by Rojas et al (2009).…”