 |
| Titel |
Assessment of conceptual model uncertainty for the regional aquifer Pampa del Tamarugal – North Chile |
| VerfasserIn |
R. Rojas, O. Batelaan, L. Feyen, A. Dassargues |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 14, no. 2 ; Nr. 14, no. 2 (2010-02-02), S.171-192 |
| Datensatznummer |
250012175
|
| Publikation (Nr.) |
 copernicus.org/hess-14-171-2010.pdf |
|
|
|
|
|
| Zusammenfassung |
| 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. 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. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|