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Hydrological post-processing based on approximate Bayesian computation (ABC)

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Romero-Cuellar, J.; Abbruzzo, A.; Adelfio, G.; Francés, F. (2019). Hydrological post-processing based on approximate Bayesian computation (ABC). Stochastic Environmental Research and Risk Assessment. 33(7):1361-1373. https://doi.org/10.1007/s00477-019-01694-y

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Title: Hydrological post-processing based on approximate Bayesian computation (ABC)
Author: Romero-Cuellar, Jonathan Abbruzzo, Antonino Adelfio, Giada Francés, F.
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient
Issued date:
[EN] This study introduces a method to quantify the conditional predictive uncertainty in hydrological post-processing contexts when it is cumbersome to calculate the likelihood (intractable likelihood). Sometimes, it can ...[+]
Subjects: Free-likelihood approach , Probabilistic modelling , Uncertainty analysis , Hydrological forecasting , Summary statistics
Copyrigths: Reserva de todos los derechos
Stochastic Environmental Research and Risk Assessment. (issn: 1436-3240 )
DOI: 10.1007/s00477-019-01694-y
Publisher version: http://doi.org/10.1007/s00477-019-01694-y
Project ID:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093717-B-I00/ES/MEJORAS DEL CONOCIMIENTO Y DE LAS CAPACIDADES DE MODELIZACION PARA LA PROGNOSIS DE LOS EFECTOS DEL CAMBIO GLOBAL EN UNA CUENCA HIDROLOGICA/
This study was partially supported by the Departamento del Huila Scholarship Program No. 677 (Colombia) and Colciencias, by the Spanish Research Project TETIS-MED (ref. CGL2014-58127-C3-3-R) and TETIS-CHANGE (ref.RTI2018 ...[+]
Type: Artículo


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