Abstract:La dinámica de un mundo global y el hombre como nueva fuerza geológica plantean la necesidad de tomar decisiones robustas, diseñar estrategias de manejo y de adaptarse al cambio climático. Este estudio investiga la respuesta hidrológica de la cuenca hidrográfica del río Aipe (688.9 km 2), en Huila, Colombia, en acorde con los escenarios de cambio climático desde 2011 a 2040. El modelo hidrológico abcd de Thomas (4 parámetros) fue calibrado y validado comparando el caudal simulado y lo observado en el punto de … Show more
“…Figure 12 represents the output from the hydrological model. The abcd water balance model implemented in Aipe catchment is described in detail by Romero-Cuéllar et al (2018). The simulated streamflow time series in Figure 12 shows that deterministic hydrological predictions overestimate the observed streamflows.…”
Section: Applicationsmentioning
confidence: 99%
“…Romero-Cuellar, J., Buitrago-Vargas, A., Quintero-Ruiz, T., Francés, F (2018) Modelling the potential impacts of climate change on the hydrology of the Aipe river basin in Huila, Colombia, Ribagua, 5:1, 63-78, DOI:…”
Section: Future Research Linesmentioning
confidence: 99%
“…Romero-Cuellar, J., Adelfio, G., Francés, F. (2018). Estimating predictive hydrological uncertainty by dressing a probabilistic post-processing approach; a comparison with application to a tropical catchment.…”
Section: Conference Contributions and Publications In Proceedingsmentioning
“…Figure 12 represents the output from the hydrological model. The abcd water balance model implemented in Aipe catchment is described in detail by Romero-Cuéllar et al (2018). The simulated streamflow time series in Figure 12 shows that deterministic hydrological predictions overestimate the observed streamflows.…”
Section: Applicationsmentioning
confidence: 99%
“…Romero-Cuellar, J., Buitrago-Vargas, A., Quintero-Ruiz, T., Francés, F (2018) Modelling the potential impacts of climate change on the hydrology of the Aipe river basin in Huila, Colombia, Ribagua, 5:1, 63-78, DOI:…”
Section: Future Research Linesmentioning
confidence: 99%
“…Romero-Cuellar, J., Adelfio, G., Francés, F. (2018). Estimating predictive hydrological uncertainty by dressing a probabilistic post-processing approach; a comparison with application to a tropical catchment.…”
Section: Conference Contributions and Publications In Proceedingsmentioning
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 be difficult to calculate the likelihood itself in hydrological modelling, specially working with complex models or with ungauged catchments. Therefore, we propose the ABC post-processor that exchanges the requirement of calculating the likelihood function by the use of some sufficient summary statistics and synthetic datasets. The aim is to show that the conditional predictive distribution is qualitatively similar produced by the exact predictive (MCMC post-processor) or the approximate predictive (ABC post-processor). We also use MCMC post-processor as a benchmark to make results more comparable with the proposed method. We test the ABC post-processor in two scenarios: i) the Aipe catchment with tropical climate and a spatially-lumped hydrological model (Colombia) and ii) the Oria catchment with oceanic climate and a spatially-distributed hydrological model (Spain). The main finding of the study is that the approximate (ABC post-processor) conditional predictive uncertainty is almost equivalent to the exact predictive (MCMC post-processor) in both scenarios.
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