Improvement of hydroclimatic projections over Southeast Spain by applying a novel RCM ensemble approach
Climate model outputs can be used as climate forcing for hydrological models to study the impact of climate change on the water cycle. This usually propagates cumulative uncertainties, transferring the errors from the climate models to the hydrological models. Then, methodologies are needed to evalu...
| Autores: | , , |
|---|---|
| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Recursos: | Universidad Politécnica de Cartagena(UPCT) |
| Repositorio: | Repositorio Digital UPCT |
| OAI Identifier: | oai:repositorio.upct.es:10317/10357 |
| Acesso em linha: | http://hdl.handle.net/10317/10357 https://www.mdpi.com/2073-4441/10/1/52 |
| Access Level: | acceso abierto |
| Palavra-chave: | Climate change Regional climate models PDF ensemble Hydrological cycle Runoff projection Uncertainties reduction Hydrological modeling Ingeniería Hidráulica 2508 Hidrología |
| Resumo: | Climate model outputs can be used as climate forcing for hydrological models to study the impact of climate change on the water cycle. This usually propagates cumulative uncertainties, transferring the errors from the climate models to the hydrological models. Then, methodologies are needed to evaluate the impact of climate change at basin scale by reducing the uncertainties involved in the modeling chain. The paper aims to assess the impact of climate change on the runoff, considering a novel approach to build a Regional Climate Model (RCM) ensemble as climate forcing for a parsimonious spatially distributed hydrological model. A semiarid basin of southeast of Spain was selected for the study. The RCM ensembles were built based on seasonal and annual variability of rainfall and temperature. If the runoff projections for 2021–2050 are compared to the 1961–1990 observed period, a significant decrease in runoff equal to −20% (p-value t-test 0.05) was projected. However, by changing the observed period to 1971–2000, a despicable change (2.5%) is identified. This fact demonstrates that trends based on short records are very sensitive to the beginning and end dates, due to the natural variability. Special attention should be paid to the selection of the period for impact studies. |
|---|