Abstract
The response of Mediterranean small catchments hydrology to climate change is still relatively unexplored. Regional Climate Models (RCMs) are an established tool for evaluating the expected climate change impact on hydrology. Due to the relatively low resolution and systematic errors, RCM outputs are routinely and statistically post-processed before being used in impact studies. Nevertheless, these techniques can impact the original simulated trends and then impact model results. In this work, we characterize future changes of a small Apennines (Central Italy) catchment hydrology, according to two radiative forcing scenarios (Representative Concentration Pathways, RCPs, 4.5 and 8.5). We also investigate the impact of a widely used bias correction technique, the empirical Quantile Mapping (QM) on the original Climate Change Signal (CCS), and the subsequent alteration of the original Hydrological Change Signal (HCS). Original and bias-corrected simulations of five RCMs from Euro-CORDEX are used to drive the CETEMPS hydrological model CHyM. HCS is assessed by using monthly mean discharge and a hydrological-stress index. HCS shows a large spatial and seasonal variability where the summer results are affected by the largest decrease of mean discharge (down to −50%). QM produces a small alteration of the original CCS, which generates a generally wetter HCS, especially during the spring season.
Highlights
Projecting the response of the hydrological cycle to climate change is essential for managing freshwater resources in future decades
The attention should not be paid to the improvement provided by the Quantile Mapping (QM), which by construction leads simulated Probability Density Functions (PDFs) much closer to the observed PDFs but rather to the original simulations’
Simulations shown belong to a representative Regional Climate Models (RCMs) (CNRM-CM5-RCA4)
Summary
Projecting the response of the hydrological cycle to climate change is essential for managing freshwater resources in future decades. There is a particular concern on how different precipitation statistics (i.e., mean and extremes) will scale with different levels of global warming [1,2]. In spite of these uncertainties, a large consensus prevails on expecting an acceleration of the hydrological cycle in warmer climate conditions [3,4,5,6,7,8,9]. Another level of complexity is added when projected changes, to be efficiently informative, have to be scaled at the regional scale
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