TY - JOUR
T1 - Impacts of climate change on precipitation and discharge extremes through the use of statistical downscaling approaches in a Mediterranean basin
AU - Piras, Monica
AU - Mascaro, Giuseppe
AU - Deidda, Roberto
AU - Vivoni, Enrique
N1 - Funding Information: This study was developed in the project CLIMB ( http://www.climb-fp7.eu ) funded by the European Commission's 7th Framework Program. The authors also thank financial support by the Sardinian Region L.R. 7/2007 ( F71J09000120002 ), funding call 2008. They acknowledge the ENSEMBLES project, funded by the EU- FP6 through contract GOCE-CT-2003-505539 , and the data providers in the ECA&D project for making RCM outputs and the E-OBS data set available. Publisher Copyright: © 2015 Elsevier B.V.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5 km2), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs.
AB - Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5 km2), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs.
KW - Climate change
KW - Distributed hydrologic model
KW - Extreme events
KW - Mediterranean region
KW - Statistical downscaling
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U2 - 10.1016/j.scitotenv.2015.06.088
DO - 10.1016/j.scitotenv.2015.06.088
M3 - Article
SN - 0048-9697
VL - 543
SP - 952
EP - 964
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -