Abstract
Abstract. This work addresses the impact of climate change on the hydrology of a catchment in the Mediterranean, a region that is highly susceptible to variations in rainfall and other components of the water budget. The assessment is based on a comparison of responses obtained from five hydrologic models implemented for the Rio Mannu catchment in southern Sardinia (Italy). The examined models – CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TOPographic Kinematic APproximation and Integration (TOPKAPI), TIN-based Real time Integrated Basin Simulator (tRIBS), and WAter balance SImulation Model (WASIM) – are all distributed hydrologic models but differ greatly in their representation of terrain features and physical processes and in their numerical complexity. After calibration and validation, the models were forced with bias-corrected, downscaled outputs of four combinations of global and regional climate models in a reference (1971–2000) and future (2041–2070) period under a single emission scenario. Climate forcing variations and the structure of the hydrologic models influence the different components of the catchment response. Three water availability response variables – discharge, soil water content, and actual evapotranspiration – are analyzed. Simulation results from all five hydrologic models show for the future period decreasing mean annual streamflow and soil water content at 1 m depth. Actual evapotranspiration in the future will diminish according to four of the five models due to drier soil conditions. Despite their significant differences, the five hydrologic models responded similarly to the reduced precipitation and increased temperatures predicted by the climate models, and lend strong support to a future scenario of increased water shortages for this region of the Mediterranean basin. The multimodel framework adopted for this study allows estimation of the agreement between the five hydrologic models and between the four climate models. Pairwise comparison of the climate and hydrologic models is shown for the reference and future periods using a recently proposed metric that scales the Pearson correlation coefficient with a factor that accounts for systematic differences between datasets. The results from this analysis reflect the key structural differences between the hydrologic models, such as a representation of both vertical and lateral subsurface flow (CATHY, TOPKAPI, and tRIBS) and a detailed treatment of vegetation processes (SWAT and WASIM).
Highlights
Climate studies agree on the prediction that the Mediterranean area will be affected by changes under global warming (IPCC, 2014)
Climate change impact assessment at the catchment scale is usually conducted through a procedure that involves the following steps (e.g., Xu et al, 2005): (i) selection of global climate models (GCMs) and regional climate models (RCMs) for future climate predictions; (ii) correction of the discrepancies between simulated and observed climatological features; (iii) application of downscaling techniques to increase the coarse scale of climate model outputs to the finer resolutions required by hydrologic models; and (iv) use of downscaled outputs as forcing for the calibrated hydrologic models to simulate the basin hydrologic response (Sulis et al, 2011, 2012; Piras et al, 2014; Hawkins et al, 2015; Majone et al, 2016; Meyer et al, 2016)
Five hydrologic models forced with the outputs of four combinations of global and regional climate models were compared to evaluate climate change consequences on the response of a medium-sized Mediterranean basin, the Rio Mannu catchment
Summary
Climate studies agree on the prediction that the Mediterranean area will be affected by changes under global warming (IPCC, 2014). Climate change impact assessment at the catchment scale is usually conducted through a procedure that involves the following steps (e.g., Xu et al, 2005): (i) selection of global climate models (GCMs) and regional climate models (RCMs) for future climate predictions; (ii) correction of the discrepancies between simulated and observed climatological features; (iii) application of downscaling techniques to increase the coarse scale of climate model outputs to the finer resolutions required by hydrologic models; and (iv) use of downscaled outputs as forcing for the calibrated hydrologic models to simulate the basin hydrologic response (Sulis et al, 2011, 2012; Piras et al, 2014; Hawkins et al, 2015; Majone et al, 2016; Meyer et al, 2016) Each of these steps is affected by uncertainties (Xu and Singh, 2004), including the choice of emission scenarios and climate forcings (Giorgi and Mearns, 2002; Tebaldi et al, 2005; Pechlivanidis et al, 2017), the selection of downscaling techniques (Wood et al, 2004; Im et al, 2010) and hydrologic model (Clark et al, 2008; Jiang et al, 2007; Dams et al, 2015), and the availability of observed data required for calibration and validation of both downscaling techniques and hydrologic models. Each of these steps is affected by uncertainties (Xu and Singh, 2004), including the choice of emission scenarios and climate forcings (Giorgi and Mearns, 2002; Tebaldi et al, 2005; Pechlivanidis et al, 2017), the selection of downscaling techniques (Wood et al, 2004; Im et al, 2010) and hydrologic model (Clark et al, 2008; Jiang et al, 2007; Dams et al, 2015), and the availability of observed data required for calibration and validation of both downscaling techniques and hydrologic models. Hawkins and Sutton (2009) estimate that by the end of the century, the emission scenarios will represent the dominant source of uncertainty in climate projections
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