Multimodel assessment of climate change-induced hydrologic impacts for a Mediterranean catchment

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).

Temperature effects on heavy rainfall modify catchment hydro-morphological response

“…In recent years, there was an increase in the availability of distributed hydrological models (Fatichi et al, 2016;Paniconi and Putti 2015) and they have been used in the context of climate impacts (e.g. Dams et al, 2015;Fatichi et al, 2015;Perra et al, 2018). However, this is much less the case for geomorphological impacts (e.g.…”

Investigating Parameter Transferability across Models and Events for a Semiarid Mediterranean Catchment

“…TOPKAPI has been successfully implemented as a research and operational hydrologic model in several catchments worldwide (e.g., [52][53][54][55]). The CATHY model has been used in many exploratory studies, benchmarking exercises, and real catchment applications (e.g., [18,31,[56][57][58][59]).…”

“…Location of the Rio Mannu basin within (a) Italy and (b) Sardinia. (c) Boundaries (in WGS84 UTM coordinates) and elevation and stream network of the basin (adapted from Perra et al[31]). …”

“…(a) Soil texture and (b) land cover maps used for the three hydrologic models (adapted from Perra et al,[31]). …”

Analysis of a Flash Flood in a Small Basin in Crete

“…Climate change effect is expected to produce more intense and more frequent heavy precipitation events [12]. Many researchers have studied the hydrological impacts of climate change in several Mediterranean basins, based on different Representative Concentration Pathways [13,14], as well as bias-corrected and downscaled datasets from Global Climate Models and Regional Climate Models [15].…”