Evaluation of climate change impacts on the hydrologic response of a sparsely-monitored basin in Sardinia, Italy, through distributed hydrologic simulations and hydrometeorological downscaling

摘要

The water resources and hydrologic extremes in Mediterranean basins are heavily influenced by climate variability. Modeling these watersheds is difficult due to the complex nature of the hydrologic response as well as the sparseness of hydrometeorological observations.udIn this work, we first present a strategy to calibrate a distributed hydrologic model, known as TIN-based Real-time Integrated Basin Simulator (tRIBS), in the Rio Mannu basin, a mediumsized watershed (472.5 km2) located in an agricultural area in Sardinia, Italy. In the basin,udprecipitation, streamflow and meteorological data were collected within different historical periods and at diverse temporal resolutions. We designed two statistical tools for downscaling precipitation and potential evapotranspiration data to create the hourly, high-resolution forcing for the hydrologic model from daily records. Despite the presence of several sources ofuduncertainty in the observations and model parameterization, the use of the disaggregated forcing led to good calibration and validation performances for the tRIBS model, when daily discharge observations were available.udFuture climate projections based on global and regional climate models (GCMs and RCMs) indicate that the Mediterranean basins will most likely suffer a decrease in water availability and an intensification of hydrologic extremes. Process-based distributed hydrologicudmodels (DHMs), like tRIBS, have the potential to simulate the complex hydrologic response of Mediterranean watersheds. Thus, when used in combination with RCMs, DHMs can reduce the uncertainty in the quantification of the local impacts of climate change on water resources. Inudthis study, we apply the calibrated tRIBS model in the Rio Mannu basin to evaluate the effects of climate changes reducing related uncertainties. The two downscaling algorithms and the DHM were used to simulate the watershed response to a set of bias-corrected outputs from four RCMsudfor two simulation extents: a reference (1971 to 2000) and a future (2041 to 2070) period. The time series and spatial maps simulated by the DHM were then post-processed by computing several metrics to quantify the changes on water resource availability and hydrologic extremes inudthe future climate scenarios as compared to historical conditions. The research was carried out within the CLIMB project, founded by the 7th Framework Programme of the European Commission.