Literature DB >> 25863313

Hydrological simulation of Po River (North Italy) discharge under climate change scenarios using the RCM COSMO-CLM.

R Vezzoli1, P Mercogliano2, S Pecora3, A L Zollo4, C Cacciamani5.   

Abstract

The impacts of climate change on Po River discharges are investigated through a set of climate, hydrological, water-balance simulations continuous in space and time. Precipitation and 2m mean temperature fields from climate projections under two different representative concentration pathways, RCP4.5 and RCP8.5, have been used to drive the hydrological model. Climate projections are obtained nesting the regional climate model COSMO-CLM into the global climate model CMCC-CM. The bias in climate projections is corrected applying the distribution derived quantile mapping. The persistence of climate signal in precipitation and temperature after the bias correction is assessed in terms of climate anomaly for 2041-2070 and 2071-2100 periods versus 1982-2011. To account for the overall uncertainty of emission scenarios, climate models and bias correction, the hydrological/water balance simulations are carried out using both raw and bias corrected climate datasets. Results show that under both RCPs, either considering raw and bias corrected climate datasets, temperature is expected to increase on the whole Po River basin and in all the seasons; the most significant changes in precipitation and discharges occur in summer, when the reduction of precipitation leads to an increase in low flow duration and occurrence likelihood, and in autumn and winter where precipitation shows a positive variation increasing the high flows frequency.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bias correction; Climate projections; Hydrological modelling; Po River basin; Regional climate model; Water availability

Year:  2015        PMID: 25863313     DOI: 10.1016/j.scitotenv.2015.03.096

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  A distributional multivariate approach for assessing performance of climate-hydrology models.

Authors:  Renata Vezzoli; Gianfausto Salvadori; Carlo De Michele
Journal:  Sci Rep       Date:  2017-09-21       Impact factor: 4.379

2.  Simulating the Impact of Future Climate Change and Ecological Restoration on Trade-Offs and Synergies of Ecosystem Services in Two Ecological Shelters and Three Belts in China.

Authors:  Liang-Jie Wang; Shuai Ma; Yong-Peng Qiao; Jin-Chi Zhang
Journal:  Int J Environ Res Public Health       Date:  2020-10-26       Impact factor: 3.390

  2 in total

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