Climate change impact on streamflow in large-scale river basins: projections and their uncertainties sourced from GCMs and RCP scenarios

Olga N Nasonova,Georgy V Ayzel,Evgeny E Kovalev,Yeugeniy M Gusev

doi:10.5194/piahs-379-139-2018

Abstract

Abstract. Climate change impact on river runoff was investigated within the framework of the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP2) using a physically-based land surface model Soil Water – Atmosphere – Plants (SWAP) (developed in the Institute of Water Problems of the Russian Academy of Sciences) and meteorological projections (for 2006–2099) simulated by five General Circulation Models (GCMs) (including GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M) for each of four Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). Eleven large-scale river basins were used in this study. First of all, SWAP was calibrated and validated against monthly values of measured river runoff with making use of forcing data from the WATCH data set and all GCMs' projections were bias-corrected to the WATCH. Then, for each basin, 20 projections of possible changes in river runoff during the 21st century were simulated by SWAP. Analysis of the obtained hydrological projections allowed us to estimate their uncertainties resulted from application of different GCMs and RCP scenarios. On the average, the contribution of different GCMs to the uncertainty of the projected river runoff is nearly twice larger than the contribution of RCP scenarios. At the same time the contribution of GCMs slightly decreases with time.

Highlights

The most common approach for assessing the impact of climate change on river runoff is to run regional hydrological models (RHMs) or global hydrological models (GHMs) driven by meteorological projections from General Circulation Models (GCMs)
Many modeling studies have been carried out to explore uncertainties in projected hydrological variables (e.g., Wilby and Harris, 2006; Gosling et al, 2011; Vetter et al, 2017; Nasonova et al, 2018), according to which the following sources of uncertainties can be distinguished with respect to climatic runoff: scenarios of greenhouse-gas emissions to the atmosphere; application of different GCMs for simulating meteorological projections; downscaling and post-processing biascorrection techniques applied for GCMs’ outputs; hydrological models applied for hydrological projections
It was concluded that studying the contribution of different sources of uncertainties to the overall uncertainty of hydrological projections should be continued with involvement of large amount of river basins located in different parts of the Earth under a wide variety of climatic conditions

Summary

Introduction

The most common approach for assessing the impact of climate change on river runoff is to run regional hydrological models (RHMs) or global hydrological models (GHMs) driven by meteorological projections from General Circulation Models (GCMs). Many modeling studies have been carried out to explore uncertainties in projected hydrological variables (e.g., Wilby and Harris, 2006; Gosling et al, 2011; Vetter et al, 2017; Nasonova et al, 2018), according to which the following sources of uncertainties can be distinguished with respect to climatic runoff: scenarios of greenhouse-gas emissions to the atmosphere; application of different GCMs for simulating meteorological projections; downscaling and post-processing biascorrection techniques applied for GCMs’ outputs; hydrological models applied for hydrological projections In the latter case, uncertainties can be associated with differences in model structure, complexity, representation of hydrological processes, spatial and temporal resolution, estimation and calibration of model parameters. This was done within the framework of the second phase of the Inter-Sectoral Impact Model In-

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