Abstract
Abstract. We quantify uncertainty in the impacts of climate change on the discharge of Rio Grande, a major tributary of the Paraná River in South America and one of the most important basins in Brazil for water supply and hydro-electric power generation. We consider uncertainty in climate projections associated with the greenhouse-gas emission scenarios (A1b, A2, B1, B2) and increases in global mean air temperature of 1 to 6° C for the HadCM3 GCM (Global Circulation Model) as well as uncertainties related to GCM structure. For the latter, multimodel runs using 6 GCMs (CCCMA CGCM31, CSIRO Mk30, IPSL CM4, MPI ECHAM5, NCAR CCSM30, UKMO HadGEM1) and HadCM3 as baseline, for a +2° C increase in global mean temperature. Pattern-scaled GCM-outputs are applied to a large-scale hydrological model (MGB-IPH) of Rio Grande Basin. Based on simulations using HadCM3, mean annual river discharge increases, relative to the baseline or control run period (1961–1990), by +5% to +10% under the SRES emissions scenarios and from +8% to +51% with prescribed increases in global mean air temperature of between 1 and 6° C. Substantial uncertainty in projected changes to mean river discharge (−28% to +13%) under the 2° C warming scenario is, however, associated with the choice of GCM. We conclude that, in the case of Rio Grande Basin, the most important source of uncertainty derives from the GCM rather than the emission scenario or the magnitude of rise in mean global temperature.
Highlights
The well-being of human societies is closely associated with climate and thereby influenced by climate variability
Model results when meteorological inputs from different Global Circulation Models (GCM) (CCCMA, CSIRO, ECHAM, IPSL, HadCM3, HadGEM1) for the A1b emission scenario are compared with those results obtained by running the hydrological model with the detrended baseline (Table 5)
Uncertainty in the impact of climate change on the discharge of Rio Grande, one of the most important rivers in Brazil for hydro-electric power generation, was assessed in terms of (1) GCM structure using a priority subset of six Coupled Model Intercomparison Project phase 3 (CMIP3)/IPCC-AR4 GCMs, (2) emission scenarios, which are commonly adopted according to the IPCC Special Report on Emission Scenarios, and are called A1B, A2, B1 and B2, and prescribed increases in global mean air temperature of 1 ◦C to 6 ◦C
Summary
The well-being of human societies is closely associated with climate and thereby influenced by climate variability. Tomasella et al (2008) analysed the impacts of climate change on the discharge of the rivers Araguaia and Tocantins that flow from central to northern Brazil They used the MGB-IPH hydrological model (Collischonn et al, 2007a) driven by climate projections from one GCM (HadCM3). Most analyses of climate change impacts on river discharge in South America have, to date, relied upon climate projections from a single GCM The results of these assessments should be viewed with caution since the uncertainty associated with model (GCM) structure is not considered. We estimate climate change impacts on stream flow in the Rio Grande Basin of South America through the application of a range of climate scenarios to a large-scale distributed hydrological model (MGB-IPH) (Collischonn et al, 2007a). The range of applied climate scenarios enables the quantification of uncertainty between different GCMs, emission scenarios (A1b, A2, B1, B2) and prescribed increases in global mean air temperature (1 to 6 ◦C), including the 2 ◦C threshold of “dangerous” climate change (Todd et al, 2010)
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