Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil

Nóbrega, M. T.; Collischonn, Walter; Tucci, Carlos Eduardo Morelli; Paz, Adriano Rolim da

doi:10.5194/hessd-7-6099-2010

Cited by 6 publications

(7 citation statements)

References 21 publications

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“…Furthermore, the nature of the response of runoff to climate change is complex and the common use of mean annual runoff as a measure of the response of hydrological systems to climate change is over-simplistic. The analysis presented here and by others (Nóbrega et al, 2010Hughes et al, 2010Arnell, 2010;Xu et al, 2010) shows that mean annual runoff can mask considerably greater seasonal variations which are of fundamental importance to water management and our understanding of freshwater availability.…”

Section: Discussionmentioning

confidence: 50%

“…Whilst one should be cautious with results based on projections from a single GCM because mistaken management decisions may follow (Nóbrega et al, 2010), decision-makers are faced with a challenging prospect when approached with a range of projections from several GCMs that are different in sign. In the case of the Liard, where 6 of 7 GCMs suggest very little change or an increase in runoff with climate change, the GCM that suggests a decrease in annual runoff may arguably be considered as an outlier .…”

Section: Discussionmentioning

confidence: 99%

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A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Gosling

Taylor

Arnell

et al. 2011

Hydrol. Earth Syst. Sci.

225

124

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Abstract. We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in globalmean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 • C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 • C relative to baseline for seven GCMs to explore response to climate model structural uncertainty.We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absoluteCorrespondence to: S. N. Gosling (simon.gosling@nottingham.ac.uk) GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 • C warming of up to 25%), and they are generally larger for indicators of high and low monthly runoff. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are represented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs. This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM (Mac-PDM.09 here) as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find however, that for some catchments there are differences between GHMs and CHMs in mean ann...

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Section: Discussionmentioning

confidence: 50%

Section: Discussionmentioning

confidence: 99%

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Gosling

Taylor

Arnell

et al. 2011

Hydrol. Earth Syst. Sci.

225

124

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“…Modelling of baseline and projected river discharge consequently do not consider changes in land-use and it as acknowledged that some disparities between simulated and observed discharge may be attributable to landuse change during the simulation period. (Mitchell and Jones, 2005), which included monthly precipitation total and monthly average as well as maximum and minimum air temperatures.…”

Section: Available Datamentioning

confidence: 99%

“…After considering land use and soil characteristics, the River Xiangxi catchment was divided into 195 HRUs and River Huangfuchuan was divided into 314 HRUs. Potential evapotranspiration was calculated using the Hargreaves function (Hargreaves et al, 1985); surface runoff was estimated by a modification of the SCS curve number method (USDA-NRCS, 2004), and routing processes were estimated by the Muskingum method (Neitsch et al, 2005). The employed SWAT model had recently been calibrated and validated for the River Xiangxi using monthly river discharge observations for the periods 1970-1974and 1976-1986(Xu et al, 2010.…”

Section: Calibration and Validation Of Hydrological Modelmentioning

confidence: 99%

“…The hydrological model used here is Soil and Water Assessment Tool (SWAT) model, which is a physically based semi-distributed hydrological model that operates on a daily time step. Baseline climate that derives from detrended monthly CRU TS3.0 datasets (Mitchell and Jones, 2005) for the period during 1961-2005, were used for calibrating and validating the SWAT model. We quantify uncertainty in projections of climate change on river discharge by applying a range of climate scenarios using different GCMs (subset of IPCC AR4 GCMs), emission scenarios (SRES 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 .…”

Section: Introductionmentioning

confidence: 99%

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Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the Yangtze and Yellow River Basins, China

Taylor

2011

Hydrol. Earth Syst. Sci.

106

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Abstract. Quantitative evaluations of the impacts of climate change on water resources are primarily constrained by uncertainty in climate projections from GCMs. In this study we assess uncertainty in the impacts of climate change on river discharge in two catchments of the Yangtze and Yellow River Basins that feature contrasting climate regimes (humid and semi-arid). Specifically we quantify uncertainty associated with GCM structure from a subset of CMIP3 AR4 GCMs (HadCM3, HadGEM1, CCSM3.0, IPSL, ECHAM5, CSIRO, CGCM3.1), SRES emissions scenarios (A1B, A2, B1, B2) and prescribed increases in global mean air temperature (1 • C to 6 • C). Climate projections, applied to semi-distributed hydrological models (SWAT 2005) in both catchments, indicate trends toward warmer and wetter conditions. For prescribed warming scenarios of 1 • C to 6 • C, linear increases in mean annual river discharge, relative to baseline , for the River Xiangxi and River Huangfuchuan are +9% and 11% per +1 • C respectively. Intra-annual changes include increases in flood (Q05) discharges for both rivers as well as a shift in the timing of flood discharges from summer to autumn and a rise (24 to 93%) in dry season (Q95) discharge for the River Xiangxi. Differences in projections of mean annual river discharge between SRES emission scenarios using HadCM3 are comparatively minor for the River Xiangxi (13 to 17% rise from baseline) but substantial (73 to 121%) for the River Huangfuchuan. With one minor exception of a slight (−2%) decrease in river discharge projected using HadGEM1 for the River Xiangxi, mean annual river Correspondence to: H. Xu (xuhm@cma.gov.cn) discharge is projected to increase in both catchments under both the SRES A1B emission scenario and 2 • rise in global mean air temperature using all AR4 GCMs on the CMIP3 subset. For the River Xiangxi, there is substantial uncertainty associated with GCM structure in the magnitude of the rise in flood (Q05) discharges (−1 to 41% under SRES A1B and −3 to 41% under 2 • global warming) and dry season (Q95) discharges (2 to 55% under SRES A1B and 2 to 39% under 2 • global warming). For the River Huangfuchuan, all GCMs project a rise in the Q05 flow but there is substantial uncertainty in the magnitude of this rise (7 to 70% under SRES A1B and 2 to 57% under 2 • global warming). Differences in the projected hydrological changes are associated with GCM structure in both catchments exceed uncertainty in emission scenarios. Critically, estimated uncertainty in projections of mean annual flows is less than that calculated for extreme (Q05, Q95) flows. The common approach of reporting of climate change impacts on river in terms of mean annual flows masks the magnitude of uncertainty in flows that are of most importance to water management.

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Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the River Yangtze and Yellow Basins, China

Xu¹,

Taylor²,

Xu³

2010

Preprint

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Quantitative evaluations of the impacts of climate change on water resources are primarily constrained by uncertainty in climate projections from GCMs. In this study we assess uncertainty in the impacts of climate change on river discharge in two catchments of the River Yangtze and Yellow Basins that feature contrasting climate regimes (humid and semi-arid). Specifically we quantify uncertainty associated with GCM structure from a subset of CMIP3 AR4 GCMs (HadCM3, HadGEM1, CCSM3.0, IPSL, ECHAM5, CSIRO, CGCM3.1), SRES emissions scenarios (A1B, A2, B1, B2) and prescribed increases in global mean air temperature (1 °C to 6 °C). Climate projections, applied to semi-distributed hydrological models (SWAT 2005) in both catchments, indicate trends toward warmer and wetter conditions. For prescribed warming scenarios of 1 °C to 6 °C, linear increases in mean annual river discharge, relative to baseline (1961–1990), for the River Xiangxi and River Huangfuchuan are +9% and 11% per +1 °C, respectively. Intra-annual changes include increases in flood (Q05) discharges for both rivers as well as a shift in the timing of flood discharges from summer to autumn and a rise (24 to 93%) in dry season (Q95) discharge for the River Xiangxi. Differences in projections of mean annual river discharge between SRES emission scenarios using HadCM3 are comparatively minor for the River Xiangxi (13% to 17% rise from baseline) but substantial (73% to 121%) for the River Huangfuchuan. With one minor exception of a slight (−2%) decrease in river discharge projected using HadGEM1 for the River Xiangxi, mean annual river discharge is projected to increase in both catchments under both the SRES A1B emission scenario and 2° rise in global mean air temperature using all AR4 GCMs on the CMIP3 subset. For the River Xiangxi, there is great uncertainty associated with GCM structure in the magnitude of the rise in flood (Q05) discharges (−1% to 41% under SRES A1B and −3% to 41% under 2° global warming) and dry season (Q95) discharges (2% to 55% under SRES A1B and 2% to 39% under 2° global warming). For the River Huangfuchuan, all GCMs project a rise in the Q05 flow but there is substantial uncertainty in the magnitude of this rise (7% to 70% under SRES A1B and 2% to 57% under 2° global warming). Greatest differences in the projected hydrologic changes are associated with GCMs in both catchments than emission scenarios and climate sensitivity. Critically, estimated uncertainty in projections of mean annual flows is less than that calculated for extreme (Q05, Q95) flows. This research suggest that the common approach of reporting of climate change impacts on river in terms of mean annual flows may mask the magnitude of uncertainty in flows of most importance to water managers

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Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil

Cited by 6 publications

References 21 publications

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the Yangtze and Yellow River Basins, China

Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the River Yangtze and Yellow Basins, China

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