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Simulated Climate Change Impacts on Streamflow in Vietnam's Be River Catchment

Reference
Khoi, D.N. and Suetsugi, T. 2012. Uncertainty in climate change impacts on streamflow in Be River Catchment, Vietnam. Water and Environment Journal 26: 530-539.
In the words of Khoi and Suetsugi (2012), "many general circulation models (GCMs) consistently predict increases in frequency and magnitudes of extreme climate events and variability of precipitation (IPCC, 2007)," noting that "this will affect terrestrial water resources in the future, perhaps severely (Srikanthan and McMahon, 2001; Xu and Singh, 2004; Chen et al., 2011)." And, therefore, they conducted a study to see what aspect of the climate modeling enterprise led to the greatest degree of uncertainty in predicting rates of streamflow in Vietnam's Be River Catchment. In so doing, the climate scenarios investigated by Khoi and Suetsugi were generated from seven different CMIP3 GCMs - CCCMA CGCM3.1, CSIRO Mk30, IPSL CM4, MPI ECHAM5, NCAR CCSM3.0, UKMO HadGEM1, UKMO Had CM3 - using SRES emission scenarios A1B, A2, B1 and B2, along with prescribed increases in global mean temperature ranging from 0.5 to 6°C.

At the conclusion of their study, the two Vietnamese researchers report finding that "the greatest source of uncertainty in impact of climate change on streamflow is GCM structure (choice of GCM)." And they say that this result "is in accordance with findings of other authors who also suggest that the choice of the GCM is the largest source of uncertainty in hydrological projection," citing Kingston and Taylor (2010), Kingston et al. (2011), Nobrega et al. (2011), Thorne (2011) and Xu et al. (2011)," adding that the range of uncertainty could increase even further if the analysis employed a larger number of GCMs.

In the concluding words of Khoi and Suetsugi, their findings (and those of many others) indicate that "single GCM or GCMs ensemble mean evaluations of climate change impact are unlikely to provide a representative depiction of possible future changes in streamflow." And that is saying a lot!

Additional References
Chen, J., Brissette, F.P. and Leconte, R. 2011. Uncertainty of downscaling method in quantifying the impact of climate change on hydrology. Journal of Hydrology 401: 190-202.

Intergovernmental Panel on Climate Change (IPCC). 2007. Climate Change. Fourth Assessment Report.

Kingston, D.G. and Taylor, R.G. 2010. Sources of uncertainty in climate change impacts on river discharge and groundwater in a headwater catchment of the Upper Nile Basin, Uganda. Hydrology and Earth System Sciences 14: 1297-1308.

Kingston, D.G., Thompson, J.R. and Kite, G. 2011. Uncertainty in climate change projections of discharge for Mekong River Basin. Hydrology and Earth System Sciences 15: 1459-1471.

Nobrega, M.T., Collischonn, W., Tucci, C.E.M. and Paz, A.R. 2011. Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil. Hydrology and Earth System Sciences 15: 585-595.

Srikanthan, R. and McMahon, T.A. 2001. Stochastic generation of annual, monthly and daily climate data: A review. Hydrology and Earth System Sciences 5: 653-670.

Thorne, R. 2011. Uncertainty in the impacts of projected climate change on the hydrology of a subarctic environment: Laird River Basin. Hydrology and Earth System Sciences 15: 1483-1492.

Xu, C.Y. and Singh, V.P. 2004. Review on regional water resources assessment models under stationary and changing climate. Water Resources Management 18: 591-612.

Xu, H., Taylor, R.G. and Xu, Y. 2011. Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the Yangtze and Yellow River Basins, China. Hydrology and Earth System Sciences 15: 333-344.

Archived 26 March 2013