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http://dx.doi.org/10.3741/JKWRA.2016.49.8.657

Development of climate change uncertainty assessment method for projecting the water resources  

Lee, Moon-Hwan (Dept. of Civil and Environmental Engrg., Sejong University)
So, Jae-Min (Dept. of Civil and Environmental Engrg., Sejong University)
Bae, Deg-Hyo (Dept. of Civil and Environmental Engrg., Sejong University)
Publication Information
Journal of Korea Water Resources Association / v.49, no.8, 2016 , pp. 657-671 More about this Journal
Abstract
It is expected that water resources will be changed spatially and temporally due to the global climate change. The quantitative assessment of change in water availability and appropriate water resources management measures are needed for corresponding adaptation. However, there are large uncertainties in climate change impact assessment on water resources. For this reason, development of technology to evaluate the uncertainties quantitatively is required. The objectives of this study are to develop the climate change uncertainty assessment method and to apply it. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods (SPP) and 2 hydrological models (HYM) were applied for evaluation. The results of the uncertainty analysis showed that the RCM was the largest sources of uncertainty in Spring, Summer, Autumn (29.3~68.9%), the hydrological model was the largest source of uncertainty in Winter (46.5%). This method can be possible to analyze the changes in the total uncertainty according to the specific RCM, SPP, HYM model. And then it is expected to provide the method to reduce the total uncertainty.
Keywords
Climate Change; Uncertainty Assessment; Water Resources; Variance Analysis;
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1 Bae, D.H., Jung, I.W., and Chang, H. (2008). "Potential changes in Korean water resources estimated by high-resolution climate simulation." Climate Research, Vol. 35, pp. 213-226.   DOI
2 Bae, D.H., Jung, I.W., and Lettenmaier, D.P. (2011). "Hydrologic uncertainties in climate change from IPCC AR4 GCM simulations of the Chungju basin, Korea." Journal of Hydrology, Vol. 401, pp. 90-105.   DOI
3 Beven, K.J., and Freer, J. (2001) "Equifinality, data assimilation, and uncertainty estimation in mechanistic modeling of complex environmental systems using the GLUE methodology." Journal of Hydrology, Vol. 249, pp. 11-29.   DOI
4 Chen, J., Brissette, F.P., and Leconte, R. (2011). "Uncertainty of dowscaling method in quantifying the impact of climate change on hydrology." Journal of Hydrology, Vol. 401, pp. 190-202.   DOI
5 Fisher, R.A. (1925). "Statistical methods for research workers." Classics in the history of phychology.
6 IPCC (2001). Climate change 2001: The Scientific basis, IPCC Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambrige University Press, Cambridge.
7 IPCC (2013). Climate change 2013: The Physical Scientific basis, IPCC Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambrige University Press, Cambridge.
8 Kay, A.L., Davies, H.N., Bell, V.A., and Jones, R.G. (2009). "Comparison of uncertainty sources for climate change impacts: flood frequency in England." Climatic Change, Vol. 92, pp. 41-63.   DOI
9 KMA (2010). Assessment of uncertainties in regional climate models and prediction of detailed regional climate change over Korea, RACS 2010-2602.
10 Lee, M.H., and Bae, D.H. (2013). "Evaluation of hybrid downscaling method combined regional climate model with Step-wise Scaling method." Journal of Korea Water Resources Association, KWRA, Vol. 46, No. 6, pp. 585-596.   DOI
11 Lee, M.H. (2016). "Development and application of climate change uncertainty assessment method on water availability." Ph. D thesis, Sejong University.
12 Lee, M.H., and Bae, D.H. (2015). "Climate change impact assessment on green and blue water over Asian monsoon region." Water Resources Management, Vol. 29, pp. 2407-2427.   DOI
13 Liang, X., Lettenmainer, D.P., Wood, E.F., and Burges, S.J. (1994). "A simple hydrologically based model of land surface water and energy fluxes for General Circulation Models." Journal of Geophysical Research, Vol. 99, pp. 14415-14428.   DOI
14 Liang, X., Wood, E.F., and Lettenmaier, D.P. (1996). "Surface soil moisture parameterization of the VIC-2L model: Evaluation and modifications." Global and Planetary Change, Vol. 13, pp. 195-206.   DOI
15 Prudhomme, C., and Davies, H. (2009). "Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 2: Future climate." Climatic Change, Vol. 93, pp. 197-222.   DOI
16 Sloan, P.G., and Moore. I.D. (1984). "Modeling subsurface stormflow on steeply sloping forested watersheds." Water Resources Research, Vol. 20, No. 12, pp. 1815-1822.   DOI
17 Son (2015). "Enhancement of hydrological drought outlook accuracy using Bayesian method and their real-time prediction applicability." Ph. D. thesis, Sejong Unversity.
18 Xu, H., Taylor, R.G., and Xu, Y. (2011). "Quantifying uncertainty in the impacts of climate change on river discharge in subcatchments of the Yangtze and Yellow river basin, China." Hydrology and Earth System Sciences, Vol. 15, pp. 333-344.   DOI
19 Steinschneider, S., Polebitski, A., Brown, C., Letcher, B.H. (2012). "Toward a statistical framework to quantify the uncertainties of hydrologic response under climate change." Water Resources Research, Vol. 48, W11525.
20 Wilby, R.L., and Harris, I. (2006). "A framework for assessing uncertainties in climate change impacts: Low-flow scenarios for the River Thames, U.K.." Water Resources Research, Vol. 42, W02419.