Editorial Type:
Article
Article Type:
Research Article

Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

Jin Teng Water for a Healthy Country National Research Flagship, CSIRO Land and Water, Canberra, Australian Capital Territory, Australia

Search for other papers by Jin Teng in
Current site
Google Scholar
PubMed Close
,
Jai Vaze Water for a Healthy Country National Research Flagship, CSIRO Land and Water, Canberra, Australian Capital Territory, Australia

Search for other papers by Jai Vaze in
Current site
Google Scholar
PubMed Close
,
Francis H. S. Chiew Water for a Healthy Country National Research Flagship, CSIRO Land and Water, Canberra, Australian Capital Territory, Australia

Search for other papers by Francis H. S. Chiew in
Current site
Google Scholar
PubMed Close
,
Biao Wang Water for a Healthy Country National Research Flagship, CSIRO Land and Water, Canberra, Australian Capital Territory, Australia

Search for other papers by Biao Wang in
Current site
Google Scholar
PubMed Close
, and
Jean-Michel Perraud Water for a Healthy Country National Research Flagship, CSIRO Land and Water, Canberra, Australian Capital Territory, Australia

Search for other papers by Jean-Michel Perraud in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Feb 2012
DOI:
https://doi.org/10.1175/JHM-D-11-058.1
Page(s):
122–139
Restricted access

Abstract

This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.

Corresponding author address: Jin Teng, CSIRO Land and Water, GPO Box 1666, Canberra ACT 2601, Australia. E-mail: jin.teng@csiro.au.

Abstract

This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.

Corresponding author address: Jin Teng, CSIRO Land and Water, GPO Box 1666, Canberra ACT 2601, Australia. E-mail: jin.teng@csiro.au.
Save
Cover Journal of Hydrometeorology
Journal of Hydrometeorology

  • Boughton, W., 2004: The Australian water balance model. Environ. Modell. Software, 19, 943–956, doi:10.1016/j.envsoft.2003.10.007.

  • Boughton, W., and Chiew F. H. S. , 2007: Estimating runoff in ungauged catchments from rainfall, PET and the AWBM model. Environ. Modell. Software, 22, 476–487, doi:10.1016/j.envsoft.2006.01.009.

    • Search Google Scholar
    • Export Citation

  • Burnash, R. J. C., Ferral R. L. , and McGuire R. A. , 1973: A generalized streamflow simulation system—Conceptual modeling for digital computers. Joint Federal and State River Forecast Center Tech. Rep., 204 pp.

    • Search Google Scholar
    • Export Citation

  • Chiew, F. H. S., 2006: Estimation of rainfall elasticity of streamflow in Australia. Hydrol. Sci. J., 51, 613–625, doi:10.1623/hysj.51.4.613.

    • Search Google Scholar
    • Export Citation

  • Chiew, F. H. S., and McMahon T. A. , 1991: The applicability of Morton’s and Penman’s evapotranspiration estimates in rainfall–runoff modeling. Water Resour. Bull., 27, 611–620.

    • Search Google Scholar
    • Export Citation

  • Chiew, F. H. S., Peel M. C. , and Western A. W. , 2002: Application and testing of the simple rainfall–runoff model SIMHYD. Mathematical Models of Small Watershed Hydrology and Applications, V. P. Singh and D. K. Frevert, Eds., Water Resources Publications, 335–367.

    • Search Google Scholar
    • Export Citation

  • Chiew, F. H. S., Teng J. , Vaze J. , Post D. A. , Perraud J. M. , Kirono D. G. C. , and Viney N. R. , 2009: Estimating climate change impact on runoff across southeast Australia: Method, results, and implications of the modeling method. Water Resour. Res., 45, W10414, doi:10.1029/2008wr007338.

    • Search Google Scholar
    • Export Citation

  • Chiew, F. H. S., Kirono D. G. C. , Kent D. M. , Frost A. J. , Charles S. P. , Timbal B. , Nguyen K. C. , and Fu G. , 2010: Comparison of runoff modelled using rainfall from different downscaling methods for historical and future climates. J. Hydrol., 387, 10–23, doi:10.1016/j.jhydrol.2010.03.025.

    • Search Google Scholar
    • Export Citation

  • Cleugh, H., Smith M. S. , Battaglia M. , and Graham P. , Eds., 2011: Climate Change: Science and Solutions for Australia. CSIRO Publishing, 155 pp.

    • Search Google Scholar
    • Export Citation

  • Croke, B. F. W., Andrews F. , Jakeman A. J. , Cuddy S. M. , and Luddy A. , 2006: IHACRES Classic Plus: A redesign of the IHACRES rainfall–runoff model. Environ. Modell. Software, 21, 426–427, doi:10.1016/j.envsoft.2005.07.003.

    • Search Google Scholar
    • Export Citation

  • CSIRO and Australian Bureau of Meteorology, 2007: Climate Change in Australia. Australian Commonwealth Scientific and Industrial Research Organisation and Australian Bureau of Meteorology Tech. Rep., 148 pp. [Availible online at www.climatechangeinaustralia.gov.au.]

    • Search Google Scholar
    • Export Citation

  • Dibike, Y. B., and Coulibaly P. , 2007: Validation of hydrological models for climate scenario simulation: The case of Saguenay watershed in Quebec. Hydrol. Processes, 21, 3123–3135, doi:10.1002/hyp.6534.

    • Search Google Scholar
    • Export Citation

  • Duan, Q. Y., Gupta V. K. , and Sorooshian S. , 1993: Shuffled complex evolution approach for effective and efficient global minimization. J. Optim. Theory Appl., 76, 501–521.

    • Search Google Scholar
    • Export Citation

  • Fowler, H. J., Blenkinsop S. , and Tebaldi C. , 2007a: Linking climate change modelling to impacts studies: Recent advances in downscaling techniques for hydrological modelling. Int. J. Climatol., 27, 1547–1578, doi:10.1002/joc.1556.

    • Search Google Scholar
    • Export Citation

  • Fowler, H. J., Kilsby C. G. , and Stunell J. , 2007b: Modelling the impacts of projected future climate change on water resources in north-west England. Hydrol. Earth Syst. Sci., 11, 1115–1126.

    • Search Google Scholar
    • Export Citation

  • Gan, T. Y., and Burges S. J. , 2006: Assessment of soil-based and calibrated parameters of the Sacramento model and parameter transferability. J. Hydrol., 320, 117–131, doi:10.1016/j.jhydrol.2005.07.008.

    • Search Google Scholar
    • Export Citation

  • Harrold, T. I., and Jones R. N. , 2003: Generation of rainfall scenarios using daily patterns of change from GCMs. Water Resources Systems—Water Availability and Global Change, S. Franks et al., Eds., IAHS Press, 165–172.

    • Search Google Scholar
    • Export Citation

  • Jeffrey, S. J., Carter J. O. , Moodie K. B. , and Beswick A. R. , 2001: Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environ. Modell. Software, 16, 309–330.

    • Search Google Scholar
    • Export Citation

  • Jiang, T., Chen Y. Q. D. , Xu C. Y. Y. , Chen X. H. , Chen X. , and Singh V. P. , 2007: Comparison of hydrological impacts of climate change simulated by six hydrological models in the Dongjiang basin, South China. J. Hydrol., 336, 316–333, doi:10.1016/j.jhydrol.2007.01.010.

    • Search Google Scholar
    • Export Citation

  • Jones, R. N., Chiew F. H. S. , Boughton W. C. , and Zhang L. , 2006: Estimating the sensitivity of mean annual runoff to climate change using selected hydrological models. Adv. Water Resour., 29, 1419–1429, doi:10.1016/j.advwatres.2005.11.001.

    • Search Google Scholar
    • Export Citation

  • 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, 92, 41–63, doi:10.1007/s10584-008-9471-4.

    • Search Google Scholar
    • Export Citation

  • Knutti, R., Furrer R. , Tebaldi C. , Cermak J. , and Meehl G. A. , 2010: Challenges in combining projections from multiple climate models. J. Climate, 23, 2739–2758.

    • Search Google Scholar
    • Export Citation

  • Maurer, E. P., and Duffy P. B. , 2005: Uncertainty in projections of streamflow changes due to climate change in California. Geophys. Res. Lett., 32, L03704, doi:10.1029/2004gl021462.

    • Search Google Scholar
    • Export Citation

  • McMahon, T. A., and Finlayson B. L. , 2003: Droughts and anti-droughts: The low flow hydrology of Australian rivers. Freshwater Biol., 48, 1147–1160.

    • Search Google Scholar
    • Export Citation

  • Milly, P. C. D., Betancourt J. , Falkenmark M. , Hirsch R. M. , Kundzewicz Z. W. , Lettenmaier D. P. , and Stouffer R. J. , 2008: Stationarity is dead: Whither water management? Science, 319, 573–574, doi:10.1126/science.1151915.

    • Search Google Scholar
    • Export Citation

  • Mitchell, T. D., 2003: Pattern scaling—An examination of the accuracy of the technique for describing future climates. Climatic Change, 60, 217–242.

    • Search Google Scholar
    • Export Citation

  • Morton, F. I., 1983: Operational estimates of areal evapotranspiration and their significance to the science and practice of hydrology. J. Hydrol., 66, 1–76.

    • Search Google Scholar
    • Export Citation

  • Mote, P., Brekke L. , Duffy P. B. , and Maurer E. P. , 2011: Guidelines for constructing climate scenarios. Eos, Trans. Amer. Geophys. Union, 92, 257–258.

    • Search Google Scholar
    • Export Citation

  • Mpelasoka, F. S., and Chiew F. H. S. , 2009: Influence of rainfall scenario construction methods on runoff projections. J. Hydrometeor., 10, 1168–1183.

    • Search Google Scholar
    • Export Citation

  • Nash, J. E., and Sutcliffe J. V. , 1970: River flow forecasting through conceptual models part I—A discussion of principles. J. Hydrol., 10, 282–290.

    • Search Google Scholar
    • Export Citation

  • Nyenje, P. M., and Batelaan O. , 2009: Estimating the effects of climate change on groundwater recharge and baseflow in the upper Ssezibwa catchment, Uganda. Hydrol. Sci. J., 54, 713–726.

    • Search Google Scholar
    • Export Citation

  • Oudin, L., Andréassian V. , Perrin C. , Michel C. , and Le Moine N. , 2008: Spatial proximity, physical similarity, regression and ungaged catchments: A comparison of regionalization approaches based on 913 French catchments. Water Resour. Res., 44, W03413, doi:10.1029/2007wr006240.

    • Search Google Scholar
    • Export Citation

  • Perkins, S. E., Pitman A. J. , Holbrook N. J. , and McAneney J. , 2007: Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. J. Climate, 20, 4356–4376.

    • Search Google Scholar
    • Export Citation

  • Post, D. A., Jakeman A. J. , Littlewood I. G. , Whitehead P. G. , and Jayasuriya M. D. A. , 1996: Modelling land-cover-induced variations in hydrologic response: Picaninny Creek, Victoria. Ecol. Modell., 86, 177–182, doi:10.1016/0304-3800(95)00048-8.

    • Search Google Scholar
    • Export Citation

  • 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, 93, 197–222, doi:10.1007/s10584-008-9461-6.

    • Search Google Scholar
    • Export Citation

  • Prudhomme, C., Reynard N. , and Crooks S. , 2002: Downscaling of global climate models for flood frequency analysis: Where are we now? Hydrol. Processes, 16, 1137–1150, doi:10.1002/hyp.1054.

    • Search Google Scholar
    • Export Citation

  • Quintana Segui, P., Ribes A. , Martin E. , Habets F. , and Boé J. , 2010: Comparison of three downscaling methods in simulating the impact of climate change on the hydrology of Mediterranean basins. J. Hydrol., 383, 111–124, doi:10.1016/j.jhydrol.2009.09.050.

    • Search Google Scholar
    • Export Citation

  • Reichl, J. P. C., Western A. W. , McIntyre N. R. , and Chiew F. H. S. , 2009: Optimization of a similarity measure for estimating ungauged streamflow. Water Resour. Res., 45, W10423, doi:10.1029/2008wr007248.

    • Search Google Scholar
    • Export Citation

  • Rosenbrock, H. H., 1960: An automatic method for finding the greatest or least value of a function. Comput. J., 3, 175–184.

  • Sankarasubramanian, A., Vogel R. M. , and Limbrunner J. F. , 2001: Climate elasticity of streamflow in the United States. Water Resour. Res., 37, 1771–1781.

    • Search Google Scholar
    • Export Citation

  • Schaake, J. C., 1990: From climate to flow. Climate Change and U.S. Water Resources, P. E. Waggoner, Ed., Wiley-Interscience, 177–206.

    • Search Google Scholar
    • Export Citation

  • Smakhtin, V. U., 2001: Low flow hydrology: A review. J. Hydrol., 240, 147–186.

  • Smith, I., and Chandler E. , 2010: Refining rainfall projections for the Murray Darling Basin of south-east Australia—The effect of sampling model results based on performance. Climatic Change, 102, 377–393, doi:10.1007/s10584-009-9757-1.

    • Search Google Scholar
    • Export Citation

  • Solomon, S., Qin D. , Manning M. , Marquis M. , Averyt K. , Tignor M. M. B. , Miller H. L. Jr., and Chen Z. , Eds., 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.

    • Search Google Scholar
    • Export Citation

  • Suppiah, R., Hennessy K. , Whetton P. H. , McInnes K. , Macadam I. , Bathols J. , Ricketts J. , and Page C. M. , 2007: Australian climate change projections derived from simulations performed for the IPCC 4th Assessment Report. Aust. Meteor. Mag., 56, 131–152.

    • Search Google Scholar
    • Export Citation

  • Tuteja, N. K., Vaze J. , Teng J. , and Mutendeudzi M. , 2007: Partitioning the effects of pine plantations and climate variability on runoff from a large catchment in southeastern Australia. Water Resour. Res., 43, W08415, doi:10.1029/2006wr005016.

    • Search Google Scholar
    • Export Citation

  • van Roosmalen, L., Christensen J. H. , Butts M. B. , Jensen K. H. , and Refsgaard J. C. , 2010: An intercomparison of regional climate model data for hydrological impact studies in Denmark. J. Hydrol., 380, 406–419, doi:10.1016/j.jhydrol.2009.11.014.

    • Search Google Scholar
    • Export Citation

  • Vaze, J., and Teng J. , 2011: Future climate and runoff projections across New South Wales, Australia: Results and practical applications. Hydrol. Processes, 25, 18–35, doi:10.1002/hyp.7812.

    • Search Google Scholar
    • Export Citation

  • Vaze, J., and Coauthors, 2004: Modelling the effects of land-use change on water and salt delivery from a catchment affected by dryland salinity in south-east Australia. Hydrol. Processes, 18, 1613–1637, doi:10.1002/hyp.1409.

    • Search Google Scholar
    • Export Citation

  • Vaze, J., Post D. A. , Chiew F. H. S. , Perraud J.-M. , Viney N. R. , and Teng J. , 2010: Climate non-stationarity—Validity of calibrated rainfall–runoff models for use in climate change studies. J. Hydrol., 394, 447–457, doi:10.1016/j.jhydrol.2010.09.018.

    • Search Google Scholar
    • Export Citation

  • Vaze, J., and Coauthors, 2011a: Rainfall–runoff modelling across southeast Australia: Datasets, models and results. Aust. J. Water Resour., 14, 101–116.

    • Search Google Scholar
    • Export Citation

  • Vaze, J., Davidson A. , Teng J. , and Podger G. , 2011b: Impact of climate change on water availability in the Macquarie-Castlereagh River Basin in Australia. Hydrol. Processes, 25, 2597–2612, doi:10.1002/hyp.8030.

    • Search Google Scholar
    • Export Citation

  • Vaze, J., Teng J. , and Chiew F. H. S. , 2011c: Assessment of GCM simulations of annual and seasonal rainfall and daily rainfall distribution across south-east Australia. Hydrol. Processes, 25, 1486–1497, doi:10.1002/hyp.7916.

    • Search Google Scholar
    • Export Citation

  • Viney, N. R., Perraud J.-M. , Vaze J. , Chiew F. H. S. , Post D. A. , and Yang A. , 2009: The usefulness of bias constraints in model calibration for regionalisation to ungauged catchments. Proc. 18th World IMACS Congress and MODSIM09 Int. Congress on Modelling and Simulation, Cairns, QLD, Australia, Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, 3421–3427.

    • Search Google Scholar
    • Export Citation

  • Watterson, I. G., 2008: Calculation of probability density functions for temperature and precipitation change under global warming. J. Geophys. Res., 113, D12106, doi:10.1029/2007jd009254.

    • Search Google Scholar
    • Export Citation

  • Wigley, T. M. L., and Jones P. D. , 1985: Influences of precipitation changes and direct CO2 effects on streamflow. Nature, 314, 149–152.

    • Search Google Scholar
    • Export Citation

  • Wilby, R. L., 2005: Uncertainty in water resource model parameters used for climate change impact assessment. Hydrol. Processes, 19, 3201–3219, doi:10.1002/hyp.5819.

    • Search Google Scholar
    • Export Citation

  • Wilby, R. L., and Wigley T. M. L. , 1997: Downscaling general circulation model output: A review of methods and limitations. Prog. Phys. Geogr., 21, 530–548.

    • Search Google Scholar
    • Export Citation

  • Wilby, R. L., and Harris I. , 2006: A framework for assessing uncertainties in climate change impacts: Low-flow scenarios for the River Thames, UK. Water Resour. Res., 42, W02419, doi:10.1029/2005wr004065.

    • Search Google Scholar
    • Export Citation

  • Zhang, Y. Q., and Chiew F. H. S. , 2009: Relative merits of different methods for runoff predictions in ungauged catchments. Water Resour. Res., 45, W07412, doi:10.1029/2008wr007504.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1759 455 30
PDF Downloads 1240 273 22