Influence of Rainfall Scenario Construction Methods on Runoff Projections

Freddie S. Mpelasoka CSIRO Land and Water, Canberra, Australian Capital Territory, Australia

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Francis H. S. Chiew CSIRO Land and Water, Canberra, Australian Capital Territory, Australia

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Abstract

The future rainfall series used to drive hydrological models in most climate change impact studies is informed by global climate models (GCMs). This paper compares future runoff projections in ∼11 000 0.25° grid cells across Australia from a daily rainfall–runoff model driven with future daily rainfall series obtained using three simple scaling methods, informed by 14 GCMs. In the constant scaling and daily scaling methods, the historical daily rainfall series is scaled by the relative difference between GCM simulations for the future and historical climates. The constant scaling method scales all the daily rainfall by the same factor, and the daily scaling method takes into account changes in the daily rainfall distribution by scaling the different daily rainfall amounts differently. In the daily translation method, the GCM future daily rainfall series is translated to a 0.25° gridcell rainfall series using the relationship established between the historical GCM-scale rainfall and 0.25° gridcell rainfall data. The daily scaling and daily translation methods generally give higher extreme and annual runoff than the constant scaling method because they take into account the increase in extreme daily rainfall (which generates significant runoff) simulated by the large majority of the GCMs. However, the difference between the mean annual runoff simulated with future daily rainfall series obtained using the constant versus daily scaling methods is generally less than 5%, which is relatively smaller than the range of runoff results from the different GCMs of 30%–40%.

Corresponding author address: Freddie Mpelasoka, CSIRO Land and Water, Black Mountain Laboratories, GPO Box 1666, Canberra, ACT 2601, Australia. Email: freddie.mpelasoka@csiro.au

Abstract

The future rainfall series used to drive hydrological models in most climate change impact studies is informed by global climate models (GCMs). This paper compares future runoff projections in ∼11 000 0.25° grid cells across Australia from a daily rainfall–runoff model driven with future daily rainfall series obtained using three simple scaling methods, informed by 14 GCMs. In the constant scaling and daily scaling methods, the historical daily rainfall series is scaled by the relative difference between GCM simulations for the future and historical climates. The constant scaling method scales all the daily rainfall by the same factor, and the daily scaling method takes into account changes in the daily rainfall distribution by scaling the different daily rainfall amounts differently. In the daily translation method, the GCM future daily rainfall series is translated to a 0.25° gridcell rainfall series using the relationship established between the historical GCM-scale rainfall and 0.25° gridcell rainfall data. The daily scaling and daily translation methods generally give higher extreme and annual runoff than the constant scaling method because they take into account the increase in extreme daily rainfall (which generates significant runoff) simulated by the large majority of the GCMs. However, the difference between the mean annual runoff simulated with future daily rainfall series obtained using the constant versus daily scaling methods is generally less than 5%, which is relatively smaller than the range of runoff results from the different GCMs of 30%–40%.

Corresponding author address: Freddie Mpelasoka, CSIRO Land and Water, Black Mountain Laboratories, GPO Box 1666, Canberra, ACT 2601, Australia. Email: freddie.mpelasoka@csiro.au

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  • Alcamo, J., Kreileman G. J. J. , Krol M. S. , and Zuidema G. , 1994a: Modeling the global society-biosphere-climate system. Part 1: Model description and testing. Water Air Soil Pollut., 76 , 135.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alcamo, J., and Coauthors, 1994b: Modeling the global society-biosphere-climate system. Part 2: Computed scenarios. Water Air Soil Pollut., 76 , 3778.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Allan, R. P., and Soden B. J. , 2008: Atmospheric warming and the amplification of precipitation extremes. Science, 321 , 14811484. doi:10.1126/science.1160787.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Allen, M. R., and Ingram W. J. , 2002: Constraints on future changes in climate and the hydrological cycle. Nature, 419 , 224232.

  • Chandler, R. E., and Wheater H. S. , 2002: Analysis of rainfall variability using generalized linear models: A case study from the west of Ireland. Water Resour. Res., 38 , 1192. doi:10.1029/2001WR000906.

    • Search Google Scholar
    • Export Citation
  • Charles, S. P., Bates B. C. , Smith I. N. , and Hughes J. P. , 2004: Statistical downscaling of daily precipitation from observed and modelled atmospheric fields. Hydrol. Processes, 18 , 13731394.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chiew, F. H. S., 2006: Estimation of rainfall elasticity of streamflow in Australia. Hydrol. Sci. J., 51 , 613625.

  • 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 , 611620.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chiew, F. H. S., and McMahon T. A. , 2002: Global ENSO–streamflow teleconnection, streamflow forecasting and interannual variability. Hydrol. Sci. J., 47 , 505522.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chiew, F. H. S., Whetton P. H. , McMahon T. A. , and Pittock A. B. , 1995: Simulation of the impacts of climate change on runoff and soil moisture in Australian catchments. J. Hydrol., 167 , 121147.

    • Crossref
    • 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., and Coauthors, 2008: Climate data for hydrologic scenario modelling across the Murray-Darling Basin: A report to the Australian Government from the CSIRO Murray-Darling Basin Sustainable Yields Project. CSIRO Tech. Rep., 42 pp.

    • Search Google Scholar
    • Export Citation
  • Christensen, N. S., Wood A. W. , Lettenmaier D. P. , and Palmer R. N. , 2004: Effects of climate change on the hydrology and water resources of the Colorado River basin. Climatic Change, 62 , 337363.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cubasch, U., von Storch H. , Waszkewitz J. , and Zorith E. , 1996: Estimates of climate change in Southern Europe derived from dynamical climate model output. Climate Res., 7 , 129149.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dettinger, M. D., Cayan D. R. , Meyer M. K. , and Jeton A. E. , 2004: Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900–2099. Climatic Change, 62 , 283317.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Diaz-Nieto, J., and Wilby R. L. , 2005: A comparison of statistical downscaling and climate change factor methods: Impacts on low flows in the River Thames, United Kingdom. Climatic Change, 69 , 245268.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fowler, H. J., Blenkinsop S. , and Tebaldi C. , 2007: Linking climate change modelling to impacts studies: Recent advances in downscaling techniques for hydrological modelling. Int. J. Climatol., 27 , 15471578.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giorgi, F., 1990: Simulation of regional climate using a limited area model nested in a general circulation model. J. Climate, 3 , 941963.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gordon, H. B., and O’Farrell S. P. , 1997: Transient climate change in the CSIRO coupled model with dynamic sea ice. Mon. Wea. Rev., 125 , 875907.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gordon, H. B., Whetton P. H. , Pittock A. B. , Fowler A. M. , and Haylock M. R. , 1992: Simulated changes in daily rainfall intensity due to the enhanced greenhouse effect: Implications for extreme rainfall events. Climate Dyn., 8 , 83102.

    • Crossref
    • 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 Publication 280, IAHS Press, 165–174 pp.

    • Search Google Scholar
    • Export Citation
  • Held, I. M., and Soden B. J. , 2006: Robust responses of hydrological cycle to global warming. J. Climate, 19 , 56865699.

  • Hulme, M., and Carter T. R. , 2000: The changing climate of Europe. Assessment of the Potential Effects of Climate Change in Europe, Rep. of the ACACIA Concerted Action, University of East Anglia, 350 pp.

    • Search Google Scholar
    • Export Citation
  • Hulme, M., Jiang T. , and Wigley T. M. L. , 1995a: SCENGEN: A climate change scenario generator. Software user manual, version 1.0. Climatic Research Unit, University of East Anglia, 38 pp.

    • Search Google Scholar
    • Export Citation
  • Hulme, M., Raper S. C. B. , and Wigley T. M. L. , 1995b: An integrated framework to address climate change (ESCAPE) and further developments of the global and regional climate modules (MAGICC). Energy Policy, 23 , 347355.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jeffrey, S. J., Carter J. O. , Moodie K. M. , and Beswick R. A. , 2001: Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environ. Modell. Software, 16 , 309330.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kenny, G. J., and Coauthors, 2000: Investigating climate change impacts and thresholds: An application of the CLIMPACTS integrated assessment model for New Zealand agriculture. Climatic Change, 46 , 91113.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kite, G. W., Dalton A. , and Dion K. , 1994: Simulation of streamflow in a macroscale watershed using general circulation model data. Water Resour. Res., 30 , 15471559.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuhl, S. C., and Miller J. R. , 1992: Seasonal river runoff calculated from a global atmospheric model. Water Resour. Res., 28 , 20292039.

  • Lettenmaier, D. P., and Gan T. Y. , 1990: Hydrologic sensitivities of the Sacramento-San Joaquin River basin, California, to global warming. Water Resour. Res., 26 , 6986.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maurer, E. P., and Hidalgo H. G. , 2008: Utility of daily vs. monthly large-scale climate data: An intercomparison of two statistical downscaling methods. Hydrol. Earth Syst. Sci., 12 , 551563.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mehrotra, R., Sharma A. , and Cordery I. , 2004: Comparison of two approaches for downscaling synoptic atmospheric patterns to multisite precipitation occurrence. J. Geophys. Res., 109 , D14107. doi:10.1029/2004JD004823.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miller, J. R., and Russell G. L. , 1992: The impact of global warming on river runoff. J. Geophys. Res., 97 , 27572764.

  • Mitchell, J. F. B., Manabe S. , Meleshko V. , and Tokioka T. , 1990: Equilibrium climate change and its implications for the future. Climate Change: The IPCC Scientific Assessment, J. T. Houghton, G. J. Jenkins, and J. J. Ephraums, Eds., Cambridge University Press, 131–172.

    • 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 , 176.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mpelasoka, F., and Chiew F. H. S. , 2008: Runoff projection sensitivity to rainfall scenario methodology. Proc. Fourth Biennial Meeting of the Int. Congress on Environmental Modelling and Software, Barcelona, Catalonia, Spain, International Environmental Modelling and Software Society, 1169–1176.

    • Search Google Scholar
    • Export Citation
  • Mpelasoka, F., Mullan A. B. , and Heerdegen R. G. , 2001: New Zealand climate change information derived by multivariate statistical and artificial neural network approaches. Int. J. Climatol., 21 , 14151433.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nunez, M., and McGregor J. L. , 2007: Modelling future water environments of Tasmania, Australia. Climate Res., 34 , 114.

  • Payne, J. T., Wood A. W. , Hamlet A. F. , Palmer R. N. , and Lettenmaier D. P. , 2004: Mitigating the Effects of Climate Change on the Water Resources of the Columbia River Basin. Climatic Change, 62 , 233256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Perica, S., and Foufoula-Georgiou E. , 1996: Model for multiscale disaggregation of spatial rainfall based on coupling meteorological and scaling descriptions. J. Geophys. Res., 101 , (D21). 2634726362.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reichl, J. P. C., Chiew F. H. S. , and Western A. W. , 2006: Model averaging, equifinality and uncertainty estimation in the modelling of ungauged catchments. Proc. Third Biennial Meeting: Summit on Environmental Modelling and Software, Burlington, Vermont, International Environmental Modeling and Software Society, 6 pp.

    • Search Google Scholar
    • Export Citation
  • Renwick, J. A., Katzfey J. J. , Nguyen K. C. , and McGreor J. L. , 1998: Regional model simulation of New Zealand climate. J. Geophys. Res., 103 , 59735982.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotmans, J., Hulme M. , and Downing T. E. , 1994: Climate change implications for Europe: An application of the ESCAPE model. Global Environ. Change, 4 , 97124.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salathe, E. P., 2005: Downscaling simulations of future global climate with application to hydrologic modelling. Int. J. Climatol., 23 , 419436.

    • Search Google Scholar
    • Export Citation
  • Santer, B. D., Wigley T. M. L. , Schlesinger M. E. , and Mitchell J. F. B. , 1990: Developing climate scenarios from equilibrium GCM results. Max-Planck-Institut für Meteorologie Rep. 47, 29 pp.

    • Search Google Scholar
    • Export Citation
  • Sharma, D., Gupta A. D. , and Babel M. S. , 2007: Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand. Hydrol. Earth Syst. Sci. Discuss., 4 , 3574.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Singh, P., and Bengtsson L. , 2004: Hydrological sensitivity of a large Himalayan basin to climate change. Hydrol. Processes, 18 , 23632385.

  • 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
  • Trenberth, K. E., Dai A. , Rasmussen R. M. , and Parsons D. B. , 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84 , 12051217.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • VanRheenen, N. T., Wood A. W. , Palmer R. N. , and Lettenmaier D. P. , 2004: Potential implications of PCM climate change scenarios for Sacramento–San Joaquin River Basin hydrology and water resources. Climatic Change, 62 , 257281.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vaze, J., Teng J. , Post D. , Chiew F. H. S. , Perraud J-M. , and Kirono D. , 2008: Future climate and runoff projections (∼2030) for New South Wales and Australian Capital Territory. NSW Department of Water and Energy Rep., 42 pp.

    • Search Google Scholar
    • Export Citation
  • von Storch, H., Zorita E. , and Cubash U. , 1993: Downscaling of global climate change estimates to regional scales: An application to Iberian rainfall in wintertime. J. Climate, 6 , 11611171.

    • Crossref
    • 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 , 530548.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilby, R. L., and Wigley T. M. L. , 2000: Precipitation predictors for downscaling: Observed and general circulation model relationships. Int. J. Climatol., 20 , 641661.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wood, A. W., Leung L. R. , Sridhar V. , and Lettenmaier D. P. , 2004: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change, 62 , 189216.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wurbs, R. A., Muttiah R. S. , and Felden F. , 2005: Incorporation of climate change in water availability modeling. J. Hydrol. Eng., 10 , 375385.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, C-Y., 1999: From GCMs to river flow: A review of downscaling methods and hydrologic modelling approaches. Prog. Phys. Geogr., 23 , 229249.

    • Crossref
    • Search Google Scholar
    • Export Citation
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