Skip to main content

Potential improvements to statistical downscaling of general circulation model outputs to catchment streamflows with downscaled precipitation and evaporation

Abstract

An existing streamflow downscaling model (SDM(original)), was modified with the outputs of a precipitation downscaling model (PDM) and an evaporation downscaling model (EDM) as additional inputs, for improving streamflow projections. For this purpose, lag 0, lag 1 and lag 2 outputs of PDM were individually introduced to SDM(original) as additional inputs, and then it was calibrated and validated. Performances of the resulting modified models were assessed using Nash-Sutcliffe efficiency (NSE) during calibration and validation. It was found that the use of lag 0 precipitation as an additional input to SDM(original) improves NSE in calibration and validation. This modified streamflow downscaling model is called SDM(lag0_preci). Then lag 0, lag 1 and lag 2 evaporation of EDM were individually introduced to SDM(lag0_preci) as additional inputs and it was calibrated and validated. The resulting models showed signs of over-fitting in calibration and under-fitting in validation. Hence, SDM(lag0_preci) was selected as the best model. When SDM(lag0_preci) was run with observed lag 0 precipitation, a large improvement in NSE was seen. This proved that if precipitation produced by the PDM can accurately reproduce the observations, improved precipitation predictions will produce better streamflow predictions.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  • Anandhi A, Srinivas VV, Nanjundiah RS, Kumar DN (2008) Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine. Int J Climatol 28:401–420

    Article  Google Scholar 

  • Bastola S, Misra V (2013) Evaluation of dynamically downscaled reanalysis precipitation data for hydrological application. Hydrol Process. doi:10.1002/hyp.9734

    Google Scholar 

  • Bedia J, Herrera S, Martín DS, Koutsias N, Gutiérrez JM (2013) Robust projections of fire weather index in the Mediterranean using statistical downscaling. Clim Chang 120:229–247

    Article  Google Scholar 

  • Benestad R, Hanssen-Bauer I, Chen D (2008) Empirical-statistical downscaling. World Scientific, Singapore, p 228

    Book  Google Scholar 

  • Cannon AJ, Whitfield PH (2002) Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models. J Hydrol 259:136–151

    Article  Google Scholar 

  • Cañón J, Domínguez F, Valdés JB (2011) Downscaling climate variability associated with quasi-periodic climate signals: a new statistical approach using MSSA. J Hydrol 398:65–75

    Article  Google Scholar 

  • Cayley RA, Taylor DH (1997) Grampians special map area and geological report. Geol Surv Victoria Rep 107:42–130

    Google Scholar 

  • Denis B, Laprise R, Cay D, Côté J (2002) Downscaling ability of one-way nested regional climate models: the big-brother experiment. Clim Dynam 18:627–646

    Article  Google Scholar 

  • Duan J, McIntyre N, Onof C. (2012) Resolving non-stationarity in statistical downscaling of precipitation under climate change scenarios. British Hydrological Society Eleventh National Symposium, Hydrology for a changing world, Dundee, UK

  • Flint LE, Flint AL (2012) Downscaling future climate scenarios to fine scales for hydrologic and ecological modelling and analysis. Ecol Process 1:2

    Article  Google Scholar 

  • Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578

    Article  Google Scholar 

  • Ghosh S, Mujumdar PP (2008) Statistical downscaling of GCM simulations to streamflow using relevance vector machine. Adv Water Resour 31:132–146

    Article  Google Scholar 

  • Goyal MK, Ojha CSP (2012) Downscaling of surface temperature for lake catchment in an arid region in India using linear multiple regression and neural networks. Int J Climatol 32:552–566

    Article  Google Scholar 

  • Gutiérrez JM, San-Martín D, Brands S, Manzanas R, Herrera S (2013) Reassessing statistical downscaling techniques for their robust application under climate change conditions. J Clim 26:171–188

    Article  Google Scholar 

  • GWMWater (2011a) Lake Bellfield operating rules Available online at http://www.gwmwater.org.au/information/publications/ground-and-surface-water/west-wimmera-gma/cat_view/163-reservoir-operating-rules

  • GWMWater (2011b) Storage management rules for the Wimmera Mallee system headworks. Available online at http://www.gwmwater.org.au/information/publications/ground-and-surface-water/west-wimmera-gma/cat_view/163-reservoir-operating-rules. 5–6

  • Haas R, Pinto JG (2012) A combined statistical and dynamical approach for downscaling large-scale footprints of European windstorms. J Geophys Res Lett 39:L23804

    Article  Google Scholar 

  • Hertig E, Jacobeit J (2008) Assessments of Mediterranean precipitation changes for the 21st century using statistical downscaling techniques. Int J Climatol 28:1025–1045

    Article  Google Scholar 

  • Hertig E, Jacobeit J (2013) A novel approach to statistical downscaling considering nonstationarities: application to daily precipitation in the Mediterranean area. J Geophys Res Atmos 118:520–533

    Article  Google Scholar 

  • Horvath K, Koracin D, Vellore RK, Jiang J, Belu R (2012) Sub-kilometre dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models. J Geophys Res 117:D11

    Google Scholar 

  • IPCC (2000) IPCC special report on emissions scenarios—summary for policymakers. Online report available at http://www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf. 4-8.

  • Jeong DI, St-Hilaire A, Ouarda TBMJ, Gachon P (2012) Multisite statistical downscaling model for daily precipitation combined by multivariate multiple linear regression and stochastic weather generator. Clim Chang 114:567–591

    Article  Google Scholar 

  • Karl TR, Wang WC, Schlesinger ME, Knight RW, Portman D (1990) A method of relating general circulation model simulated climate to the observed local climate part I: seasonal statistics. J Clim 3:1053–1079

    Article  Google Scholar 

  • Landman WA, Mason SJ, Tyson PD, Tennant WJ (2001) Statistical downscaling of GCM simulations to streamflow. J Hydrol 252:221–236

    Article  Google Scholar 

  • Li H, Sheffield J, Wood EF (2010) Bias correction of monthly precipitation and temperature fields from intergovernmental panel on climate change AR4 models using equidistant quantile matching. J Geophys Res-Atmos 115:1–20

    Google Scholar 

  • Maurer EP, Hidalgo HG (2008) Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods. Hydrol Earth Syst Sci 12:551–563

    Article  Google Scholar 

  • Murphy J (1998) An evaluation of statistical and dynamical techniques for downscaling local climate. Int J Climatol 12:2256–2284

    Article  Google Scholar 

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part 1—a discussion of principles. J Hydrol 10:282–290

    Article  Google Scholar 

  • Nasseri M, Tavakol-Davani H, Zahraie B (2013) Performance assessment of different data mining methods in statistical downscaling of daily precipitation. J Hydrol 492:1–14

    Article  Google Scholar 

  • Pearson K (1895) Mathematical contributions to the theory of evolution. iii. Regression heredity and panmixia. Philos T Roy Soc A 187:253–318

    Article  Google Scholar 

  • Qian JH, Zubair L (2010) The effect of grid spacing and domain size on the quality of ensemble regional climate downscaling over South Asia during the north-easterly monsoon. Mon Weather Rev 138:2780–2802

    Article  Google Scholar 

  • Raje D, Mujumdar PP (2010) Constraining uncertainty in regional hydrologic impacts of climate change: nonstationarity in downscaling. Water Resour Res 46:W07543

    Google Scholar 

  • Rojas M (2006) Multiply nested regional climate simulation for Southern America: sensitivity to model resolution. Mon Weather Rev 134:2208–2223

    Article  Google Scholar 

  • Rummukainen M (2010) State-of-the-art with regional climate models. Wiley Interdiscip Rev Clim Chang 1:82–96

    Article  Google Scholar 

  • Sachindra DA, Huang F, Barton AF, Perera BJC (2013) Least square support vector and multi-linear regression for statistically downscaling general circulation model outputs to catchment streamflows. Int J Climatol 33:1087–1106

    Article  Google Scholar 

  • Sachindra DA, Huang F, Barton AF, Perera BJC (2014a) Statistical downscaling of general circulation model outputs to precipitation part 1: calibration and validation. Int J Climatol 34:3264–3281

    Article  Google Scholar 

  • Sachindra DA, Huang F, Barton AF, Perera BJC (2014b) Statistical downscaling of general circulation model outputs to precipitation part 2: bias-correction and future projections. Int J Climatol 34:3282–3303

    Article  Google Scholar 

  • Sachindra DA, Huang F, Barton AF, Perera BJC (2014c) Multi-model ensemble approach for statistically downscaling general circulation model outputs to precipitation. Q J Roy Meteor Soc 140:1161–1178. doi:10.1002/qj.2205

    Article  Google Scholar 

  • Sachindra DA, Huang F, Barton AF, Perera BJC (2014d) Statistical downscaling of general circulation model outputs to catchment scale hydroclimatic variables issues, challenges and possible solutions. J Water Clim Change. doi:10.2166/wcc.2014.056

    Google Scholar 

  • Salvi K, Kannan S, Ghosh S (2011) Statistical downscaling and bias-correction for projections of Indian rainfall and temperature in climate change studies. Proceedings of 4 th International Conference on Environmental and Computer Science. 16–18 September 2011, Singapore, pp.7-11

  • Samadi S, Carbone GJ, Mahdavi M, Sharifi F, Bihamta MR (2012) Statistical downscaling of climate data to estimate streamflow in a semi-arid catchment. Hydrol Earth Syst Sci Discuss 9:4869–4918

    Article  Google Scholar 

  • Shang KZ, Wang SG, Ma YX, Zhou ZJ, Wang JY, Liu HL, Wang YQ (2007) A scheme for calculating soil moisture content by using routine weather data. Atmos Chem Phys 7:5197–5206

    Article  Google Scholar 

  • Sinclair KM (2004) Wimmera-Malle simulation model—Annual update methodology. A report by Sinclair, Knight Merz, Melbourne, Australia. 21–79

  • Smith I, Chandler E (2010) Refining rainfall projections for the Murray Darling Basin of south-east Australia—the effect of sampling model results based on performance. Clim Chang 102:377–393

    Article  Google Scholar 

  • Tareghian R, Rasmussen PF (2013) Statistical downscaling of precipitation using quantile regression. J Hydrol 487:122–135

    Article  Google Scholar 

  • Timbal B, Fernandez E, Li Z (2009) Generalization of a statistical downscaling model to provide local climate change projections for Australia. Environ Model Softw 24:341–358

    Article  Google Scholar 

  • Tisseuil C, Vrac M, Lek S, Wade AJ (2010) Statistical downscaling of river flows. J Hydrol 385:279–291

    Article  Google Scholar 

  • Tripathi S, Srinivas VV, Nanjundiah RS (2006) Downscaling of precipitation for climate change scenarios: a support vector machine approach. J Hydrol 330:621–640

    Article  Google Scholar 

  • van Vuuren PD, Edmonds JA, Kainuma M, Riahi K, Thomson AM, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque JF, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose S (2011) The representative concentration pathways: an overview. Clim Chang 109:5–31

    Article  Google Scholar 

  • Wang P, Yamanaka T, Qiu GY (2012) Causes of decreased reference evapotranspiration and pan evaporation in the Jinghe River catchment, northern China. Environmentalist 32:1–10

    Article  Google Scholar 

  • Wilby RL, Fowler HJ (2011) Regional climate modelling in modelling the impact of climate change on water resources. Modelling the impact of climate change on water resources. F. Fung, A. Lopez and M. New, eds., Wiley-Blackwell, Chichester, UK. 209

  • Wilby RL, Charles SP, Zorita E, Timbal B, Whetton P, Mearns LO (2004) Guidelines for use of climate scenarios developed from statistical downscaling methods, supporting material to the IPCC. Available online at http://www.ipcc-data.org/. 3–21. (Accessed 28th January 2012)

  • Wilks DS (1999) Multisite downscaling of daily precipitation with a stochastic weather generator. Climate Res 11:125–136

    Article  Google Scholar 

  • Yang T, Li H, Wang W, Xu CY, Yu Z (2012) Statistical downscaling of extreme daily precipitation, evaporation, and temperature and construction of future scenarios. Hydrol Process 26:3510–3523

    Article  Google Scholar 

  • Zhang H, Huang GH (2013) Development of climate change projections for small watersheds using multi-model ensemble simulation and stochastic weather generation. Clim Dynam 40:805–821

    Article  Google Scholar 

Download references

Acknowledgments

The authors wish to acknowledge the financial assistance provided by the Australian Research Council Linkage Grant scheme and Grampians Wimmera Mallee Water Corporation for this project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to D. A. Sachindra.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sachindra, D.A., Huang, F., Barton, A. et al. Potential improvements to statistical downscaling of general circulation model outputs to catchment streamflows with downscaled precipitation and evaporation. Theor Appl Climatol 122, 159–179 (2015). https://doi.org/10.1007/s00704-014-1288-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-014-1288-7

Keywords

  • Streamflow
  • Validation Period
  • Statistical Downscaling
  • Probable Predictor
  • Monthly Streamflows