Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 14 1 2010 10.5194/hess-14-159-2010 http://www.hydrol-earth-syst-sci.net/14/159/2010/ http://www.hydrol-earth-syst-sci.net/14/159/2010/hess-14-159-2010.html http://www.hydrol-earth-syst-sci.net/14/159/2010/hess-14-159-2010.pdf 159 169 2010-01-27 Climate and terrain factors explaining streamflow response and recession in Australian catchments A. I. J. M. van Dijk albert.vandijk@csiro.au CSIRO Land and Water, Canberra, ACT, Australia Daily streamflow data were analysed to assess which climate and terrain factors best explain streamflow response in 183 Australian catchments. Assessed descriptors of catchment response included the parameters of fitted baseflow models, and baseflow index (BFI), average quick flow and average baseflow derived by baseflow separation. The variation in response between catchments was compared with indicators of catchment climate, morphology, geology, soils and land use. Spatial coherence in the residual unexplained variation was investigated using semi-variogram techniques. A linear reservoir model (one parameter; recession coefficient) produced baseflow estimates as good as those obtained using a non-linear reservoir (two parameters) and for practical purposes was therefore considered an appropriate balance between simplicity and explanatory performance. About a third (27–34%) of the spatial variation in recession coefficients and BFI was explained by catchment climate indicators, with another 53% of variation being spatially correlated over distances of 100–150 km, probably indicative of substrate characteristics not captured by the available soil and geology data. The shortest recession half-times occurred in the driest catchments and were attributed to intermittent occurrence of fast-draining (possibly perched) groundwater. Most (70–84%) of the variation in average baseflow and quick flow was explained by rainfall and climate characteristics; another 20% of variation was spatially correlated over distances of 300–700 km, possibly reflecting a combination of terrain and climate factors. It is concluded that catchment streamflow response can be predicted quite well on the basis of catchment climate alone. The prediction of baseflow recession response should be improved further if relevant substrate properties were identified and measured. Akaike, H.: Statistical predictor identification Ann. Inst. Stat. Math., 22, 203–217 doi:10.1007/BF02506337, 1970. Bergström, S.: Bergstrom, S.: The HBV model – its structure and applications, Report RH No. 4, Swedish Meteorological and Hydrological Institute, Hydrology, Norrköping, Sweden, 35~pp. 1992. Beven, K.: Prophecy, reality and uncertainty in distributed hydrological modelling, Adv. Water Resour., 16, 41–41, 1993. Blöschl, G. and Sivapalan, M.: Scale issues in hydrological modelling: A review, Hydrol. Process., 9, 251–290, 1995. Brandes, D., Hoffmann, J. G., and Mangarillo, J. T.: Base flow recession rates, low flows, and hydrologic features of small watersheds in Pennsylvania, USA, J. Am. Water Resour. As., 41, 1177–1186, 2005. Burnash, R. J. C., Ferral, R. L., and McGuire, R.: A Generalized Streamflow Simulation System-Conceptual Modeling for Digital Computers, U.S. Department of Commerce, National Weather Service and State of California, Department of Water Resources, 1973. Chapman, T.: A comparison of algorithms for stream flow recession and baseflow separation, Hydrol. Process., 13, 701–714, 1999. Chapman, T. G.: Modelling stream recession flows, Environ. Modell. Softw., 18, 683–692, 2003. Chiew, F. H. S., Peel, M. C., and Western, A. W.: Application and testing of the simple rainfall-runoff model SIMHYD, in: Mathematical Models of Small Watershed Hydrology and Applications, edited by: Singh, V. P. and Frevert, D. K., Water resources Publication Littleton, Colorado, USA, 335–367, 2002. Coutagne, A.: Etude générale des variations de débits en fonction des facteurs qui les conditionnent, 2éme partie: les variations de débit en période non infuencée par les précipitations, La Houille Blanche, 416–436, 1948. Guerschman, J.-P., Van Dijk, A. I. J. M., McVicar, T. R., Van Niel, T. G., Li, L., Liu, Y., and Peña-Arancibia, J.: Water balance estimates from satellite observations over the Murray-Darling Basin, CSIRO, Canberra, Australia, 93~pp., 2008. Haberlandt, U., Klöcking, B., Krysanova, V., and Becker, A.: Regionalisation of the base flow index from dynamically simulated flow components – a case study in the Elbe River Basin, J. Hydrol., 248, 35–53, 2001. Jakeman, A. J. and Hornberger, G. M.: How much complexity is warranted in a rainfall-runoff model?, Water Resour. Res. 29, 2637–2649, 1993. Merz, R. and Blöschl, G.: Regionalisation of catchment model parameters, J. Hydrol., 287, 95–123, 2004. Nathan, R. J. and McMahon, T. A.: Evaluation of automated techniques for base flow and recession analyses, Water Resour. Res., 26, 1465–1473, 1990. Oudin, L., Andréassian, V., Lerat, J., and Michel, C.: Has land cover a significant impact on mean annual streamflow? An international assessment using 1508 catchments, J. Hydrol., 357, 303–316, 2008. Peel, M. C., Chiew, F. H. S., Western, A. W., and McMahon, T. A.: Extension of Unimpaired Monthly Streamflow Data and Regionalisation of Parameter Values to Estimate Streamflow in Ungauged Catchments. Report prepared for the Australian National Land and Water Resources Audit., Centre for Environmental Applied Hydrology, The University of Melbourne, 2000. Santhi, C., Allen, P. M., Muttiah, R. S., Arnold, J. G., and Tuppad, P.: Regional estimation of base flow for the conterminous United States by hydrologic landscape regions, J. Hydrol., 351, 139–153, 2008. Schoups, G., van de Giesen, N. C., and Savenije, H. H. G.: Model complexity control for hydrologic prediction, Water Resour. Res., 44, W00B03, doi:10.1029/2008WR006836, 2008. Sivapalan, M., Takeuchi, K., Franks, S. W., Gupta, V. K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J. J., Mendiondo, E. M., O'Connell, P. E., Oki, T., Pomeroy, J. W., Schertzer, D., Uhlenbrook, S., and Zehe, E.: IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences, Hydrol. Sci. J., 48, 857–880, doi:10.1623/hysj.48.6.857.51421, 2003. Tallaksen, L. M.: A review of baseflow recession analysis, J. Hydrol., 165, 349–370, 1995. van Dijk, A. I. J. M., Hairsine, P. B., Arancibia, J. P., and Dowling, T. I.: Reforestation, water availability and stream salinity: A multi-scale analysis in the Murray-Darling Basin, Australia, Forest Ecol. Manag., 251, 94–109, 2007. Wagener, T. and Wheater, H. S.: Parameter estimation and regionalization for continuous rainfall-runoff models including uncertainty, J. Hydrol., 320, 132–154, 2006. Weisman, R. N.: The effect of evapotranspiration on streamflow recession, Hydrol. Sci. Bull., XXII, 371–377, 1977. Wittenberg, H.: Baseflow recession and recharge as nonlinear storage processes, Hydrol. Process., 13, 715–726, 1999. Wittenberg, H. and Sivapalan, M.: Watershed groundwater balance estimation using streamflow recession analysis and baseflow separation, J. Hydrol., 219, 20–33, 1999. Zecharias, Y. B. and Brutsaert, W.: Recession characteristics of groundwater outflow and baseflow from mountainous watersheds, Water Resour. Res., 24, 1651–1658, 1988. Zhang, L., Hickel, K., Dawes, W. R., Chiew, F. H. S., Western, A. W., and Briggs, P. R.: A rational function approach for estimating mean annual evapotranspiration Water Resour. Res., 40, W02502, doi:10.1029/2003WR002710, 2004.