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29 - How to choose an appropriate catchment model

from Part IV - New methods for evaluating effects of land-use change

Published online by Cambridge University Press:  12 January 2010

C. Barnes
Affiliation:
Climate and Agricultural Risk Unit, Agriculture and Food Sciences Program, Bureau of Rural Sciences, P.O. Box E11, Kingston ACT 2604 Canberra, Australia
M. Bonell
Affiliation:
Hydrological Processes and Climate Section, Division of Water Sciences, UNESCO, 1 rue Miollis, 75732 Paris Cedex 15, France
M. Bonell
Affiliation:
UNESCO, Paris
L. A. Bruijnzeel
Affiliation:
Vrije Universiteit, Amsterdam
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Summary

INTRODUCTION

The existence of a large number of catchment hydrology models, evident from even a cursory glance at the literature, is likely to cause trepidation or confusion for even expert modellers, let alone practitioners of hydrology who merely require something ‘off the shelf’ which they can use with confidence. Typically, available catchment models often come with exaggerated claims for the breadth of their applicability, and little or no in-depth discussion of their inherent assumptions and consequent limitations. Two questions will therefore be addressed in this chapter:

  1. How can an appropriate model for my catchment be chosen, given an intended application? and

  2. How can an appropriate model be constructed (or an existing model be modified) if none exists at present?

There would appear to be several reasons for the present wide range of models, including:

  • a diverse range of catchments and purposes (for example, forecasting or regulatory support) which in turn implies interest in many different kinds of processes;

  • availability of different levels of information or data quantity and quality; and

  • the fact that catchments are complex systems, having a huge number of potentially significant processes, and consequently ‘emergent behaviour’ (defined later on) which is not evidently a simple sum of the component parts.

Taken together, these three factors imply that to represent catchment behaviour efficiently, much of what is deemed to be of secondary importance must inevitably be either ignored or greatly simplified by using specific assumptions.

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Forests, Water and People in the Humid Tropics
Past, Present and Future Hydrological Research for Integrated Land and Water Management
, pp. 717 - 741
Publisher: Cambridge University Press
Print publication year: 2005

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References

Baker, F. G. (1978). Variability of hydraulic conductivity within and between nine Wisconsin soil series. Wat. Resour. Res. 14, 103–108CrossRefGoogle Scholar
Barnes, C. J. (1995). The art of catchment modelling: What is a good model?Environment International 21, 747–751CrossRefGoogle Scholar
Barnes, C. J., Walker, D. and Short, D. L. (1997a). Models for Integrated Catchment Management, MODSIM97: International Conference on Modelling and Simulation Proceedings, Hobart, Tasmania (Eds. McDonald and McAleer); Vol 4, 1647–1652
Barnes, C. J. and Bonell, M. (1996). Application of unit hydrograph techniques to solute transport in catchments. Hydrol. Proc., 10: 793–8023.0.CO;2-K>CrossRefGoogle Scholar
Barnes, C. J., Short, D. L. and Bonell, M. (1997b). Modelling water, nutrient and sediment fluxes using catchment scale parameters. Hydrochemistry (Proceedings of the Rabat Symposium, April 1997) IAHS Publ. No. 244, 195–205Google Scholar
Barnes, C. J. (2000). The use of cumulative data for characterising hydrological systems. In: Proceedings of Runoff Generation and Implications for River Basin Modelling, Leibundgut, C., Uhlenbrook, S. and McDonnell, J. (Eds.), Freiburger Schriften zur Hydrologie. 82–89
Bear, J. (1972). Dynamics of Fluids in Porous Media. American Elsevier, New York
Bear, J. and Verruijt, A. (1987). Modelling Groundwater Flow and Pollution, Theory and Applications of Transport in Porous media, Reidel, Dordrecht
Bergström, S. (1995). The HBV model. In: Computer Models of Watershed Hydrology, Singh, V. P. (Editor). Water Resource Publications. Highlands Ranch, Colorado, USA. 443–476
Bergström, S., Lindström, G. and Pattersson, , (2002). Multi-variable parameter estimation to increase confidence in hydrological modelling. Hydrol. Process. 16, 413–421CrossRefGoogle Scholar
Beven, K. J. (1989). Interflow. In: Unsaturated Flow in Hydrologic Modelling, Morel-Seytoux, H. J. (ed.), Kluwer. 191–219CrossRef
Beven, K. J. (1993). Prophecy, reality and uncertainty in distributed hydrological modelling. Advances in W. Resour.. 16: 41–51CrossRefGoogle Scholar
Beven, K. J. (2002). Towards an alternative blueprint for a physically-based digitally simulated hydrologic response modelling system. Hydrol. Process., 16: 189–206CrossRefGoogle Scholar
Beven, K. J. and Kirkby, M. J. (1979). ‘A physically-based variable contributing area model of basin hydrology’, Hydrol. Sci. Bull., 24: 43–69CrossRefGoogle Scholar
Beven, K. J and Feyen, J. (2002). The future of distributed modelling. Hydrol. Process., 16, 169–172CrossRefGoogle Scholar
Beven, K. J., Kirkby, M. J., Schofield, N. and Tagg, A. F. (1984). Testing a physically-based flood forecasting model (TOPMODEL) for three UK catchments. J. Hydrol. 69: 119–143CrossRefGoogle Scholar
Bonell, M. (1998). Selected challenges in runoff generation research in forests from the hillslope to headwater drainage basin scale. J. Amer. Water Res. Assoc., 34: 765–785CrossRefGoogle Scholar
Bonell, M., Gilmour, D. A. and Sinclair, D. F. (1981). Soil hydraulic properties and their effect on surface and subsurface water transfer in a tropical rainforest catchment. Hydrol. Sci. Bull. 26: 1–18CrossRefGoogle Scholar
Bonell, M., Cassells, D. S. and Gilmour, D. A. (1987). ‘Spatial variations in soil hydraulic properties under tropical rainforest in north-eastern Australia’ in Fok Yu-Si (Ed), Proc. Int. Conf. on Infiltration Development and Application. Wat. Resour. Res. Center, Univ. of Hawaii at Manoa, Jan. 1987. 153–165
Bonell, M., Barnes, C. J., Grant, C. R., Howard, A. and Burns, J. (1998). High rainfall response-dominated catchments: A comparative study of experiments in tropical north-east Queensland with temperate New Zealand. In: Isotope Tracers in Catchment Hydrology, Kendall, C. and McDonnell, J. J. (Editors), Elsevier, Chapter 11, 347–390CrossRef
Boughton, W. C. (1984). A simple model for estimating the water yield of ungauged catchments. Civ. Engg. Trans., I. E. Aust., CE 26(2), 83–88Google Scholar
Bronswijk, J. J. B., Hamminga, W. and Oostindie, K. (1995). Field-scale solute transport in a heavy clay soil, W. Resour. Res., 31: 517–526CrossRefGoogle Scholar
Chiew, F. H. S. and McMahon, T. A. 1992. Complete set of daily rainfall potential evapotranspiration and streamflow data for 28 unregulated catchments, Department of Civil and Agricultural Engineering, The University of Melbourne (Unpubl.)
Chow, Ven Te (1964) (ed.). Handbook of Applied Hydrology, McGraw-Hill, New York
Davis, J. R. and Farley, T. F. N.. (1997). CMSS: Policy analysis software for Catchment Managers. Environmental Software and Modelling, 12, 197–210CrossRefGoogle Scholar
Dawdey, D. R. and O'Donnell, T. (1965). Mathematical models of catchment behaviour. Proc. ASCE HY4, 91: 132–137Google Scholar
Dooge, J. C. I. (1959). A general theory of the unit hydrograph technique. J. Geophys. Res. 64: 241–256CrossRefGoogle Scholar
Elsenbeer, H. (2001). Hydrologic flowpaths in tropical rainforest soilscapes-a review. Hydrol. Process. 15: 1751–1759CrossRefGoogle Scholar
Elsenbeer, H. and Vertessy, R. A. (2000). Stormflow generation and flowpath characteristics in an Amazonian rainforest catchment. Hydrol. Process. 14: 2367–23813.0.CO;2-H>CrossRefGoogle Scholar
Freeze, R. A. and Harlen, R. L. (1969). Blue print for a physically-based, digitally-simulated hydrologic response model. J. Hydrol. 9: 237–258CrossRefGoogle Scholar
Ganeshanandam, S. and Krzanowski, W. J. 1989. On selecting variables and assessing their performance in linear discriminant analysis. Austral. J. Stat., 31: 433–447CrossRefGoogle Scholar
Germann, P. F. (1990a). Macropores and hydrologic hillslope processes. In: Anderson, M. G. and Burt, T. P. (eds.), Process Studies in Hillslope Hydrology. John Wiley and Sons, Chichester. 327–363
Germann, P. F. (1990b). Preferential Flow and the Generation of Runoff. 1. Boundary Layer Flow Theory. Water Resour. Res., 26: 3055–3063Google Scholar
Gilmour, D. A. (1975). Catchment water balance studies on the wet tropical coast of North Queensland. Unpublished PhD Thesis, Dept. of Geography, James Cook University of North Queensland, Townsville, Australia
Grayson, R. B., Bloschl, G. and Moore, I. D. (1995). Distributed parameter modelling using vector elevation data: THALES and TAPES-C. In: Computer Models of Watershed Hydrology, Singh, V. P. (Ed.), Water Resource Publications, Highlands Ranch, Colorado, USA, pp. 669–696
Jakeman, A. J. and Hornberger, G. M. (1993). How much complexity is warranted in a rainfall-runoff model?Water Resour. Res. 29: 2637–2649CrossRefGoogle Scholar
Jakeman, A. J., Littlewood, I. G. and Symons, H. D. (1991). Features and applications of IHACRES: A PC program for the identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data. In: Proceedings of the 13th IMACS World Congress on Computation and Applied Mathematics, vol. 4, edited by R. Viehnevetsky and J. J. H. Miller, pp. 1963–1967, Criterion, Dublin, Ireland
Jamieson, D. G. and Wilkinson, J. C. (1972). River Dee research program. 3. A short-term control strategy for multi-purpose reservoir systems. Water Resour. Res. 8: 911–920CrossRefGoogle Scholar
Kendall, C. and McDonnell, J. J. (1998). Isotope Tracers in Catchment Hydrology, Elsevier, Amsterdam, 839 pp
Kirchner, J. W., Feng, X. and Neal, C. (2000). Fractal stream chemistry and its implications for contaminant transport in catchments. Nature, 403: 524–527CrossRefGoogle ScholarPubMed
Kirchner, J. W., Feng, X. and Neal, C. (2001). Catchment-scale advection and dispersion as a mechanism for fractal scaling in stream tracer concentrations. J. Hydrol., 254: 82–101CrossRefGoogle Scholar
Kirchner, J. W., Feng, X., Neal, C. and Robson, A. J. (2004). The fine structure of water-quality dynamics: the (high-frequency) wave of the future. Hydrol. Process., 18(7): 1353–1359CrossRefGoogle Scholar
Kirkby, M. J. (1975). Hydrograph modelling strategies. In: Processes in Physical and Human Geography, Peel, R., Chisholm, M. and Hoggett, P. (eds). 69–90
Lange, H., Lischeid, G., Hoch, R. and Hauhs, M. (1996). Water flow paths and residence times in a small headwater catchment at Gardsjon, Sweden, during steady state storm flow conditions. W. Resour. Res. 32: 1689–1698CrossRefGoogle Scholar
Lindström, G. (2000). HBV model simulations of oxygen-18 flow in small forested basins in Sweden. In: Nordic Hydrological Conference, 2000, Nilsson, T, editor, Nordic Association for Hydrology, Nordic Hydrological Programme, NHP-Report No 46, Swedish Hydrological Council, Uppsala, 2000, 374–379
Lindström, G., Johansson, B., Persson, M., Gardelin, M. and Bergström, S. (1997). Development and test of the distributed HBV-96 hydrological model. J. Hydrol., 201: 272–288CrossRefGoogle Scholar
Littlewood, I. (2001). Practical aspects of calibrating and selecting unit hydrograph-based models for continuous river flow simulation. Hydrol. Sci. J., 46: 795–811CrossRefGoogle Scholar
Michaelsen, J. 1987. Cross-validation in statistical climate forecast models. J. Climate Appl. Meteor., 26: 1589–16002.0.CO;2>CrossRefGoogle Scholar
Moore, I. D. (1992). Terrain Analysis Programs for the Environmental Sciences — TAPES, Vol. 4 No 2, Agricultural Systems and Information Technology, Bureau of Resource Science, Canberra, ACT, pp. 37–39
Moore, I. D. and Grayson, R. B. (1991). Terrain-based catchment partitioning and runoff prediction using vector elevation data. Wat. Resour. Res., 27: 1177–1191CrossRefGoogle Scholar
Moore, I. D., O'Loughlin, E. M. and Burch, G. J. (1988). A contour-based topographic model for hydrological and ecological applications. Earth Surf. Proc. and Landforms, 13: 305–320CrossRefGoogle Scholar
Mulholland, P. J. (1993). Hydrometric and stream chemistry evidence of three stream flowpaths in Walker Branch Watershed. J. Hydrol., 151: 291–316CrossRefGoogle Scholar
Nash, J. E. (1957). The form of the instantaneous unit hydrograph. IAHS Pub. No. 45, 114–121Google Scholar
Nielsen, D. R., Biggar, J. W. and Erth, K. T. (1973). Spatial variability of field measured soil water properties. Hilgardia, 42: 215–259CrossRefGoogle Scholar
O'Loughlin, E. M. (1981). Saturation regions in catchments and their relations to soil and topographic properties, J. Hydrol, 53: 229–246CrossRefGoogle Scholar
O'Loughlin, E. M. (1986). Prediction of surface saturation zones in natural catchments by topographic analysis. Wat. Resour. Res., 22: 794–804CrossRefGoogle Scholar
O'Loughlin, E. M., Short, D. L. and Dawes, W. R. (1989). Modelling the hydrological response of catchment to land use change. In: Hydrology and Water Resources Symposium, Comparison in Austral Hydrology. Inst. Engrs., Canberra, 28–30 Nov. 1989, Christchurch New Zealand, 335–340
Perrin, C., Michel, C. and Andreassian, V. (2001). Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments. J. Hydrol. 242: 275–301CrossRefGoogle Scholar
Rogowski, A. S. (1972) Watershed physics: Soil variability criteria. Wat. Resour. Res. 8: 1015–1023CrossRefGoogle Scholar
Schellekens, J. (2000). Hydrological Processes in a Humid Rain Forest: A Combined Experimental and Modelling Approach. Vrije Universiteit, Amsterdam, The Netherlands, 158 pp
Seibert, J. (1999). Conceptual Runoff Models-Fiction or Representation of Reality? Acta Universitatis Upsaliensis, Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 436. 52 pp+ 6 papers, Uppsala, Sweden
Seibert, J. and McDonnell, J. J. (2002). On the dialogue between experimentalist and modeller in catchment hydrology: Use of soft data for multi-criteria model calibration. Wat. Resour. Res. 38(11): 23.11–23.64CrossRefGoogle Scholar
Seibert, J., Rodhe, A. and Bishop, K. (2002). Simulating interactions between saturated and unsaturated storage in a conceptual runoff model. Hydrol. Proc. (in press). Revised manuscript from the Proc. Int. Workshop on Runoff Generation and Implications for River Basin Modelling (Leibundgut, C., Uhlenbrook, S. and McDonnell, J., eds.), 9–12 October, Univ. Freiberg, Germany, Institut für Hydrologie der Universitat Freiburg i. Br., 118–126
Shaw, E. M. (1983). Hydrology in Practice, Van Nostrend Reinhold (International), London (in 2nd Edition 1988, Chapter 14, 322–348)
Sherman, (1932). Streamflow from rainfall by the unitgraph method. Eng. News Record, 108: 501–505Google Scholar
Slater, R. (1991). Integrated Process Management: A Quality Model. McGraw Hill, NY
Vertessy, R. A. and Elsenbeer, H. (1999). Distributed modeling of storm flow generation in an Amazonian rainforest catchment: Effects of model parameterization, W. Resour. Res. 35: 2173–2187CrossRefGoogle Scholar
Vertessy, R. A., Dawes, W. R., Zhang, L., Hatton, T. J. and Walker, J. (1996). Catchment scale Hydroloic modelling to assess the water and salt balance behaviour of eucalypt plantations. CSIRO Division of Water, Technical Memorandum 96.2, February 1996, Resources, 23 pp
Wheater, H. S., Jakeman, A. J. and Beven, K. J. (1993). Progress and directions in rainfall-runoff modelling. In: Modelling Change in Environmental Systems (Jakeman, A. J., Beck, M. B. and McAleer, editors), Wiley, Chichester, West Sussex, UK. 101–132
Young, P. and Beven, K. J. (1991). Computation of the instantaneous unit hydrograph and identifiable component flows with application to two small upland catchments – Comment. J. Hydrol. 129: 389–396CrossRefGoogle Scholar
Young, R. A., Onstad, C. A., Bosch, D. D. and Anderson, W. P.. (1989). AGNPS: A nonpoint-source pollution model for evaluating agricultural watersheds. J. Soil and Water Conservation, 44: 168–173Google Scholar

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  • How to choose an appropriate catchment model
    • By C. Barnes, Climate and Agricultural Risk Unit, Agriculture and Food Sciences Program, Bureau of Rural Sciences, P.O. Box E11, Kingston ACT 2604 Canberra, Australia, M. Bonell, Hydrological Processes and Climate Section, Division of Water Sciences, UNESCO, 1 rue Miollis, 75732 Paris Cedex 15, France
  • Edited by M. Bonell, L. A. Bruijnzeel, Vrije Universiteit, Amsterdam
  • Book: Forests, Water and People in the Humid Tropics
  • Online publication: 12 January 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511535666.037
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  • How to choose an appropriate catchment model
    • By C. Barnes, Climate and Agricultural Risk Unit, Agriculture and Food Sciences Program, Bureau of Rural Sciences, P.O. Box E11, Kingston ACT 2604 Canberra, Australia, M. Bonell, Hydrological Processes and Climate Section, Division of Water Sciences, UNESCO, 1 rue Miollis, 75732 Paris Cedex 15, France
  • Edited by M. Bonell, L. A. Bruijnzeel, Vrije Universiteit, Amsterdam
  • Book: Forests, Water and People in the Humid Tropics
  • Online publication: 12 January 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511535666.037
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • How to choose an appropriate catchment model
    • By C. Barnes, Climate and Agricultural Risk Unit, Agriculture and Food Sciences Program, Bureau of Rural Sciences, P.O. Box E11, Kingston ACT 2604 Canberra, Australia, M. Bonell, Hydrological Processes and Climate Section, Division of Water Sciences, UNESCO, 1 rue Miollis, 75732 Paris Cedex 15, France
  • Edited by M. Bonell, L. A. Bruijnzeel, Vrije Universiteit, Amsterdam
  • Book: Forests, Water and People in the Humid Tropics
  • Online publication: 12 January 2010
  • Chapter DOI: https://doi.org/10.1017/CBO9780511535666.037
Available formats
×