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Water Resources Management

, Volume 18, Issue 6, pp 591–612 | Cite as

Review on Regional Water Resources Assessment Models under Stationary and Changing Climate

  • C.-Y. XuEmail author
  • V. P. Singh
Article

Abstract

A comprehensive assessment of the water resources available in a region or a river basin is essential for finding sustainable solutions for water-related problems concerning both the quantity and quality of the water resources. Research on the development and application of water balance models at different spatial and temporal scales has been carried out since later part of the 19th century. As a result, a great deal of experience on various models and methods has been gained. This paper reviews both traditional long-term water balance methods and the new generation distributed models for assessing available water resources under stationary and changing climatic conditions at different spatial and temporal scales. The applicability and limitations of the methods are addressed. Finally, current advances and challenges in regional- and large-scale assessment of water resources are presented.

Key words

climate change hydrologic models regional scale review water balance water resources assessment 

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References

  1. Abdulla, F. A. and Lettenmaier, D. P., 1997a, ‘Development of regional parameter estimation equations for a macroscale hydrological model’, J. Hydrol. 197, 230–257.Google Scholar
  2. Abdulla, F. A. and Lettenmaier, D. P., 1997b, ‘Application of regional parameter estimation schemes to simulate the water balance of a large continental river’, J. Hydrol. 197, 258–285.Google Scholar
  3. Alley, W. M., 1984, ‘On the treatment of evapotranspiration, soil moisture accounting and aquifer recharge in monthly water balance models’, Water Resour. Res. 20(4), 1137–1149.Google Scholar
  4. Ambroise, B., Perrin, J. L., and Reutenauer, D., 1995, ‘Multicriterion validation of a semidistributed conceptual model of the water cycle in the Facht Catchment (Vosges Massif, France)’, Water Resour. Res. 31(3), 1467–1481.Google Scholar
  5. Anderson, M. P. and Woessner, W. W., 1992, ‘The role of postaudit in model validation’, Adv. Water Res. 15, 167–173.Google Scholar
  6. Arnell, N. W., 1992, ‘Factors controlling the effects of climate change on river flow regimes in a humid temperate environment’, J. Hydrol. 132, 321–342.Google Scholar
  7. Arnell, N. W., 1999, ‘A simple water balance model for the simulation of streamflow over a large geographic domain’, J. Hydrol. 217(3/4), 314–335.Google Scholar
  8. Arnold, J. G., Muttiah, R. S., Srinivasan, R., and Allen, P. M., 2000, ‘Regional estimation of base flow and groundwater recharge in the Upper Mississippi river basin’, J. Hydrol. 227, 21–40.Google Scholar
  9. Becker, A. and Braun, P., 1999, ‘Disaggregation, aggregation and spatial scaling in hydrological modelling’, J. Hydrol. 217, 239–252.Google Scholar
  10. Bergström, S., 1976, ‘Development and application of a conceptual runoff model for Scandinavian catchments’, Department of Water Resources Engineering, Lund Institute of Technology, Bulletin Series A-52, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden.Google Scholar
  11. Bergström, S., 1990, ‘Parametervärden för HBV-modellen I Sverige–Erfarenheter frán modellkalibreringar under perioden 1975–1989’, SMHI Report Hydrology No. 28, Swedish Metereological and Hydrological Institute, Norrköping, Sweden, 35 p (in Swedish).Google Scholar
  12. Bergström, S., 1992, ‘The HBV model–its structure and applications’, SMHI RH Report No 4. Swedish Meteorological and Hydrological Institute, Norrköping, Sweden.Google Scholar
  13. Beven, K., 1989, ‘Change ideas in hydrology: The case of physically based models’, J. Hydrol. 105, 157–172.Google Scholar
  14. Beven, K. J. and Kirkby, M. J., 1979, ‘A Physically based variable contributing area model of basin hydrology’, Hydrol. Sci. Bull. 24(1), 43–69.Google Scholar
  15. Beven, K. J., Kirkby, M. J., Schofield, N., and Tagg, A. F., 1984, ‘Testing a physically-based flood forecasting model (TOPMODEL) for three U.K. catchments’, J. Hydrol. 69, 119– 143.Google Scholar
  16. Budyko, M. I., 1955, ‘On the determination of evaporation from the land surface’, Meteorol. Gdrol, 1, 52–58 (in Russian).Google Scholar
  17. Budyko, M-I. and Zubenok, L. I., 1961, ‘On the determination of evaporation from the land surface’, Izv. Akad. Nauk SSSR Ser. Geogr. 6, 3–17.Google Scholar
  18. Bultot, F. and Dupriez, G. L., 1976, ‘Conceptual hydrologic model for an average-sized catchment area: Concepts and relationships’, J. Hydrol. 29, 251–272.Google Scholar
  19. Bultot, F., Coppens, A., Dupriez, G. L., Gellens, D., and Meulenberghs, F., 1988, ‘Repercussions of a CO2-doubling on the water cycle and on the water balance: A case study for Belgium’, J. Hydrol. 99, 319–347.Google Scholar
  20. Bultot, F., Gellens, D., Spreafico, M., and Schädler, B., 1992, ‘Repercussions of CO2 doubling on the water balance: A case study in Switzerland’, J. Hydrol. 137, 199–208.Google Scholar
  21. Burnash, R. J. C., Ferral, R. L., and McGuire, R. A., 1973, ‘A generalized streamflow simulation system, conceptual modeling for digital computer’, U.S. Department of Commerce, National Weather Service and State of California, Department of Water Resources, Sacramento, CA.Google Scholar
  22. Crawford, N. H. and Linsley, R. K., 1964, ‘A conceptual model of hydrologic cycle’, IAHS Publication No. 63, 573–587.Google Scholar
  23. Dingman, S. L., 1994, Physical Hydrology, Prentice Hall, Inc., Englewood Cliffs, NJ.Google Scholar
  24. Dolman, A. J., Hall, A. J., Kavvas, M. L., Oki, T., and Pomeroy, J. W. (eds), 2001, Soil-Vegetation-Atmosphere Transfer Schemes and Large-Scale Hydrological Models IAHS Publication No. 270.Google Scholar
  25. Dooge, J. C. I., 1992, ‘Hydrologic models and climate change’, J. Geophys. Res. D3(97), 2677–2686.Google Scholar
  26. Dyck, S., 1983, ‘Overview on the present status of the concepts of water balance models’, IAHS Publication No. 148, 3–19.Google Scholar
  27. Ewen, J. and Parkin, G., 1996, ‘Validation of catchment models for predicting land-use and climate change impacts 1: Method’, J. Hydrol. 175, 583–594.Google Scholar
  28. Fernandez, W., Vogel, R. M., and Sankarasubramanian, A., 2000, ‘Regional calibration of a watershed model’, Hydrol. Sci. J. 45, 689–707.Google Scholar
  29. Fleming, G., 1975, Computer Simulation Techniques in Hydrology, Elsevier, New York.Google Scholar
  30. Gottschalk, L., Beldring, S., Engeland, K., Tallaksen, L., Saelthun, N-R, Kolberg, S., and Motovilov, Y., 2001, ‘Regional/macroscale hydrological modelling: A Scandinavian experience’, Hydrol. Sci. J. 46(3), 1–23.Google Scholar
  31. Guo, S., Wang, J. and Yang, J., 2001, ‘A semi-distributed hydrological model and its application in a macroscale basin in China’, IAHS Publication No. 270, 167–174.Google Scholar
  32. Hendrickson, J. D., Sorooshian, S., and Brazil, L. E., 1988, ‘Comparison of Newton-Type and direct search algorithms for calibration of conceptual rainfall-runoff models’, Water Resour. Res. 24(2), 691–700.Google Scholar
  33. Hultcrantz, K. (ed), 1997, ‘Comprehensive Assessment of Freshwater Resources of the World. The final report (E/CN.17/1997/9), prepared by a Steering Committee consisting of representatives for UN/DPCSD, UN/DDSMS, FAO, UNEP, WMO, UNESCO, WHO, UNDP, UNIDO, The World Bank. Stockholm Environment Institute, 59 pp’,Google Scholar
  34. IAHR, 1994, ‘Publication of guidelines for validation documents and call for discussion’, Int. Assoc. Hydraul. Res. Bull. 11, 41.Google Scholar
  35. James, L. D., 1972, ‘Hydrologic modelling, parameter estimation and watershed characteristics’, J. Hydrol. 17, 283–307.Google Scholar
  36. Jarboe, J. E. and Haan, C. T., 1974, ‘Calibrating a water yield model for small ungaged watersheds’, Water. Resour. Res. 10(2), 256–262.Google Scholar
  37. Kim, W., Arai, T., Kanae, S., Oki, T., and Musiake, K., 2001, ‘Application of the simple biosphere model (sib2) to a paddy field for a period of growing season in GAME-tropics’, J. Meteo. Soc. Jpn. 79(1B), 387–400.Google Scholar
  38. 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, 1547–1599.Google Scholar
  39. Klemes, V., 1986, ‘Operational testing of hydrological simulation’, Hydrol. Sci. J. 31, 13–24.Google Scholar
  40. Leavesley, G. H., 1994, ‘Modelling the effects of climate change on water resources–A review’, Climatic Change 28, 159–177.Google Scholar
  41. Liang, X., Lettenmaier, D. P., Wood, E., and Burges, S. J., 1994, ‘A simple hydrologically based model of land surface water and energy fluxes for general circulation models’, J. Geophys. Res. 99(D7), 14415–14428.Google Scholar
  42. Liston, G. E., Sud, Y. C., and Wood, E. F., 1994, ‘Evaluating GCM land surface hydrology parameterisations by computing river discharges using a runoff routing model: Application to the Mississippi Basin’, J. Appl. Meteorol. 33, 394–404.Google Scholar
  43. Loague, K. M., 1990, ‘R-5 revisited 2. Reevaluation of a quasi-physically based rainfall-runoff model with supplemental information’, Water Resour. Res. 21, 973–987.Google Scholar
  44. Loaiciga, H. A., Valdes, J. B., Vogel, R., Garvey, J., and Schwarz, H., 1996, ‘Global warming and the hydrologic cycle’, J. Hydrol. 174, 83–127.Google Scholar
  45. Ma, X., Fukushima, Y., Hiyama, T., Hashimoto, T., and Ohata, T., 2000, ‘A macro-scale hydrological analysis of the Lena River basin’, Hydrol. Process. 14, 639–651.Google Scholar
  46. Magette, W. L., Shanholtz, V. O., and Carr, J. C., 1976, ‘Estimating selected parameters for the Kentucky watershed model from watershed characteristics’, Water Resour. Res. 12(3), 472– 476.Google Scholar
  47. Maidment, D. R., 1996, ‘GIS and hydrologic modelling: An assessment of progress. Presented at The Third International Conference on GIS and Environmental Modeling’, January 22–26, Santa Fe, New Mexico.Google Scholar
  48. Matheussen, B., Kirschbaum, R. L., Goodman, I. A., O’Donnell, G. M., and Lettenmaier, D. P., 2000, ‘Effects of land cover change on streamflow in the interior Columbia River basin (U.S.A. and Canada)’, Hydrol. Process. 14, 867–885.Google Scholar
  49. Mintz, Y. and Walker, G. K., 1993, ‘Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature’, J. Appl. Meteorol. 32, 1305–1334.Google Scholar
  50. Müller-Wohlfeil, Dirk-I., Xu, C-Y, and Iversen, H. L., 2003, ‘Estimation of monthly river discharge from Danish catchments’, Nordic Hydrol. 34(1), 295–320.Google Scholar
  51. Nash, J. E. and Sutcliffe, J., 1970, ‘River flow forecasting through conceptual models Part 1. A discussion of principles’, J. Hydrol. 10, 282–290.Google Scholar
  52. Nash, L. and Gleick, P., 1993, ‘The Colorado River basin and climate change. Rep’, EPA 230-R-93-009, United States Environmental Agency, Washington, DC.Google Scholar
  53. Nathan, R. J., McMahon, T. A., and Finlayson, B. L., 1988, ‘The impact of the Greenhouse effect on catchment hydrology and storage-yield relationships in both winter and summer rainfall zones’, In G. I. Pearman (ed), Greenhouse, Planning for Climate Change, Division of Atmospheric Research, CSIRO, East Melbourne, Australia.Google Scholar
  54. Nemec, J. and Schaake, J., 1982, ‘Sensitivity of water resources system to climate variation’, Hydrol. Sci. J. 2, 327–343.Google Scholar
  55. Ng, H. Y. F. and Marsalek, J., 1992, ‘Sensitivity of streamflow simulation to changes in climatic inputs’, Nordic Hydrol. 23, 257–272.Google Scholar
  56. Nijssen, B., Lettenmaier, D. P., Liang, X., Wetzel, S. W., and Wood, E., 1997, ‘Streamflow simulation for continental-scale river basins’, Water Resour. Res. 33(1), 711–724.Google Scholar
  57. Ol’dekop, E. M., 1911, ‘On evaporation from the surface of river basins’, Tr. Meteorol. Observ. Iur’evskogo Univ. Tartu., 4.Google Scholar
  58. Oreskes, N., Shrader-Frechette, K., Belitz, K., 1994, ‘Verification, validation and confirmation of numerical models in earth sciences’, Sciences 264, 641–646.Google Scholar
  59. Pickup, G., 1977, ‘Testing the efficiencies of algorithms and strategies for automatic calibration of rainfall runoff models’, Hydrol. Sci. Bull. 22(2), 257–274.Google Scholar
  60. Pike, J. G., 1964, ‘The estimation of annual runoff from meteorological data in a tropical climate’, J. Hydrol. 2, 116–123.Google Scholar
  61. Porter, J. W. and McMahon, T. A., 1971, ‘A model for the simulation of streamflow data from climatic records’, J. Hydrol. 13, 297–324.Google Scholar
  62. Refsgaard and Knudsen, 1996, ‘Operational validation and intercomparison of different typs of hydrological models’, Water Resour. Res. 32(7), 2189–2202.Google Scholar
  63. Refsgaard, J. C., 1997, ‘Parameterisation, calibration and validation of distributed hydrological models’, J. Hydrol. 198, 69–97.Google Scholar
  64. Rosenbrock, H. H., 1960, ‘An automatic method of finding the greatest of least value of a function’, Comput. J. 3, 175–184.Google Scholar
  65. Rosso, R., 1994, ‘An introduction to spatially distributed modelling of basin response’, in R. Rosso, A Peano, I. Becchi, G. A. Bemporad (eds), Advances in Distributed Hydrology, Water Resources Publications, Portland, OR, USA, pp. 3–30.Google Scholar
  66. Rowntree, P., 1989, The Needs of Climate Modellers for Water Runoff Data. Workshop on Global Runoff Data Sets and Grid Estimation, 10–15 November 1988, Koblenz. World Climate Programme, WMO, June 1989, Geneva.Google Scholar
  67. Schaake, J. C. and Liu, C., 1989, ‘Development and application of simple water balance models to understand the relationship between climate and water resources. New Directions for Surface Water Modeling (Proceedings of the Baltimore Symposium, May 1989)’, IAHS Publication No. 181.Google Scholar
  68. Schneiderman, E. M., Pierson, D. C., Lounsbury, D. G., and Zion, M. S., 2002, ‘Modelling the hydrochemistry of the Cannonsville watershed with generalized watershed loading functions (GWLF)’, J. Am. Water Resour. Assoc. 38(2), 1323–1347.Google Scholar
  69. Schreiber, P., 1904, ‘On the relationship between precipitation and the runoff of rivers in Central Europe’, Z. Meteorol. 21, 441–452.Google Scholar
  70. Seibert, J., 1999, ‘Regionalisation of parameters for a conceptual rainfall-runoff model’, Agricultural and Forest Meteorology 98–99 pp. 279–293.Google Scholar
  71. Seibert, J., 2000, ‘Multi-criteria calibration of a conceptual rainfall-runoff model using a genetic algorithm’, Hydrol. Earth Sys. Sci. 4(2), 215–224.Google Scholar
  72. Servat, E. and Dezetter, A., 1993, ‘Rainfall-runoff modelling and water resources assessment in north-western Ivory Coast. Tentative extension to ungauged catchments’, J. Hydrol. 148, 231– 248.Google Scholar
  73. Shuttleworth, J. W., 1993, ‘Evaporation. Handbook of Hydrology’, D. R. Maimdent Editor, McGraw-Hill, Inc.Google Scholar
  74. Singh, V. P. (ed), 1995, ‘Computer Models of Watershed Hydrology’, Water Resources Publications, Littleton, Colorado.Google Scholar
  75. Singh, V. P. and Frevert, D. K., (eds), 2002a, ‘Mathematical Models of Large Watershed Hydrology’, Water Resources Publications, Highlands Ranch, Colorado.Google Scholar
  76. Singh, V. P. and Frevert, D. K. (eds), 2002b, ‘Mathematical Models of Small Watershed Hydrology and Applications’, Water Resources Publications, Highlands Ranch, Colorado.Google Scholar
  77. Singh, V. P. and Woolhiser, D. A., 2002, ‘Mathematical modeling of watershed hydrology’, J.Hydrol. Eng. 7, 270–292.Google Scholar
  78. Sivapalan, M., Ruprecht, J. K., and Viney, N. R., 1996a, ‘Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 1. Small catchment water balance model. Hydrol. Process. 10, 393–411.Google Scholar
  79. Sivapalan, M., Viney, N. R., and Jeevaraj, C. G., 1996b, Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 3. Coupled model of water and salt balances. Hydrol. Process. 10, 413–428.Google Scholar
  80. Sivapalan, M., Viney, N. R., and Jeevaraj, C. G., 1996c, ‘Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 3. The large catchment model’, Hydrol. Process. 10, 429–446Google Scholar
  81. Sorooshian, S., V. K. Gupta and J. L. Fulton, 1983, ‘Evaluation of maximum likelihood estimation techniques for conceptual rainfall-runoff models: Influence of calibration data variability and length on model credibility’, Water Resour. Res. 10(1), 251–259.Google Scholar
  82. Stamm, J. F., Wood, E. F., and Lettenmaier, D. P., 1994, ‘Sensitivity of a GCM simulation of global climate to the representation of land-surface hydrology’, J. Climate 7, 1218–1239.Google Scholar
  83. Thornthwaite, C. W., 1948, ‘An approach toward a rational classification of climate’, Geogr. Rev. 38(1), 55–94.Google Scholar
  84. Todini, E., 1996, ‘The ARNO rainfall-runoff model’, J. Hydrol. 175, 339–382.Google Scholar
  85. Tung, Y. K., Yeh, K. C., and Yang, J. C., 1997, ‘Regionalization of unit hydrograph parameters: 1. Comparison of regression analysis techniques’, Stoch. Hydrol. Hydraul. 11, 145–171.Google Scholar
  86. Turc, L., 1954, ‘The water balance of soils’, Relation between precipitation evaporation and flow. Ann. Agron. 5, 491–569.Google Scholar
  87. U.S. Environmental Protection Agency (U.S.E.P.A.), 1984, Users manual for hydrological simulation program-FORTRAN (HSPF), EPA-600/3-84-066, Environmental Research Laboratory, Athens, GA.Google Scholar
  88. Vandewiele, G. L. and Elias, A., 1995, ‘Monthly water balance of ungauged catchments obtained by geographical regionalization’, J. Hydrol. 170, 277–291.Google Scholar
  89. Vehviläinen, B. and Lohvansuu, J., 1991, ‘The effects of climate change on discharges and snow cover in Finland’, Hydrol. Sci. J. 36, 109–121.Google Scholar
  90. Vörösmarty, C. J., Gutowski, W. J., Person, M., Chen, T.-C., and Case, D., 1993, ‘Linked atmosphere-hydrology models at the macroscale’, IAHS Publication No. 214, 3–27.Google Scholar
  91. Watson, F. G. R., Vertessy, R. A., and Grayson, R. B., 1999, ‘Large-scale modelling of forest hydrological processes and their long-term effect on water yield’, Hydrol. Process. 13, 689–700.Google Scholar
  92. Weeks, W. D. and Ashkanasy, N. M., 1983, ‘Regional parameters for the Sacramento Model: A case study’, Hydrology and Water Resources Symposium, Hobart.Google Scholar
  93. Wen, C.-G. and Lee, C.-S., 1998. ‘A neural network approach to multiobjective optimization for water quality management in river basin’, Water Resour. Res. 34(3), 427–436.Google Scholar
  94. Wilby, R. L., Greenfield, B., and Glenny, C., 1994, ‘A coupled synoptic-hydrological model for climate change impact assessment’, J. Hydrol., 153, 265–290.Google Scholar
  95. Wilkinson, W. B. (Editor), 1993. Macroscale Modelling of the Hydrosphere. IAHS Publ. 212.Google Scholar
  96. Wood, E. F. (Editor), 1991, ‘Land Surface–Atmospheroc Interactions for Climate Modelling: Observations’, Models and Analysis. Kluwer Academic Publ. 314p.Google Scholar
  97. Wood, E. F., Lettenmaier, D. P., and Zartarian, V. G., 1992, ‘A land-surface hydrology parameterisation with subgrid variability for general circulation models’, J. Geophys. Res. 97(D3), 2717–2728.Google Scholar
  98. Xu C.-Y. and Singh, V. P., 1998, ‘A review on monthly water balance models for water resources investigations’, Water Resour. Manage. 12, 31–50.Google Scholar
  99. Xu, C.-Y., Seibert, J., and Halldin, S. 1996, ‘Regional water balance modelling in the NOPEX area: Development and application of monthly water balance models’, J. Hydrol. 180, 211–236.Google Scholar
  100. Xu, C.-Y., 1999a, ‘Operational testing of a water balance model for predicting climate change impacts’, Agri. Forest Meteorol. 98/99(1–4), 295–304.Google Scholar
  101. Xu, C.-Y., 1999b, ‘Estimation of parameters of a conceptual water balance model for ungauaged catchments’, Water Resour. Manage. 13(2), 353–368.Google Scholar
  102. Xu, C.-Y., 1999c, ‘Climate change and hydrologic models: A review of existing gaps and recent research developments’, Water Resour. Manage. 13(2), 369–382.Google Scholar
  103. Xu, C.-Y., 2000, ‘Modelling the effects of climate change on water resources in central Sweden’, Water Resour. Manage. 14, 177–189.Google Scholar
  104. Xu, C.-Y., 2003, ‘Testing the transferability of regression equations derived from small sub-catchments to large area in central Sweden’, Hydrology and Earth System Sciences, 7(3), 317–324.Google Scholar
  105. Yao, H. and Hashino, M., 2001, ‘A completely-formed distributed rainfall-runoff model for the catchment scale’, IAHS Publ. 270, 183–190.Google Scholar
  106. Zhao, R. J., 1992, ‘The Xinanjiang model applied in China’, J. Hydrol. 135, 371–381.Google Scholar
  107. Zhao, R. J., Zhang, Y. L., Fang, L. R., Liu, X. R., and Zhang, Q. S., 1980, ‘The Xinanjiang model. Hydrological forecasting proceedings, Oxford Symposium, IAHS Publication No’, 129, 351–356.Google Scholar

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© Kluwer Academic Publishers 2004

Authors and Affiliations

  1. 1.Department of Earth Sciences, HydrologyUppsala UniversityUppsalaSweden
  2. 2.Department of Civil and Environmental EngineeringLouisiana State UniversityBaton RougeU.S.A.
  3. 3.Nanjing Institute of Geography and Limnology, Chinese Academy of SciencesNanjingP. R. China

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