Toward improved identification of hydrological models: A diagnostic evaluation of the "abcd" monthly water balance model for the conterminous United States

Water Resources Research

Volumn 46, Issue 8, 2010, Pages

  Martinez, Guillermo F ^a   Gupta, Hoshin V ^a  

^a UNIVERSITY OF ARIZONA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONVENTIONAL IDENTIFICATION; DATA REQUIREMENTS; DIAGNOSTIC MODEL; HYDROCLIMATIC; HYDROCLIMATIC VARIABLES; HYDROGEOLOGICAL CONDITIONS; HYDROLOGIC SYSTEMS; HYDROLOGICAL MODELS; MODEL ERRORS; MODEL PERFORMANCE; MODEL RESULTS; MODEL SELECTION; MONTHLY WATER BALANCE MODEL; RELEVANT COMPONENTS; SPATIAL VARIABILITY; SPATIO-TEMPORAL DYNAMICS; SPATIO-TEMPORAL SCALE; WATER BALANCE;

CATCHMENTS; DATA PROCESSING; MODEL STRUCTURES; RUNOFF;

IDENTIFICATION (CONTROL SYSTEMS);

CATCHMENT; DATA PROCESSING; ERROR ANALYSIS; HYDROGEOLOGY; HYDROLOGICAL MODELING; HYDROLOGICAL REGIME; IDENTIFICATION METHOD; MODEL TEST; SPATIAL VARIATION; SPATIOTEMPORAL ANALYSIS; WATER BUDGET;

UNITED STATES;

EID: 77955574732     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2009WR008294     Document Type: Article

References (76)

1. Acreman, M. C., and C. D. Sinclair (1986), Classification of drainage basins according to their physical characteristics; an application for flood frequency analysis in Scotland, J. Hydrol., 84, 365-380, doi:10.1016/ 0022-1694(86)90134-90144
2. Alley, W. M. (1984), Treatment of evapotranspiration, soil moisture accounting, and aquifer recharge in monthly water balance models, Water Resour. Res., 20, 1137-1149, doi:10.1029/WR020i008p01137.
3. Alley, W. M. (1985), Water balance models in one-month-ahead streamflow forecasting, Water Resour. Res., 21, 597-606, doi:10.1029/ WR021i004p00597.
4. Andreassian, V., J. Lerat, C. Loumagne, T. Mathevet, C. Michel, L. Oudin, and C. Perrin (2007), What is really undermining hydrologic science today?, Hydrol. Processes, 21, 2819-2822, doi:10.1002/hyp.6854. (Pubitemid 47559605)
5. Arnell, N. W. (1999), Climate change and global water resources, Global Environ. Change, 9, S31-S49, doi:10.1016/S0959-3780(99)00017-5. (Pubitemid 29523847)
6. Arnold, J. G., R. Srinivasan, R. S. Muttiah, and P. M. Allen (1999), Continental scale simulation of the hydrologic balance, J. Am. Water Resour. Assoc., 35, 1037-1051, doi:10.1111/j.1752-1688.1999.tb04192.x.
7. Bai, Y., T. Wagener, and P. Reed (2009), A top-down framework for watershed model evaluation and selection under uncertainty, Environ. Modell. Software, 24, 901-916, doi:10.1016/j.envsoft.2008.12.012.
8. Beran, B., and M. Piasecki (2008), Availability and coverage of hydrologic data in the US geological survey National Water Information System (NWIS) and US Environmental Protection Agency Storage and Retrieval System (STORET), Earth Sci. Inf., 1, 119-129, doi:10.1007/s12145-008-0015-2.
9. Berger, K. P., and D. Entekhabi (2001), Basin hydrologic response relations to distributed physiographic descriptors and climate, J. Hydrol., 247, 169-182, doi:10.1016/S0022-1694(01)00383-3. (Pubitemid 32631985)
10. Blöschl, G. (2006), Hydrologic synthesis: Across processes, places, and scales, Water Resour. Res., 42, W03S02, doi:10.1029/2005WR004319.
11. Budyko, M. I. (1974), Climate and Life, Academic, San Diego, Calif.
12. Clark, M. P., A. G. Slater, D. E. Rupp, R. Woods, J. A. Vrugt, H. V. Gupta, T. Wagener, and L. E. Hay (2008), Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models, Water Resour. Res., 44, W00B02, doi:10.1029/2007WR006735.
13. Daly, C., R. P. Neilson, and D. L. Phillips (1994), A statistical-topographic model for mapping climatological precipitation over mountainous terrain, J. Appl. Meteorol., 33, 140-158, doi:10.1175/1520- 0450(1994) 033<0140:ASTMFM>2.0.CO;2.
14. Duan, Q., S. Sorooshian, and H. V. Gupta (1992), Effective and efficient global optimization for conceptual rainfall-runoff models, Water Resour. Res., 28, 1015-1031, doi:10.1029/91WR02985.
15. Duan, Q., J. Schaake, V. Andreassian, S. Franks, G. Goteti, H. V. Gupta, Y. M. Gusev, F. Habets, A. Hall, and L. Hay (2006), Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops, J. Hydrol., 320, 3-17, doi:10.1016/j.jhydrol.2005. 07.031.
16. Dunne, T. (1983), Relation of field studies and modeling in the prediction of storm runoff, J. Hydrol., 65, 25-48, doi:10.1016/0022-1694(83) 90209-3.
17. Ebtehaj, M., H. Moradkhani, and H. V. Gupta (2010), Improving robustness of hydrologic parameter estimation by the use of moving block bootstrap, Water Resour. Res., doi:10.1029/2009WR007981, in press.
18. Euliss, N. H., D. A. Wrubleski, and D. M. Mushet (1999), Wetlands of the Prairie Pothole region: Invertebrate species composition, ecology, and management, in Invertebrates in Freshwater Wetlands of North America: Ecology and Management, edited by D. P. Batzer, R. B. Rader, and S. A. Wissinger, pp. 471-514, John Wiley, New York.
19. Fernandez, W., R. M. Vogel, and A. Sankarasubramanian (2000), Regional calibration of a watershed model, Hydrol. Sci. J., 45, 689-707, doi:10.1080/02626660009492371.
20. Gleick, P. H. (1987), The development and testing of a water balance model for climate impact assessment: Modeling the Sacramento Basin, Water Resour. Res., 23, 1049-1061, doi:10.1029/WR023i006p01049.
21. Guo, S., J. Wang, L. Xiong, A. Ying, and D. Li (2002), A macro-scale and semi-distributed monthly water balance model to predict climate change impacts in China, J. Hydrol., 268, 1-15, doi:10.1016/S0022-1694(02) 00075-6.
22. Gupta, H. V., T. Wagener, and Y. Liu (2008), Reconciling theory with observations: Elements of a diagnostic approach to model evaluation, Hydrol. Processes, 22, 3802-3813, doi:10.1002/hyp.6989.
23. Gupta, H. V., H. Kling, K. K. Yilmaz, and G. F. Martinez (2009), Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80-91, doi:10.1016/j.jhydrol.2009.08.003.
24. Gupta, V. K., and S. Sorooshian (1985), Automatic calibration of conceptual catchment models using derivative-based optimization algorithms, Water Resour. Res., 21, 473-485, doi:10.1029/WR021i004p00473.
25. Hargreaves, G. H., and Z. A. Samani (1982), Estimating potential evapotranspiration, J. Irrig. Drain. Eng., 108, 225-230.
26. Hay, L. E., and G. J. McCabe (2002), Spatial variability in water-balance model performance in the conterminousUnited States, J. Am. Water Resour. Assoc., 38, 847-860, doi:10.1111/j.1752-1688.2002.tb01001.x.
27. Hughes, M. G., and D. A. Robinson (1996), Historical snow cover variability in the Great Plains region of the USA: 1910 through to 1993, Int. J. Climatol., 16, 1005-1018, doi:10.1002/(SICI)1097-0088(199609)16:9<1005:: AID-JOC63>3.0.CO;2-0.
28. Institute of Hydrology (Ed.) (1980), Low Flow Studies, Inst. of Hydrol., Wallingford, U. K.
29. Kling, H., and H. P. Nachtnebel (2009), A method for the regional estimation of runoff separation parameters for hydrological modelling, J. Hydrol., 364, 163-174, doi:10.1016/j.jhydrol.2008.10.015.
30. Kling, H., J. Fürst, and H. P. Nachtnebel (2006), Seasonal, spatially distributed modelling of accumulation and melting of snow for computing runoff in a long-term, large-basin water balance model, Hydrol. Processes, 20, 2141-2156, doi:10.1002/hyp.6203. (Pubitemid 44027013)
31. Kumar, P., M. Folk, J. C. Alameda, M. Markus, and P. Bajcsy (2006), Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling, CRC Press, Boca Raton, Fla.
32. Lins, H. F. (1997), Regional streamflow regimes and hydroclimatology of the United States, Water Resour. Res., 33, 1655-1667, doi:10.1029/ 97WR00615.
33. Makhlouf, Z., and C. Michel (1994), A two-parameter monthly water balance model for French watersheds, J. Hydrol., 162, 299-318, doi:10.1016/0022- 1694(94)90233-X.
34. Martinez, G. F. (2007), Diagnostic evaluation of watershed models, M.S. thesis, Univ. of Ariz., Tucson.
35. Maurer, E. P., A. W. Wood, J. C. Adam, D. P. Lettenmaier, and B. Nijssen (2002), A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States, J. Clim., 15, 3237-3251, doi:10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2.
36. McCabe, G. J., and D. M. Wolock (1999), General-circulation-model simulations of future snowpack in the western United States, J. Am. Water Resour. Assoc., 35, 1473-1484, doi:10.1111/j.1752-1688.1999.tb04231.x.
37. McDonnell, J. J., and R. Woods (2004), On the need for catchment classification, J. Hydrol., 299, 2-3.
38. Milly, P. C. D. (1994), Climate, soil water storage, and the average annual water balance, Water Resour. Res., 30, 2143-2156, doi:10.1029/ 94WR00586.
39. Milly, P. C. D., J. Betancourt, M. Falkenmark, R. M. Hirsch, Z. W. Kundzewicz, D. P. Lettenmaier, and R. J. Stouffer (2008), Stationarity is dead: Whither water management?, Science, 319, 573-574, doi:10.1126/science.1151915. (Pubitemid 351197047)
40. Mouelhi, S., C. Michel, C. Perrin, and V. Andréassian (2006), Stepwise development of a two-parameter monthly water balance model, J. Hydrol., 318, 200-214, doi:10.1016/j.jhydrol.2005.06.014. (Pubitemid 43120795)
41. Nash, J. E., and J. V. Sutcliffe (1970), River flow forecasting through conceptual models part I-A discussion of principles, J. Hydrol., 10, 282, doi:10.1016/0022-1694(70)90255-6.
42. National Climatic Data Center (2002), Climate Atlas of the United States [CD-rOM], Natl. Oceanic and Atmos. Admin., U.S. Dep. of Commer., Asheville, N. C.
43. Neuman, S. P. (2003), Maximum likelihood Bayesian averaging of uncertain model predictions, Stochastic Environ. Res. Risk Assess., 17, 291-305, doi:10.1007/s00477-003-0151-7. (Pubitemid 38013163)
44. Perrin, C., C. Michel, and V. Andreassian (2001), Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments, J. Hydrol., 242, 275-301, doi:10.1016/S0022-1694(00)00393-0. (Pubitemid 32169968)
45. Perrin, C., V. Andréassian, C. R. Serna, T. Mathevet, and N. Le Moine (2008), Discrete parameterization of hydrological models: Evaluating the use of parameter sets libraries over 900 catchments, Water Resour. Res., 44, W08447, doi:10.1029/2007WR006579.
46. Rodell, M., P. R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C. J. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, and M. Bosilovich (2004), The global land data assimilation system, Bull. Am. Meteorol. Soc., 85, 381-394, doi:10.1175/BAMS-85-3-381.
47. Sankarasubramanian, A., and R. M. Vogel (2002a), Annual hydroclimatology of the United States, Water Resour. Res., 38(6), 1083, doi:10.1029/ 2001WR000619.
48. Sankarasubramanian, A., and R. M. Vogel (2002b), Comment on the paper: "Basin hydrologic response relations to distributed physiographic descriptors and climate" by Karen Plaut Berger, Dara Entekhabi, 2001. Journal of Hydrology 247, 169-182, J. Hydrol., 263, 257-261.
49. Savenije, H. H. G. (2008), The art of hydrology, Hydrol. Earth Syst. Sci. Discuss., 5, 3157-3167, doi:10.5194/hessd-5-3157-2008.
50. Schaefli, B., and H. V. Gupta (2007), Do Nash values have value?, Hydrol. Processes, 21, 2075-2080, doi:10.1002/hyp.6825. (Pubitemid 47098253)
51. Seaber, P. R., F. P. Kapinos, and G. L. Knapp (1987), Hydrologic unit maps, U.S. Geol. Surv. Water Supply Pap., 2294, 61 pp.
52. Sivapalan, M. (2005), Pattern, process and function: Elements of a unified theory of hydrology at the catchment scale, in Encyclopedia of Hydrological Sciences, vol.13, edited by M. G. Anderson, pp. 193-219, John Wiley, Chichester, U. K.
53. Sivapalan, M., J. Schaake, and J. Sapporo (2003), PUB science and implementation plan, Int. Assoc. of Hydrol. Sci., Gentbrugge, Belgium.
54. Slack, J. R., A. M. Lumb, and J. M. Landwehr (1993), Hydro-climatic Data Network (HCDN) streamflow data set, 1874-1988, U.S. Geol. Surv. Water Resour. Invest. Rep., 93-4076.
55. Smith, M. B., D. J. Seo, V. I. Koren, S. M. Reed, Z. Zhang, Q. Duan, F. Moreda, and S. Cong (2004), The distributed model intercomparison project (DMIP): Motivation and experiment design, J. Hydrol., 298, 4-26, doi:10.1016/j.jhydrol.2004.03.040. (Pubitemid 39098766)
56. Sturm, M., J. Holmgren, and G. E. Liston (1995), A seasonal snow cover classification system for local to global applications, J. Clim., 8, 1261-1283, doi:10.1175/1520-0442(1995)008<1261:ASSCCS>2.0.CO;2.
57. Thomas, H. A. (1981), Improved methods for national water assessment: Final report, U.S. Geol. Surv. Water Resour. Contract WR15249270, 44 pp.
58. Thomson, A. M., N. J. Rosenberg, R. C. Izaurralde, and R. A. Brown (2005), Climate change impacts for the conterminous USA: An integrated assessment-Part 2: Models and validation, Clim. Change, 69, 27-41, doi:10.1007/s10584-005-3609-4. (Pubitemid 40534143)
59. Thornthwaite, C. W. (1948), An approach toward a rational classification of climate, Geogr. Rev., 38, 55-94, doi:10.2307/210739.
60. Vandewiele, G. L., and A. Elias (1995), Monthly water balance of ungauged catchments obtained by geographical regionalization, J. Hydrol., 170, 277-291, doi:10.1016/0022-1694(95)02681-E.
61. Vandewiele, G. L., C.-Y. Xu, and N.-L. Win (1992), Methodology and comparative study of monthly water balance models in Belgium, China and Burma, J. Hydrol., 134, 315-347, doi:10.1016/0022-1694(92) 90041-S.
62. Vogel, R. M., and A. Sankarasubramanian (2005), USGS Hydro-climatic Data Network (HCDN): Monthly Climate Database, 1951-1990, vol.2005, http://daac.ornl.gov/cgi-bin/dsviewer.pl-ds-id=810, Oak Ridge Natl. Lab. Distributed Active Arch. Cent., Oak Ridge, Tenn.
63. Vrugt, J. A., H. V. Gupta, W. Bouten, and S. Sorooshian (2003), A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters, Water Resour. Res., 39(8), 1201, doi:10.1029/2002WR001642.
64. Wagener, T., M. Sivapalan, P. A. Troch, and R. Woods (2007), Catchment classification and hydrology similarity, Geogr. Compass, 1(4), 901-931, doi:10.1111/j.1749-8198.2007.00039.x.
65. Walter, M. T., E. S. Brooks, D. K. McCool, L. G. King, M. Molnau, and J. Boll (2005), Process-based snowmelt modeling: Does it require more input data than temperature-index modeling?, J. Hydrol., 300, 65-75, doi:10.1016/j.jhydrol. 2004.05.002. (Pubitemid 39588505)
66. Wang, G., J. Xia, and J. Chen (2009), Quantification of effects of climate variations and human activities on runoff by a monthly water balance model: A case study of the Chaobai River basin in northern China, Water Resour. Res., 43, W00A11, doi:10.1029/2007WR006768.
67. Wardrop, D. H., J. A. Bishop, M. Easterling, K. Hychka, W. Myers, G. P. Patil, and C. Taillie (2005), Use of landscape and land use parameters for classification and characterization of watersheds in the mid-atlantic across five physiographic provinces, Environ. Ecol. Stat., 12, 209-223, doi:10.1007/s10651-005-1042-5. (Pubitemid 40782278)
68. Winter, T. C. (2001), The concept of hydrologic landscapes, J. Am. Water Resour. Assoc., 37, 335-349, doi:10.1111/j.1752-1688.2001.tb00973.x.
69. Wolock, D. M., and G. J. McCabe (1999), Explaining spatial variability in mean annual runoff in the conterminous United States, Clim. Res., 11, 149-159, doi:10.3354/cr011149.
70. Wolock, D. M., T. C. Winter, and G. McMahon (2004), Delineation and evaluation of hydrologic-Landscape regions in the United States using geographic information system tools and multivariate statistical analyses, Environ. Manage. N. Y., 34, Suppl. 1, S71-S88, doi:10.1007/s00267-003-5077-9.
71. Xiong, L., and S. Guo (1999), A two-parameter monthly water balance model and its application, J. Hydrol., 216, 111-123, doi:10.1016/ S0022-1694(98)00297-302
72. Xu, C.-Y., and V. P. Singh (1998), A review on monthly water balance models for water resources investigations, Water Resour. Manage., 12, 20-50, doi:10.1023/A:1007916816469.
73. Xu, C.-Y., and G. L. Vandewiele (1995), Parsimonious monthly rainfallrunoff models for humid basins with different input requirements, Adv. Water Resour., 18, 39-48, doi:10.1016/0309-1708(94)00017-Y.
74. Yadav, M., T. Wagener, and H. V. Gupta (2007), Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins, Adv. Water Resour., 30, 1756-1774, doi:10.1016/j.advwatres. 2007.01.005. (Pubitemid 46712120)
75. Ye, M., P. D. Meyer, and S. P. Neuman (2008), On model selection criteria in multimodel analysis, Water Resour. Res., 44, W03428, doi:10.1029/ 2008WR006803.
76. Zhang, L., N. Potter, K. Hickel, Y. Zhang, and Q. Shao (2008), Water balance modeling over variable time scales based on the Budyko framework-Model development and testing, J. Hydrol., 360, 117-131, doi:10.1016/j.jhydrol.2008. 07.021.