Do time-variable tracers aid the evaluation of hydrological model structure? A multimodel approach

Water Resources Research

Volumn 48, Issue 5, 2012, Pages

  McMillan, Hilary ^a   Tetzlaff, Doerthe ^b   Clark, Martyn ^c   Soulsby, Chris ^b  

^a NATIONAL INSTITUTE OF WATER AND ATMOSPHERIC RESEARCH   (New Zealand)

^b UNIVERSITY OF ABERDEEN   (United Kingdom)

^c NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGE DISTRIBUTION; COMPLEMENTARY TOOLS; FLOW PATHWAYS; FLOW SERIES; HYDROLOGICAL MODELS; HYPOTHESIS TESTING; KEY MODELING; MEAN TRANSIT TIME; MULTI-CRITERIA MODEL; MULTIMODEL APPROACH; NEAR-SURFACE; RAINFALL-RUNOFF MODELING; STRUCTURAL ERRORS; STRUCTURE EVALUATIONS; TIME VARIATIONS; TRACER CONCENTRATION; TRANSIT-TIME DISTRIBUTIONS; WATER MOVEMENTS;

CATCHMENTS; DYNAMICS; RUNOFF; STREAM FLOW;

SENSITIVITY ANALYSIS;

CATCHMENT; HYPOTHESIS TESTING; RAINFALL-RUNOFF MODELING; STREAMFLOW; TRACER;

SCOTLAND; UNITED KINGDOM;

EID: 84862064819     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2011WR011688     Document Type: Article

References (84)

1. Akaike, H. (1974), A new look at the statistical model identification, IEEE Trans. Autom. Control, 19(6), 716-723.
2. Andreassian, V., C. Perrin, and C. Michel (2004), Impact of imperfect potential evapotranspiration knowledge on the efficiency and parameters of watershed models, J. Hydrol., 286, 19-35.
3. Barnes, C. J., and M. Bonell (1996), Application of unit hydrograph techniques to solute transport in catchments, Hydrol. Processes, 10, 793-802.
4. Beck, M. B. (1987), Water-quality modelling-A review of the analysis of uncertainty, Water Resour. Res., 23, 1393-1442.
5. Bergstrom, S., B. Carlsson, and G. Sandberg (1985), Integrated modelling of runoff, alkalinity and pH on a daily base, Nord. Hydrol., 16, 89-104.
6. Beven, K. J. (2010), Preferential flows and travel time distributions: Defining adequate hypothesis tests for hydrological process models, Hydrol. Processes, 24, 1537-1547.
7. Beven, K. J., and M. J. Kirkby (1979), A physically based, variable contributing area model of basin hydrology, Hydrol. Sci. Bull., 24, 43-69.
8. Birkel, C., S. M. Dunn, D. Tetzlaff, and C. Soulsby (2010), Assessing the value of high-resolution isotope tracer data in the stepwise development of a lumped conceptual rainfall-runoff model, Hydrol. Processes, 24, 2335-2348.
9. Birkel, C., D. Tetzlaff, S. M. Dunn, and C. Soulsby (2011a), Using lumped conceptual rainfall-runoff models to simulate daily isotope variability with fractionation in a nested mesoscale catchment, Adv. Water Resour., 34, 383-394.
10. Birkel, C., D. Tetzlaff, S. M. Dunn, and C. Soulsby (2011b), Using time domain and geographic source tracers to conceptualize streamflow generation processes in lumped rainfall-runoff models, Water Resour. Res., 47, W02515, doi:10.1029/2010WR009547.
11. Birkel, C., C. Soulsby, D. Tetzlaff, S. Dunn, and L. Spezia (2012), Highfrequency storm event isotope sampling reveals time-variant transit time distributions and influence of diurnal cycles, Hydrol. Processes, 26, 308-316, doi:10.1002/hyp.8210.
12. Blöschl, G., andM. Sivapalan (1995), Scale issues in hydrological modeling-A review, Hydrol. Processes, 9, 251-290.
13. Botter, G., F. Peratoner, M. Putti, A. Zuliani, R. Zonta, A. Rinaldo, and M. Marani (2008), Observation and modeling of catchment-scale solute transport in the hydrologic response: A tracer study, Water Resour. Res., 44, W05409, doi:10.1029/2007WR006611.
14. Botter, G., E. Bertuzzo, and A. Rinaldo (2010), Transport in the hydrologic response: Travel time distributions, soil moisture dynamics, and the old water paradox, Water Resour. Res., 46, W03514, doi:10.1029/2009WR008371.
15. Botter, G., E. Bertuzzo, and A. Rinaldo (2011), Catchment residence and travel time distributions: The master equation, Geophys. Res. Lett., 38, L11403, doi:10.1029/2011GL047666.
16. Brooks, J. R., H. R. Barnard, R. Coulombe, and J. J. McDonnell (2010), Ecohydrologic separation of water between trees and streams in a Mediterranean climate, Nat. Geosci., 3, 100-104.
17. Burnash, R. J. C., R. L. Ferral, and R. A. McGuire (1973), A generalized streamflow simulation system: Conceptual modeling for digital computers, Technical Report, U.S. Natl. Weather Serv., Sacramento, CA.
18. Clark, M., H. McMillan, D. Collins, D. Kavetski, and R. Woods (2011a), Hydrological field data from a modeller's perspective: Part 2: processbased evaluation of model hypotheses, Hydrol. Processes, 25, 523-543.
19. Clark, M. P., and D. Kavetski (2010), Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes, Water Resour. Res., 46, W10510, doi:10.1029/2009WR008894.
20. Clark, M. P., A. G. Slater, D. E. Rupp, R. A. 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.
21. Clark, M. P., D. Kavetski, and F. Fenicia (2011b), Pursuing the method of multiple working hypotheses for hydrological modeling, Water Resour. Res., 47, W09301, doi:10.1029/2010WR009827.
22. Dawson, J. J. C., C. Soulsby, D. Tetzlaff, M. Hrachowitz, S. M. Dunn, and I. A. Malcolm (2008), Influence of hydrology and seasonality on DOC exports from three contrasting upland catchments, Biogeochemistry, 90, 93-113.
23. Dunn, S. M., J. J. McDonnell, and K. B. Vache (2007), Factors influencing the residence time of catchment waters: A virtual experiment approach, Water Resour. Res., 43, W06408, doi:10.1029/2006WR005393.
24. Dunn, S. M., C. Birkel, D. Tetzlaff, and C. Soulsby (2010), Transit time distributions of a conceptual model: Their characteristics and sensitivities, Hydrol. Processes, 24, 1719-1729.
25. Fenicia, F., H. H. G. Savenije, P.Matgen, and L. Pfister (2007), A comparison of alternative multiobjective calibration strategies for hydrological modeling, Water Resour. Res., 43,W03434, doi:10.1029/2006WR005098.
26. Fenicia, F., J. J. McDonnell, and H. H. G. Savenije (2008), Learning from model improvement : On the contribution of complementary data to process understanding, Water Resour. Res., 44(6), W06419, doi:10.1029/2007WR006386.
27. Fenicia, F., S. Wrede, D. Kavetski, L. Pfister, L. Hoffmann, H. H. G. Savenije, and J. J. McDonnell (2010), Assessing the impact of mixing assumptions on the estimation of streamwater mean residence time, Hydrol. Processes, 24, 1730-1741.
28. Godsey, S. E., et al. (2010), Generality of fractal 1/f scaling in catchment tracer time series, and its implications for catchment travel time distributions, Hydrol. Processes, 24, 1660-1671.
29. Gupta, H. V., T. Wagener, and Y. Q. Liu (2008), Reconciling theory with observations: Elements of a diagnostic approach to model evaluation, Hydrol. Processes, 22, 3802-3813.
30. Harman, C. J., M. Sivapalan, and P. Kumar (2009), Power law catchmentscale recessions arising from heterogeneous linear small-scale dynamics, Water Resour. Res., 45, W09404, doi:10.1029/2008WR007392.
31. Hrachowitz, M., C. Soulsby, D. Tetzlaff, J. J. C. Dawson, S. M. Dunn, and I. A. Malcolm (2009a), Using long-term data sets to understand transit times in contrasting headwater catchments, J. Hydrol., 367, 237-248.
32. Hrachowitz, M., C. Soulsby, D. Tetzlaff, J. J. C. Dawson, and I. A. Malcolm (2009b), Regionalization of transit time estimates in montane catchments by integrating landscape controls, Water Resour. Res., 45, W05421, doi:10.1029/2008WR007496.
33. Hrachowitz, M., C. Soulsby, D. Tetzlaff, I. A. Malcolm, and G. Schoups (2010), Gamma distribution models for transit time estimation in catchments: Physical interpretation of parameters and implications for timevariant transit time assessment, Water Resour. Res., 46, W10536, doi:10.1029/2010WR009148.
34. Hrachowitz, M., C. Soulsby, D. Tetzlaff, and I. A. Malcolm (2011), Sensitivity of mean transit time estimates to model conditioning and data availability, Hydrol. Processes, 25, 980-990.
35. Iorgulescu, I., K. J. Beven, and A. Musy (2005), Data-based modelling of runoff and chemical tracer concentrations in the Haute-Mentue research catchment (Switzerland), Hydrol. Processes, 19, 2557-2573.
36. Kavetski, D., and M. P. Clark (2010), Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction, Water Resour. Res., 46, W10511, doi:10.1029/ 2009WR008896.
37. Kavetski, D., F. Fenicia, and M. P. Clark (2011), Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment, Water Resour. Res., 47, W05501, doi:10.1029/2010WR009525.
38. Kirchner, J. W. (2006), Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology, Water Resour. Res., 42, W03S04, doi:10.1029/2005 WR004362.
39. Kirchner, J. W., X. H. Feng, and C. Neal (2000), Fractal stream chemistry and its implications for contaminant transport in catchments, Nature, 403, 524-527.
40. Kirchner, J. W., D. Tetzlaff, and C. Soulsby (2010), Comparing chloride and water isotopes as hydrological tracers in two Scottish catchments, Hydrol. Processes, 24, 1631-1645.
41. Krueger, T., J. N. Quinton, J. Freer, C. J. A. Macleod, G. S. Bilotta, R. E. Brazier, P. Butler, and P. M. Haygarth (2009), Uncertainties in data and models to describe event dynamics of agricultural sediment and phosphorus transfer, J. Environ. Qual., 38, 1137-1148.
42. Brazier, P. Butler, and P. M. Haygarth (2010), Ensemble evaluation of hydrological model hypotheses, Water Resour. Res., 46, W07516, doi:10.1029/2009WR007845.
43. Leavesley, G. H., R. W. Lichty, B. M. Troutman, and L. G. Saindon (1983), Precipitation-runoff modeling system: User's manual, U.S. Geol. Surv. Water Invest. Rep., 83-4238, 207 pp.
44. Lindstrom, G., and A. Rodhe (1992), Transit times of water in soil lysimeters from modeling of oxygen-18, Water Air Soil Pollut., 65(1-2), 83-100.
45. Lu, J. B., G. Sun, S. G. McNulty, and D. M. Amatya (2005), A comparison of six potential evapotranspiration methods for regional use in the southeastern United States, J. Am. Water Resour. Assoc., 41, 621-633.
46. McDonnell, J. J., et al. (2010), How old is streamwater? Open questions in catchment transit time conceptualization, modelling and analysis, Hydrol. Processes, 24, 1745-1754.
47. McGuire, K. J., and J. J. McDonnell (2006), A review and evaluation of catchment transit time modeling, J. Hydrol., 330, 543-563.
48. McGuire, K. J., and J. J. McDonnell (2010), Hydrological connectivity of hillslopes and streams: Characteristic time scales and nonlinearities, Water Resour. Res., 46(10), W10543, doi:10.1029/2010WR009341.
49. McGuire, K. J., M. Weiler, and J. J. McDonnell (2007), Integrating tracer experiments with modeling to assess runoff processes and water transit times, Adv. Water Resour., 30, 824-837.
50. McMillan, H., and M. Clark (2009), Rainfall-runoff model calibration using informal likelihood measures within aMarkov chainMonte Carlo sampling scheme,Water Resour. Res., 45,W04418, doi:10.1029/2008WR007288.
51. McMillan, H., J. Freer, F. Pappenberger, T. Krueger, and M. Clark (2010), Impacts of uncertain flow data on rainfall-runoff model calibration and discharge predictions, Hydrol. Processes, 24, 1270-1284.
52. McMillan, H., M. Clark, W. B. Bowden, M. J. Duncan, and R. Woods (2011), Hydrological field data from a modeller's perspective. Part 1: Diagnostic tests for model structure, Hydrol. Processes, 25, 511-522.
53. Miller, J. D., H. A. Anderson, R. C. Ferrier, and T. A. B. Walker (1990), Hydrochemical fluxes and their effects on stream acidity in two forested catchments in central Scotland, Forestry 63, 311-331.
54. Nyberg, L., A. Rodhe, and K. Bishop (1999), Water transit times and flow path from two line injections of 3H and 36Cl in a microcatchment at Gardsjön, Sweden, Hydrol. Processes, 13, 1557-1575.
55. Oda, T., Y. Asano, and M. Suzuki (2009), Transit time evaluation using a chloride concentration input step shift after forest cutting in a Japanese headwater catchment, Hydrol. Processes, 23(19), 2705-2713.
56. Page, T., K. J. Beven, J. Freer, and C. Neal (2007), Modelling the chloride signal at Plynlimon, Wales, using a modified dynamic TOPMODEL incorporating conservative chemical mixing (with uncertainty), Hydrol. Processes, 21(3), 292-307.
57. Pelletier, M. P. (1988), Uncertainties in the determination of river discharge: A literature review, Can. J. Civil Eng., 15, 834-850.
58. Phillips, F. M. (2010), Soil-water bypass, Nat. Geosci., 3, 77-78.
59. Reichert, P., and J. Mieleitner (2009), Analyzing input and structural uncertainty of nonlinear dynamic models with stochastic, time-dependent parameters, Water Resour. Res., 45,W10402, doi:10.1029/2009WR007814.
60. Rinaldo, A., G. Botter, E. Bertuzzo, A. Uccelli, T. Settin, and M. Marani (2006), Transport at basin scales: 1. Theoretical framework, Hydrol. Earth Syst. Sci., 10, 19-29.
61. Rinaldo, A., K. J. Beven, E. Bertuzzo, L. Nicotina, J. Davies, A. Fiori, D. Russo, and G. Botter (2011), Catchment travel time distributions and water flow in soils, Water Resour. Res., 47, W07537, doi:10.1029/2011WR010478.
62. Rodgers, P., C. Soulsby, and S. Waldron (2005a), Stable isotope tracers as diagnostic tools in upscaling flow path understanding and residence time estimates in a mountainous mesoscale catchment, Hydrol. Processes, 19, 2291-2307.
63. Rodgers, P., C. Soulsby, S. Waldron, and D. Tetzlaff (2005b), Using stable isotope tracers to assess hydrological flow paths, residence times and landscape influences in a nested mesoscale catchment, Hydrol. Earth Syst. Sci., 9, 139-155.
64. Savenije, H. H. G. (2009), HESS opinions "The art of hydrology," Hydrol. Earth Syst. Sci., 13, 157-161.
65. Schaefli, B., and H. V. Gupta (2007), Do Nash values have value?, Hydrol. Processes, 21, 2075-2080.
66. Seibert, J., and J. J. McDonnell (2002), On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration, Water Resour. Res., 3(11), 1241, doi:10.1029/2001WR000978.
67. Singh, V. P. (1995), Computer Models of Watershed Hydrology, p. 1130, Water Resources Publications, Highlands Ranch, Colorado.
68. Sivapalan M. (2009), The secret to 'doing better hydrological science': Change the question!, Hydrol. Processes, 23, 1391-1396.
69. Sivapalan, M., R. Grayson, and R. Woods (2004), Scale and scaling in hydrology, Hydrol. Processes, 18, 1369-1371.
70. Son, K., and M. Sivapalan (2007), Improving model structure and reducing parameter uncertainty in conceptual water balance models through the use of auxiliary data, Water Resour. Res., 43, W01415, doi:10.1029/2006WR005032.
71. Soulsby, C., and B. Reynolds (1993), Influence of soil hydrological pathways on stream aluminium chemistry at Llyn Brianne, Mid Wales, Environ. Pollut., 81, 51-60.
72. Soulsby, C., P. Rodgers, R. Smart, J. Dawson, and S. Dunn (2003), A tracerbased assessment of hydrological pathways at different spatial scales in a mesoscale Scottish catchment, Hydrol. Processes, 17, 759-777.
73. Soulsby, C., D. Tetzlaff, P. Rodgers, S. Dunn, and S. Waldron (2006), Runoff processes, stream water residence times and controlling landscape characteristics in a mesoscale catchment: An initial evaluation, J. Hydrol., 325, 197-221.
74. Speed, M., D. Tetzlaff, C. Soulsby, M. Hrachowitz, and S. Waldron (2010), Isotopic and geochemical tracers reveal similarities in transit times in contrasting mesoscale catchments, Hydrol. Processes, 24, 1211-1224.
75. Stewart, M. K., U. Morgenstern, and J. J. McDonnell (2010), Truncation of stream residence time: How the use of stable isotopes has skewed our concept of streamwater age and origin, Hydrol. Processes, 24, 1646-1659.
76. Tetzlaff, D., I. A. Malcolm, and C. Soulsby (2007a), Influence of forestry, environmental change and climatic variability on the hydrology, hydrochemistry and residence times of upland catchments, J. Hydrol., 346, 93-111.
77. Tetzlaff, D., S. Waldron, M. J. Brewer, and C. Soulsby (2007b), Assessing nested hydrological and hydrochemical behaviour of a mesoscale catchment using continuous tracer data, J. Hydrol., 336, 430-443.
78. Tetzlaff, D., J. Seibert, and C. Soulsby (2009), Inter-catchment comparison to assess the influence of topography and soils on catchment transit times in a geomorphic province; the Cairngorm mountains, Scotland, Hydrol. Processes, 23, 1874-1886.
79. Tetzlaff, D., M. J. Brewer, I. A. Malcolm, and C. Soulsby (2010), Storm flow and baseflow response to reduced acid deposition-using Bayesian compositional analysis in hydrograph separation with changing end members, Hydrol. Processes, 24, 2300-2312.
80. Turner, J. V., D. K. Macpherson, and R. A. Stokes (1987), The mechanisms of catchment flow processes using natural variations in deuterium and O-18, J. Hydrol., 94(1-2), 143-162.
81. Uhlenbrook, S., and C. Leibundgut (2002), Process-oriented catchment modelling and multiple-response validation, Hydrol. Processes, 16, 423-440.
82. Vache, K. B., and J. J. McDonnell (2006), A process-based rejectionist framework for evaluating catchment runoff model structure, Water Resour. Res., 42, W02409, doi:10.1029/2005WR004247.
83. Weiler, M., B. L. McGlynn, K. J. McGuire, and J. J. McDonnell (2003), How does rainfall become runoff? A combined tracer and runoff transfer function approach, Water Resour. Res., 39(11), 1315, doi:10.1029/2003WR002331.
84. Wood, E. F., D. P. Lettenmaier, and V. G. Zartarian (1992), A land-surface hydrology parameterization with subgrid variability for general-circulation models, J. Geophys. Res., 97(D3), 2717-2728.