Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China

Journal of Hydrology

Volumn 358, Issue 1-2, 2008, Pages 1-23

  Yang, Jing ^a   Reichert, Peter ^a   Abbaspour, K C ^a   Xia, Jun ^b   Yang, Hong ^a  

^a SWISS FEDERAL INSTITUTE OF AQUATIC SCIENCE AND TECHNOLOGY   (Switzerland)

^b INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

Author keywords

Bayesian inference; GLUE; ParaSol; SUFI 2; Uncertainty analysis; Watershed modeling

Indexed keywords

BAYESIAN NETWORKS; CLIMATE CHANGE; COMPUTATIONAL EFFICIENCY; EARTH SCIENCES; ESTIMATION; FUNCTION EVALUATION; HYDRAULIC MODELS; HYDROLOGY; INFERENCE ENGINES; LAND USE; LANDFORMS; MARKOV PROCESSES; PARAMETER ESTIMATION; PHILOSOPHICAL ASPECTS; POLLUTION; REUSABILITY; SEQUENTIAL SWITCHING; STATISTICAL TESTS; WATER; WATER MANAGEMENT; WATER POLLUTION CONTROL; WATERSHEDS;

(001) PARAMETER; ALTERNATIVE MANAGEMENT; ANALYSIS TECHNIQUES; APPLIED (CO); AUTOREGRESSIVE ERROR MODEL; BAYESIAN; BAYESIAN FRAMEWORKS; BAYESIAN INFERENCES; BEST ESTIMATES (BE); COMPARISON RESULTS; CONTINUOUS-TIME (CT); ELSEVIER (CO); GENERALIZED LIKELIHOOD UNCERTAINTY ESTIMATION (GLUE); IMPORTANCE SAMPLING (IS); LAND USE CHANGES; LIKELIHOOD FUNCTIONS; MARKOV CHAIN MONTE CARLO (MCMC); OBJECTIVE FUNCTION (OF); PARAMETER DISTRIBUTIONS; PREDICTION UNCERTAINTY; SEQUENTIAL UNCERTAINTY FITTING (SUFI); SOIL AND WATER ASSESSMENT TOOL (SWAT); WATER ALLOCATIONS; WATERSHED MODELLING;

UNCERTAINTY ANALYSIS;

ALGORITHM; COMPARATIVE STUDY; DECISION SUPPORT SYSTEM; HYDROLOGICAL MODELING; LAND USE CHANGE; MARKOV CHAIN; MONTE CARLO ANALYSIS; SPATIAL DISTRIBUTION; UNCERTAINTY ANALYSIS;

ASIA; CHAOHE BASIN; CHINA; EURASIA; FAR EAST;

EID: 47949086314     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2008.05.012     Document Type: Article

References (71)

1. Abbaspour K.C., Johnson C.A., and van Genuchten M.T. Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure. Vadose Zone Journal 3 4 (2004) 1340-1352
2. Abbaspour K.C., Yang J., Maximov I., Siber R., Bogner K., Mieleitner J., Zobrist J., and Srinivasan R. Spatially-distributed modelling of hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology 333 (2007) 413-430
3. Adeuya R.K., Lim K.J., Engel B.A., and Thomas M.A. Modeling the average annual nutrient losses of two watersheds in Indiana using GLEAMS-NAPRA. Transactions of the Asae 48 5 (2005) 1739-1749
4. Ajami, N.K., Duan, Q.Y., Sorooshian, S., 2007. An integrated hydrologic Bayesian multimodal combination framework: confronting input, parameter, and model structural uncertainty in hydrologic prediction. Water Resources Research 43 (1), Art. No. W01403.
5. Arnold J.G., Srinivasan R., Muttiah R.S., and Williams J.R. Large area hydrologic modeling and assessment - Part 1: Model development. Journal of the American Water Resources Association 34 1 (1998) 73-89
6. Arnold Z. An Introduction to Bayesian Inference in Econometrics. Wiley Classics Library Edition (1996), John Wiley, New York p. 66
7. Bates B.C., and Campbell E.P. A Markov chain Monte Carlo scheme for parameter estimation and inference in conceptual rainfall-runoff modeling. Water Resources Research 37 4 (2001) 937-947
8. Bayarri M.J., Berger J.O., Paulo R., Sacks J., Cafeo J.A., Cavendish J., Lin C.-H., and Tu J. A framework for validation of computer models. Technometrics 49 2 (2007) 138-154
9. Bekele E.G., and Nicklow J.W. Multiobjective management of ecosystem services by integrative watershed modeling and evolutionary algorithms. Water Resources Research 41 (2005) W10406 10.1029/2005WR004090
10. Best, N.G., Cowles, M.K., Vines, S.K., 1995. Convergence Diagnosis and Output Analysis software for Gibbs Sampler output: Version 0.3. Medical Research Council Biostatistics Unit, Cambridge.
11. Beven K., and Binley A. The future of distributed models - model calibration and uncertainty prediction. Hydrological Processes 6 3 (1992) 279-298
12. Beven K., and Freer J. Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology. Journal of Hydrology 249 1-4 (2001) 11-29
13. Bicknell, B.R., Imhoff, J., Kittle, J., Jobes, T., Donigian, A.S., 2000. Hydrological Simulation Program - Fortran User's Manual. Release 12, US EPA.
14. Blazkova S., Beven K., Tacheci P., and Kulasova A. Testing the distributed water table predictions of TOPMODEL (allowing for uncertainty in model calibration): the death of TOPMODEL?. Water Resources Research 38 11 (2002) 1257 10.1029/2001WR000912
15. Box G.E.P., and Cox D.R. An analysis of transformations. Journal of the Royal Statistical Society Series B (1964) 211-252
16. Box G.E.P., and Cox D.R. An analysis of transformations revisited, rebutted. Journal of the American Statistical Association 77 377 (1982) 209-210
17. Brockwell P.J., and Davis R.A. Introduction to Time Series and Forecasting (1996), Springer, New York
18. Brockwell P.J. Continuous-time ARMA processes. In: Shanbhag D.N., and Rao C.R. (Eds). Stochastic Processes: Theory and Methods. Handbook of Statistics vol. 19 (2001), Elsevier, Amsterdam 249-276
19. Cameron D., Beven K., and Naden P. Flood frequency estimation by continuous simulation under climate change (with uncertainty). Hydrology and Earth System Sciences 4 3 (2000) 393-405
20. Cameron D., Beven K., Tawn J., and Naden P. Flood frequency estimation by continuous simulation (with likelihood based uncertainty estimation). Hydrology and Earth System Sciences 4 1 (2000) 23-34
21. Chow V.T., Maidment D.R., and Mays L.W. Applied Hydrology (1988), McGraw-Hill, New York
22. Claessens L., Hopkinson C., Rastetter E., and Vallino J. Effect of historical changes in land use and climate on the water budget of an urbanizing watershed. Water Resources Research 42 3 (2006) W03426 10.1029/2005WR004131
23. Cochrane T.A., and Flanagan D.C. Effect of DEM resolutions in the runoff and soil loss predictions of the WEPP watershed model. Transactions of the Asae 48 1 (2005) 109-120
24. Cotler H., and Ortega-Larrocea M.P. Effects of land use on soil erosion in a tropical dry forest ecosystem, Chamela watershed, Mexico. Catena 65 2 (2006) 107-117
25. Cowles M.K., and Carlin B.P. Markov chain Monte Carlo convergence diagnostics: a comparative review. Journal of the American Statistical Association 91 434 (1996) 883-904
26. Cunge J.A. On the subject of a flood propagation method (Muskingum method). Journal of Hydraulics Research 7 2 (1969) 205-230
27. Duan Q.Y., Sorooshian S., and Ibbitt R.P. A maximum likelihood criterion for use with data collected at unequal time intervals. Water Resources Research 24 7 (1988) 1163-1173
28. Duan Q.Y., Sorooshian S., and Gupta V. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research 28 4 (1992) 1015-1031
29. Freer J., Beven K., and Ambroise B. Bayesian estimation of uncertainty in runoff prediction and the value of data: an application of the GLUE approach. Water Resources Research 32 7 (1996) 2161-2173
30. Gelman S., Carlin J.B., Stren H.S., and Rubin D.B. Bayesian Data Analysis (1995), Chapman and Hall, New York
31. Geweke J. Bayesian-Inference in Econometric-Models Using Monte-Carlo Integration. Econometrica 57 6 (1989) 1317-1339
32. Gupta H.V., Beven K.J., and Wagener T. Model calibration and uncertainty estimation. In: Anderson M.G. (Ed). Encyclopedia of Hydrological Sciences (2005), John Wiley, New York 2015-2031
33. Heidelberger P., and Welch P.D. Simulation run length control in the presence of an initial transient. Operations Research 31 6 (1983) 1109-1144
34. Hersbach H. Decomposition of the continuous ranked probability score for ensemble prediction systems. Weather and Forecasting 15 5 (2000) 559-570
35. Hornberger G.M., and Spear R.C. An approach to the preliminary-analysis of environmental systems. Journal of Environmental Management 12 1 (1981) 7-18
36. Hossain F., Anagnostou E.N., and Lee K.H. A non-linear and stochastic response surface method for Bayesian estimation of uncertainty in soil moisture simulation from a land surface model. Nonlinear Processes in Geophysics 11 4 (2004) 427-440
37. Huang Y.F., Zou Y., Huang G.H., Maqsood I., and Chakma A. Flood vulnerability to climate change through hydrological modeling - a case study of the swift current creek watershed in western Canada. Water International 30 1 (2005) 31-39
38. Hundecha Y., and Bardossy A. Modeling of the effect of land use changes on the runoff generation of a river basin through parameter regionalization of a watershed model. Journal of Hydrology 292 1-4 (2004) 281-295
39. Jorgeson J., and Julien P. Peak flow forecasting with radar precipitation and the distributed model CASC2D. Water International 30 1 (2005) 40-49
40. Kavetski D., Franks S.W., and Kuczera G. Confronting input uncertainty in environmental modelling. In: Duan Q., Gupta H.V., Sorooshian S., Rousseau A.N., and Turcotte R. (Eds). Calibration of Watershed Models (2003), American Geophysical Union, Washington, DC 49-68
41. Kavetski, D., Kuczera, G., Franks, S.W., 2006a. Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory. Water Resources Research 42 (3), Art. No. W03407.
42. Kavetski, D., Kuczera, G., Franks, S.W., 2006 b. Bayesian analysis of input uncertainty in hydrological modeling: 2. Application. Water Resources Research 42 (3), Art. No. W03408.
43. Kennedy M.C., and O'Hagan A. Bayesian calibration of computer models. Journal of the Royal Statistical Society Series B 63 3 (2001) 425-464
44. Kuczera G. Improved parameter inference in catchment models. 1. Evaluating parameter uncertainty. Water Resources Research 19 5 (1983) 1151-1162
45. Kuczera G., and Parent E. Monte Carlo assessment of parameter uncertainty in conceptual catchment models: the Metropolis algorithm. Journal of Hydrology 211 1-4 (1998) 69-85
46. Kuczera G., Kavetski D., Franks S., and Thyer M. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: characterising model error using storm-dependent parameters. Journal of Hydrology 331 (2006) 161-177
47. Makowski D., Wallach D., and Tremblay M. Using a Bayesian approach to parameter estimation: comparison of the GLUE and MCMC methods. Agronomie 22 2 (2002) 191-203
48. Mantovan P., and Todini E. Hydrological forecasting uncertainty assessment: incoherence of the GLUE methodology. Journal of Hydrology 330 (2006) 368-381
49. Marshall L., Nott D., and Sharma A. A comparative study of Markov chain Monte Carlo methods for conceptual rainfall-runoff modeling. Water Resources Research 40 (2004) W02501 10.1029/2003WR002378
50. Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., and Teller E. Equation of state calculations by fast computing machines. Journal of Chemical Physics 21 6 (1953) 1087-1092
51. Moradkhani H., Hsu K.-L., Gupta H., and Sorooshian S. Uncertainty assessment of hydrologic model states and parameters: sequential data assimilation using the particle filter. Water Resources Research 41 (2005) W05012 10.1029/2004WR003604
52. Neitsch, S.L., Arnold, J.G, Kiniry, J.R., Williams, J.R., 2001. Soil and Water Assessment Tool User's Manual, version 2000. Grassland, Soil and Water Research Laboratory, Agricultural Research Service, Blackland Research Center, Texas Agricultural Experiment Station.
53. Pednekar A.M., Grant S.B., Jeong Y., Poon Y., and Oancea C. Influence of climate change, tidal mixing, and watershed urbanization on historical water quality in Newport Bay, a saltwater wetland and tidal embayment in southern California. Environmental Science and Technology 39 23 (2005) 9071-9082
54. Reichert P., Schervish M., and Small M.J. An efficient sampling technique for Bayesian inference with computationally demanding models. Technometrics 44 4 (2002) 318-327
55. Reichert, P., 2005. UNCSIM - A computer programme for statistical inference and sensitivity, identifiability, and uncertainty analysis. In: Teixeira, J.M.F., Carvalho-Brito, A.E. (Eds.), Proceedings of the 2005 European Simulation and Modelling Conference (ESM 2005), October 24-26, Porto, Portugal, EUROSIS-ETI. pp. 51-55.
56. Reichert P. A standard interface between simulation programs and systems analysis software. Water Science and Technology 53 1 (2006) 267-275
57. Reichert, P., Mieleitner, J., submitted for publication. Analyzing input and structural uncertainty of a hydrological model with stochastic, time-dependent parameters. Water Resources Research, submitted for publication.
58. Santhi C., Arnold J.G., Williams J.R., Hauck L.M., and Dugas W.A. Application of a watershed model to evaluate management effects on point and nonpoint source pollution. Transactions of the Asae 44 6 (2001) 1559-1570
59. Schaefli B., Talamba D.B., and Musy A. Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology 332 (2007) 303-315
60. Sorooshian S., and Dracup J.A. Stochastic parameter estimation procedures for hydrologic rainfall-runoff models - correlated and heterscedastic error cases. Water Resources Research 16 2 (1980) 430-442
61. Todini E. Hydrological catchment modelling: past, present and future. Hydrology and Earth System Sciences 11 1 (2007) 468-482
62. USDA Soil Conservation Service, 1972. Section 4: Hydrology. In: National Engineering Handbook. SCS.
63. Van Griensven A., and Meixner T. Methods to quantify and identify the sources of uncertainty for river basin water quality models. Water Science and Technology 53 1 (2006) 51-59
64. Vrugt, J.A., Gupta, H.V., Bouten, W., Sorooshian, S., 2003. A shuffled complex evolution metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters. Water Resources Research 39 (8), Art. No.-1201.
65. Vrugt J.A., Diks C.G.H., Bouten W., Gupta H.V., and Verstraten J.M. Towards a complete treatment of uncertainty in hydrologic modelling: combining the strengths of global optimisation and data assimilation. Water Resources Research 41 1 (2005) W01017 10.1029/2004WR003059
66. Williams J.R. The EPIC model. In: Singh V.P. (Ed). Computer Models of Watershed Hydrology (1995), Water Resources Publication, Colorado, USA 909-1000
67. Young R.A., Onstad C.A., Bosch D.D., and Anderson W.P. AGNPS - A nonpoint-source pollution model for evaluating agricultural watersheds. Journal of Soil and Water Conservation 44 2 (1989) 168-173
68. Yang, J., Abbaspour, K.C., Reichert, P., 2005, Interfacing SWAT with systems analysis tools: a generic platform. In: Srinivasan, R., Jacobs, J., Day, D., Abbaspour, K. (Eds.), Third International SWAT Conference Proceedings, July 11-15, Zurich, Switzerland. pp. 169-178.
69. Yang J., Reichert P., Abbaspour K.C., and Yang H. Hydrological modelling of the Chaohe Basin in China: statistical model formulation and Bayesian inference. Journal of Hydrology 340 (2007) 167-182
70. Yang J., Reichert P., and Abbaspour K.C. Bayesian uncertainty analysis in distributed hydrologic modeling: a case study in the Thur River basin (Switzerland). Water Resources Research 43 (2007) W10401 10.1029/2006WR005497
71. Zacharias I., Dimitriou E., and Koussouris T. Integrated water management scenarios for wetland protection: application in Trichonis Lake. Environmental Modelling and Software 20 2 (2005) 177-185