Stochastic generation of multi-site daily precipitation for applications in risk management

Journal of Hydrology

Volumn 498, Issue , 2013, Pages 23-35

  Breinl, Korbinian ^a   Turkington, Thea ^b   Stowasser, Markus ^c  

^a UNIVERSITY OF SALZBURG   (Austria)

^b UNIVERSITY OF TWENTE   (Netherlands)

^c Allianz AG   (Germany)

Author keywords

Bootstrap; Markov chain; Multi site model; Precipitation; Stochastic simulation

Indexed keywords

BOOTSTRAP; MULTI-SITE MODEL; OBSERVATION NETWORKS; PARAMETRIC DISTRIBUTIONS; PRECIPITATION TIME SERIES; STATISTICAL PROPERTIES; STOCHASTIC GENERATION; STOCHASTIC SIMULATIONS;

CATCHMENTS; PHILOSOPHICAL ASPECTS; PRECIPITATION (CHEMICAL); RADIO COMMUNICATION; RISK MANAGEMENT; RUNOFF; STATISTICAL METHODS; STOCHASTIC MODELS;

MARKOV PROCESSES;

BOOTSTRAPPING; DIURNAL VARIATION; MARKOV CHAIN; PRECIPITATION (CLIMATOLOGY); RAINGAUGE; RISK ASSESSMENT; STOCHASTICITY;

AUSTRIA; FRANCE; GERMANY;

EID: 84880161492     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2013.06.015     Document Type: Article

References (75)

1. Ailliot P., Thompson C., Thomson P. Space-time modelling of precipitation by using a hidden Markov model and censored Gaussian distributions. J. Roy. Statist. Soc. C 2009, 58:405-426.
2. Apipattanavis S., Podesta G., Rajagopalan B., Katz R.W. A semiparametric multivariate and multisite weather generator. Water Resour. Res. 2007, 43(11).
3. Baigorria G.A., Jones J.W. GiST: A stochastic model for generating spatially and temporally correlated daily rainfall data. J. Clim. 2010, 23(22):5990-6008.
4. Bardossy A., Pegram G.G.S. Copula based multisite model for daily precipitation simulation. Hydrol. Earth Syst. Sci. 2009, 13(12):2299-2314.
5. Bardossy A., Plate E.J. Space-time model for daily rainfall using atmospheric circulation patterns. Water Resour. Res. 1992, 28(5):1247-1259.
6. Beersma J.J., Buishand T.A. Multi-site simulation of daily precipitation and temperature conditional on the atmospheric circulation. Clim. Res. 2003, 25(2):121-133.
7. Brandsma, T., Buishand, T.A., 1997a. Rainfall generator for the Rhine basin: single-site generation of weather variables by nearest-neighbour resampling. KNMI-publication 186-I, KNMI, De Bilt: 47.
8. Brandsma T., Buishand T.A. Statistical linkage of daily precipitation in Switzerland to atmospheric circulation and temperature. J. Hydrol. 1997, 198(1-4):98-123.
9. Brandsma T., Buishand T.A. Simulation of extreme precipitation in the Rhine basin by nearest-neighbour resampling. Hydrol. Earth Syst. Sci. 1998, 2(2-3):195-209.
10. Brissette F.P., Khalili M., Leconte R. Efficient stochastic generation of multi-site synthetic precipitation data. J. Hydrol. 2007, 345(3-4):121-133.
11. Buishand T.A. Some remarks on the use of daily rainfall models. J. Hydrol. 1978, 36(3-4):295-308.
12. Buishand T.A., Brandsma T. Multisite simulation of daily precipitation and temperature in the Rhine Basin by nearest-neighbor resampling. Water Resour. Res. 2001, 37(11):2761-2776.
13. Burton A., Kilsby C.G., Fowler H.J., Cowpertwait P.S.P., O'Connell P.E. RainSim: a spatial-temporal stochastic rainfall modelling system. Environ. Model Softw. 2008, 23(12):1356-1369.
14. Cannon A.J. Probabilistic multisite precipitation downscaling by an expanded Bernoulli-gamma density network. J. Hydrometeorol. 2008, 9(6):1284-1300.
15. Clark M.P., et al. A resampling procedure for generating conditioned daily weather sequences. Water Resour. Res. 2004, 40(4).
16. Corte-Real J., Xu H., Qian B.D. A weather generator for obtaining daily precipitation scenarios based on circulation patterns. Clim. Res. 1999, 13(1):61-75.
17. Cowden J.R., Watkins D.W., Mihelcic J.R. Stochastic rainfall modeling in West Africa: parsimonious approaches for domestic rainwater harvesting assessment. J. Hydrol. 2008, 361(1-2):64-77.
18. Deidda R. A multiple threshold method for fitting the generalized Pareto distribution to rainfall time series. Hydrol. Earth Syst. Sci. 2010, 14(12):2559-2575.
19. Dubrovsky M., Buchtele J., Zalud Z. High-frequency and low-frequency variability in stochastic daily weather generator and its effect on agricultural and hydrologic modelling. Clim. Change 2004, 63(1-2):145-179.
20. Filliben J.J. The probability plot correlation coefficient test for normality. Technometrics 1975, 17(1):111-117.
21. Foufoula-Georgiou E., Lettenmaier D.P. A Markov renewal model for rainfall occurrences. Water Resour. Res. 1987, 23(5):875-884.
22. Fowler H.J., Kilsby C.G., O'Connell P.E., Burton A. A weather-type conditioned multi-site stochastic rainfall model for the generation of scenarios of climatic variability and change. J. Hydrol. 2005, 308(1-4):50-66.
23. Furrer E.M., Katz R.W. Improving the simulation of extreme precipitation events by stochastic weather generators. Water Resour. Res. 2008, 44(12).
24. Guttorp P. Stochastic Modeling of Scientific Data 1995, Chapman and Hall, London.
25. Haberlandt, U., Hundecha, Y., Pahlow, M., Schumann, A.H., 2011. Rainfall generators for application in flood studies. In: Schumann, A.H. (Ed.), Flood Risk Assessment and Management. Springer Netherlands, pp. 117-147.
26. Hayhoe H.N. Improvements of stochastic weather data generators for diverse climates. Clim. Res. 2000, 14(2):75-87.
27. Herr H.D., Krzysztofowicz R. Generic probability distribution of rainfall in space: the bivariate model. J. Hydrol. 2005, 306(1-4):234-263.
28. Hughes J.P., Guttorp P., Charles S.P. A non-homogeneous hidden Markov model for precipitation occurrence. J. Roy. Stat. Soc. C 1999, 48(1):15-30.
29. Hussin H.Y., et al. Parameterization of a numerical 2-D debris flow model with entrainment: a case study of the Faucon catchment, Southern French Alps. Nat. Hazard Earth Syst. 2012, 12(10):3075-3090.
30. Kappes M.S., et al. Assessment of debris-flow susceptibility at medium-scale in the Barcelonnette Basin, France. Nat. Hazard Earth Syst. 2011, 11(2):627-641.
31. Katz R.W. Precipitation as a Chain-dependent process. J. Appl. Meteorol. 1977, 16(7):671-676.
32. Katz R.W. On some criteria for estimating the order of a Markov-chain. Technometrics 1981, 23(3):243-249.
33. Katz R.W., Parlange M.B. Mixtures of stochastic processes: application to statistical downscaling. Clim. Res. 1996, 7(2):185-193.
34. Katz R.W., Zheng X.G. Mixture model for overdispersion of precipitation. J. Clim. 1999, 12(8):2528-2537.
35. Khalili M., Brissette F., Leconte R. Stochastic multi-site generation of daily weather data. Stoch. Environ. Res. Risk A 2009, 23(6):837-849.
36. Kienberger S., Lang S., Zeil P. Spatial vulnerability units - expert-based spatial modelling of socio-economic vulnerability in the Salzach catchment, Austria. Nat. Hazard Earth Syst. 2009, 9(3):767-778.
37. Kilsby C.G., et al. A daily weather generator for use in climate change studies. Environ. Model Softw. 2007, 22(12):1705-1719.
38. Kim Y., Katz R.W., Rajagopalan B., Podesta G.P., Furrer E.M. Reducing overdispersion in stochastic weather generators using a generalized linear modeling approach. Clim. Res. 2012, 53(1):13-24.
39. Leander R., Buishand T.A. A daily weather generator based on a two-stage resampling algorithm. J. Hydrol. 2009, 374(3-4):185-195.
40. Li, Z., Brissette, F., Chen, J., 2012. Finding the most appropriate precipitation probability distribution for stochastic weather generation and hydrological modelling in Nordic watersheds. Hydrol. Process.: n/a-n/a.
41. Li C., Singh V.P., Mishra A.K. A bivariate mixed distribution with a heavy-tailed component and its application to single-site daily rainfall simulation. Water Resour. Res. 2013, 49(2):767-789.
42. McKague K., Rudra R., Ogilvie J., Ahmed I., Gharabaghi B. Evaluation of weather generator ClimGen for southern ontario. Can Water Resour. J. 2005, 30(4):315-330.
43. Mehrotra R., Sharma A. Evaluating spatio-temporal representations in daily rainfall sequences from three stochastic multi-site weather generation approaches. Adv. Water Resour. 2009, 32(6):948-962.
44. Mehrotra R., Srikanthan R., Sharma A. A comparison of three stochastic multi-site precipitation occurrence generators. J. Hydrol. 2006, 331(1-2):280-292.
45. Mhanna M., Bauwens W. Stochastic single-site generation of daily and monthly rainfall in the Middle East. Meteorol. Appl. 2012, 19(1):111-117.
46. Palutikof J.P., Goodess C.M., Watkins S.J., Holt T. Generating rainfall and temperature scenarios at multiple sites: examples from the Mediterranean. J. Clim. 2002, 15(24):3529-3548.
47. Papalexiou S.M., Koutsoyiannis D., Makropoulos C. How extreme is extreme? An assessment of daily rainfall distribution tails. Hydrol. Earth Syst. Sci. Discuss. 2012, 9(5):5757-5778.
48. Papalexiou S.M., Koutsoyiannis D., Makropoulos C. How extreme is extreme? An assessment of daily rainfall distribution tails. Hydrol. Earth Syst. Sci. 2013, 17(2):851-862.
49. Rajagopalan B., Lall U. A k-nearest-neighhor simulator for daily precipitation and other weather variables. Water Resour. Res. 1999, 35(10):3089-3101.
50. Richardson C.W. Stochastic simulation of daily precipitation, temperature, and solar-radiation. Water Resour. Res. 1981, 17(1):182-190.
51. Richardson, C., Wright, D.A., 1984. WGEN: a model for generating daily weather variables. USDA/ARS, ARS-8, Washington, DC.
52. Schubert S. A weather generator based on the European 'Grosswetterlagen'. Clim. Res. 1994, 4:191-202.
53. Schwarz G. Estimating dimension of a model. Ann. Stat. 1978, 6(2):461-464.
54. Semenov M.A., Brooks R.J., Barrow E.M., Richardson C.W. Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Clim. Res. 1998, 10(2):95-107.
55. Serinaldi F. Copula-based mixed models for bivariate rainfall data: an empirical study in regression perspective. Stoch. Environ. Res. Risk A 2009, 23(5):677-693.
56. Serinaldi F. A multisite daily rainfall generator driven by bivariate copula-based mixed distributions. J. Geophys. Res. - Atmos. 2009, 114(10).
57. Sharma A., Lall U. A nonparametric approach for daily rainfall simulation. Math. Comput. Simulat. 1999, 48(4-6):361-371.
58. Srikanthan R., McMahon T.A. Stochastic generation of annual, monthly and daily climate data: a review. Hydrol. Earth Syst. Sci. 2001, 5(4):653-670.
59. Srikanthan R., Pegram G.G.S. A nested multisite daily rainfall stochastic generation model. J. Hydrol. 2009, 371(1-4):142-153.
60. Stehlik J., Bardossy A. Multivariate stochastic downscaling model for generating daily precipitation series based on atmospheric circulation. J. Hydrol. 2002, 256(1-2):120-141.
61. Stern R.D., Coe R. A model-fitting analysis of daily rainfall data. J. Roy. Stat. Soc. A 1984, 147:1-34.
62. Stowasser M. Modelling rain risk: a multi-order Markov chain model approach. J. Risk Finance, The 2011, 13(1):45-60.
63. Villarini G., Serinaldi F., Krajewski W.F. Modeling radar-rainfall estimation uncertainties using parametric and non-parametric approaches. Adv. Water Resour. 2008, 31(12):1674-1686.
64. Vlcek O., Huth R. Is daily precipitation Gamma-distributed? Adverse effects of an incorrect use of the Kolmogorov-Smirnov test. Atmos. Res. 2009, 93(4):759-766.
65. Wan H., Zhang X.B., Barrow E.M. Stochastic modelling of daily precipitation for Canada. Atmos. Ocean 2005, 43(1):23-32.
66. Watkins D.S. Fundamentals of Matrix Computations 2010, Pure and Applied Mathematics, Wiley, Hoboken, N.J.
67. Wilby R.L., et al. Statistical downscaling of general circulation model output: a comparison of methods. Water Resour. Res. 1998, 34(11):2995-3008.
68. Wilby R.L., Tomlinson O.J., Dawson C.W. Multi-site simulation of precipitation by conditional resampling. Clim. Res. 2003, 23(3):183-194.
69. Wilks D.S. Conditioning stochastic daily precipitation models on total monthly precipitation. Water Resour. Res. 1989, 25(6):1429-1439.
70. Wilks D.S. Adapting stochastic weather generation algorithms for climate change studies. Climatic Change 1992, 22(1):67-84.
71. Wilks D.S. Multisite generalization of a daily stochastic precipitation generation model. J. Hydrol. 1998, 210(1-4):178-191.
72. Wilks D.S. Multisite downscaling of daily precipitation with a stochastic weather generator. Clim. Res. 1999, 11(2):125-136.
73. Wilks D.S., Wilby R.L. The weather generation game: a review of stochastic weather models. Prog. Phys. Geogr. 1999, 23(3):329-357.
74. Wilson P.S., Toumi R. A fundamental probability distribution for heavy rainfall. Geophys. Res. Lett. 2005, 32(14).
75. Zheng X.G., Katz R.W. Mixture model of generalized chain-dependent processes and its application to simulation of interannual variability of daily rainfall. J. Hydrol. 2008, 349(1-2):191-199.