Nonstationary Frequency Analysis of Annual Maximum Rainfall Using Climate Covariates

Water Resources Management

Volumn 29, Issue 2, 2015, Pages 339-358

  Vasiliades, L ^a   Galiatsatou, P ^b   Loukas, A ^a  

^a UNIVERSITY OF THESSALY   (Greece)

^b ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

Climate indices; GEV CDN model; Nonlinear hydroclimatology; Nonstationarity; Precipitation extremes; Teleconnection indices

Indexed keywords

ATMOSPHERIC PRESSURE; CLIMATE MODELS; MAXIMUM LIKELIHOOD; MULTILAYER NEURAL NETWORKS; NETWORK ARCHITECTURE; PARAMETER ESTIMATION; RAIN; VALUE ENGINEERING;

CLIMATE INDEX; HYDRO CLIMATOLOGIES; NON-STATIONARITIES; PRECIPITATION EXTREMES; TELECONNECTION INDICES;

CLIMATOLOGY;

EID: 84920706975     PISSN: 09204741     EISSN: 15731650     Source Type: Journal    
DOI: 10.1007/s11269-014-0761-5     Document Type: Article

References (59)

1. AghaKouchak A, Nasrollahi N (2010) Semi-parametric and parametric inference of extreme value models for rainfall data. Water Resour Manag 24:1229–1249
2. AghaKouchak A, Easterling D, Hsu K, Schubert S, Sorooshian S, (eds) (2013) Extremes in a changing climate: detection, analysis and uncertainty. Water Science and Technology Library, Vol. 65, Springer, Netherlands.
3. Aissaoui-Fqayeh I, El Adlouni S, Ouarda TBMJ, St-Hilaire A (2009) Non-stationary lognormal model development and comparison with the non-stationary GEV model. Hydrol Sci J 54:1141–1156
4. Bishop CM (2006) Pattern recognition and machine learning. Springer-Verlag, New York
5. Breiman L (1996) Bagging predictors. Mach Learn 24:123–140
6. Cannon AJ (2010) A flexible nonlinear modelling framework for nonstationary generalized extreme value analysis in hydroclimatology. Hydrol Process 24:673–685
7. Cannon AJ (2011) GEVcdn: an R package for nonstationary extreme value analysis by generalized extreme value conditional density estimation network. Comput Geosci 37:1532–1533
8. Cawley GC, Janacek GJ, Haylock MR, Dorling SR (2007) Predictive uncertainty in environmental modelling. Neural Netw 20:537–549
9. Chu P-S, Zhao X (2011) Bayesian analysis for extreme climatic events: a review. Atmos Res 102(3):243–262
10. Coles S (2001) An introduction to statistical modelling of extreme values. Springer, London
11. Coles SG, Dixon MJ (1999) Likelihood-based inference for extreme value models. Extremes 2:5–23
12. Cover TM, Thomas JA (1990) Elements of information theory. Wiley, New York
13. Cullen HM, Kaplan A, Arkin PA, Demenocal PB (2002) Impact of the North Atlantic oscillation on middle eastern climate and streamflow. Clim Change 55:315–338
14. El Adlouni S, Ouarda TBMJ, Zhang X, Roy R, Bobee B (2007) Generalized maximum likelihood estimators for the nonstationary generalized extreme value model. Water Resour Res 43, W03410. doi:10.1029/2005WR004545
15. European Environment Agency (EEA) (2010) Mapping the impacts of natural hazards and technological accidents in Europe: An overview of the last decade. European Environment Agency (EEA), Report 13/2010, Office for Official Publications of the European Communities, Luxembourg.
16. Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impact studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578
17. Galiatsatou G, Prinos P (2011) Modeling non-stationary extreme waves using a point process and wavelets. Stoch Environ Res Risk Assess 25(2):165–183
18. Gershunov A, Barnett TP (1998) Interdecadal modulation of ENSO teleconnections. Bull Am Meteorol Soc 79:2715–2725
19. Giorgi F, Lionello P (2008) Climate change projections for the Mediterranean region. Glob Planet Change 63(2–3):90–104
20. Hatzaki M, Flocas HA, Oikonomou C, Giannakopoulos C (2010) Future changes in the relationship of precipitation intensity in Eastern Mediterranean with large scale circulation. Adv Geosci 23:31–36
21. Houssos EE, Bartzokas A (2006) Extreme precipitation events in NW Greece. Adv Geosci 7:91–96
22. Hurrell JW (1995) Decadal trends in the North Atlantic oscillation: regional temperatures and precipitation. Science 7:676–679
23. Hurrell JW, VanLoon H (1997) Decadal variations in climate associated with the North Atlantic oscillation. Clim Change 36(3–4):301–326
24. Hurvich CM, Tsai C (1989) Regression and time series model selection in small samples. Biometrika 76:297–307
25. Iglesias A, Garrote L, Flores F, Moneo M (2007) Challenges to manage the risk of water scarcity and climate change in the mediterranean. Water Resour Manag 21(5):775–788
26. Intergovernmental Panel on Climate Change (IPCC) (2007) Climate change 2007: the physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) In contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
27. Intergovernmental Panel on Climate Change (IPCC) (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. In: Field CB, Barros V, Stocker TF, Qin D, Dokken DJ, Ebi KL, Mastrandrea MD, Mach KJ, Plattner G-K, Allen SK, Tignor M, Midgley PM (eds) A special report of working groups I and II of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
28. Jenkinson AF (1955) The frequency distribution of the annual maximum (or minimum) values of meteorological elements. Q J Roy Meteor Soc 81:158–171
29. Johnson F, Sharma A (2009) Measurment of GCM skills in predicting variables relevant for hydroclimatological assessments. J Clim 22:4373–4382
30. Katz RW (2010) Statistics of extremes in climate change. Clim Change 100:71–76
31. Katz RW, Parlang MB, Naveau P (2002) Statistics of extremes in hydrology. Adv Water Resour 25:1287–1304
32. Khaliq MN, Ouarda TBMJ, Ondo J-C, Gachon P, Bobee B (2006) Frequency analysis of a sequence of dependent and/or non-stationary hydro-meteorological observations: a review. J Hydrol 329:534–552
33. Kharin VV, Zwiers FW (2005) Estimating extremes in transient climate change simulations. J Clim 18:1156–1173
34. Kyselý J (2008) A cautionary note on the use of nonparametric bootstrap for estimating uncertainties in extreme-value models. J Appl Meteorol Climatol 47:3236–3251
35. Lionello P (ed) (2012) The climate of the Mediterranean region from the past to the future. Elsevier, Amsterdam
36. Lionello P, Malanotte-Rizzoli P, Boscolo R (eds) (2006) Mediterranean climate variability. Elsevier, Amsterdam
37. Mailhot A, Duchesne S (2010) Design criteria of urban drainage infrastructures under climate change. J Water Resour Plan Manage-ASCE 136:201–208
38. Maraun D, Rust HW, Osborn T (2010) Synoptic airflow and UK daily precipitation extremes. Extremes 13:133–153
39. Martins ES, Stedinger JR (2000) Generalized maximum-likelihood generalized extreme-value quantile estimators for hydrologic data. Water Resour Res 36:737–744
40. Paninski L (2003) Estimation of entropy and mutual information. Neural Comput 15(6):1191–1253
41. Pozo-Vázquez D, Esteban-Parra MJ, Rodrigo FS, Castro-Diez Y (2001) A study of NAO variability and its possible non-linear influences on European surface temperature. Clim Dyn 17:701–715
42. Price C, Stone L, Rajagopalan B, Alpert P (1998) A possible link between El Nino and precipitation in Israel. Geophys Res Lett 25:3963–3966
43. Renard B, Lang M, Bois P (2006) Statistical analysis of extreme events in a non-stationary context via a Bayesian framework: case study with peak-over-threshold data. Stoch Environ Res Risk Assess 21(2):97–112
44. Renard B, Sun X, Lang M (2013) Bayesian methods for non-stationary extreme value analysis. In AghaKouchak et al. (eds) Extremes in a changing climate: detection, analysis and uncertainty, Springer, Netherlands, pp. 39–95.
45. Rigby RA, Stasinopoulos DM (2005) Generalized additive models for location, scale and shape. Appl Stat 54:507–554
46. Salas J, Obeysekera J (2013) Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J Hydrol Eng. doi: 10.1061/(ASCE)HE.1943-5584.0000820.
47. Schürmann T, Grassberger P (1996) Entropy estimation of symbol sequences. Chaos 6(3):414–427
48. Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461–464
49. Shinyie WL, Ismail N, Jemain AA (2013) Semi-parametric estimation for selecting optimal threshold of extreme rainfall events. Water Resour Manag 27(7):2325–2352
50. Sugahara S, da Rocha RP, Silveira R (2009) Non-stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil. Int J Climatol 29(9):1339–1349
51. Sušelj K, Bergant K (2006) Mediterranean oscillation index. Geophys Res Abst 8:02145
52. Tramblay Y, Neppel L, Carreau J, Sanchez-Gomez E (2012) Extreme value modelling of daily areal rainfall over Mediterranean catchments in a changing climate. Hydrol Process 26:3934–3944
53. Trigo RM, Pozo-Vázquez D, Osborn TJ, Castro-Diez Y, Gamiz-Fortis S, Esteban-Parra MJ (2004) North Atlantic oscillation influence on precipitation, river flow and water resources in the Iberian Peninsula. Int J Climatol 24:925–944
54. Tularam GA (2010) Relationship between El Niño Southern oscillation index and rainfall (Queensland, Austalia). Int J Sus Dev Plann 5(4):378–391
55. Ulbrich U, Christoph M, Pinto JG, Corte-Real J (1999) Dependence of winter precipitation over Portugal on NAO and baroclinic wave activity. Int J Climatol 19:379–390
56. Villarini G, Smith JA, Serinaldi F, Bates J, Bates PD, Krajewski WF (2009) Flood frequency analysis for nonstationary annual peak records in an urban drainage basin. Adv Water Resour 32:1255–1266
57. Villarini G, Smith JA, Napolitano F (2010) Nonstationary modelling of a long record of rainfall and temperature over Rome. Adv Water Resour 33:1256–1267
58. Xoplaki E (2002) Climate variability over the Mediterranean. PhD thesis, University of Bern, Switzerland.
59. Yee TW, Stephenson AG (2007) Vector generalized linear and additive extreme value models. Extremes 10:1–19