Application of periodic autoregressive process to the modeling of the Garonne river flows

Stochastic Environmental Research and Risk Assessment

Volumn 30, Issue 7, 2016, Pages 1785-1795

  Ursu, Eugen ^a   Pereau, Jean Christophe ^a  

^a UNIVERSITÉ DE BORDEAUX   (France)

Author keywords

Genetic algorithms; Periodic time series; River flows analysis; Robust estimation

Indexed keywords

FLOW OF WATER; GENETIC ALGORITHMS; RESERVOIR MANAGEMENT; STATISTICS; TIME SERIES ANALYSIS;

BAYES INFORMATION CRITERION; LEAST-SQUARES ESTIMATOR; PERIODIC AUTOREGRESSIVE PROCESS; PERIODIC TIME; RESERVOIR SYSTEMS; RIVER FLOW; ROBUST ESTIMATION; SEASONAL VARIATION;

RIVERS;

ESTIMATION METHOD; FLOW MODELING; GENETIC ALGORITHM; RIVER FLOW; SEASONAL VARIATION; TIME SERIES;

FRANCE; GARONNE RIVER;

EID: 84952899752     PISSN: 14363240     EISSN: 14363259     Source Type: Journal    
DOI: 10.1007/s00477-015-1193-3     Document Type: Review

References (52)

1. Aksoy H, Dahamsheh A (2009) Artificial neural network models for forecasting monthly precipitation in Jordan. Stoch Environ Res Risk Assess 23:917–931
2. Anderson PA, Meerschaert MM, Zhang K (2013) Forecasting with prediction intervals for periodic autoregressive moving average models. J Time Ser Anal 34:187–193
3. Baker MA, Vervier P (2004) Hydrological variability, organic matter supply and denitrification in the garonne river ecosystem. Freshw Biol 49(2):181–190
4. Ben MG, Martinez EJ, Yohai VJ (1999) Robust estimation in vector autoregressive moving-average time series models. J Time Ser Anal 20:381–399
5. Boe J, Terray L, Martin E, Habets F (2009) Projected changes in components of the hydrological cycle in french river basins during the 21st century. Water Resour Res 45:W08426
6. Box GEP, Jenkins GM (1970) Time series analysis, forecasting and control. Holden-Day, San Francisco
7. Bustos OH, Yohai VJ (1986) Robust estimates for ARMA models. J Am Stat Assoc 81:155–168
8. Caballero Y, Voirin-Morel S, Habets F (2007) Hydrological sensitivity of the Adour-Garonne river basin to climate change. Water Resour Res 43(7):W07448
9. Denby L, Martin RD (1979) Robust estimation of the first-order autoregressive parameter. J Am Stat Assoc 74:140–146
10. Durdu OF (2010) Application of linear stochastic models for drought forecasting in the Buüyük Menderes river basin, western Turkey. Stoch Environ Res Risk Assess 24:1145–1162
11. Eshete Z, Vandewiele GL (1992) Comparison of non-gaussian multicomponent and periodic autoregressive models for river flow. Stoch Hydrol Hydraul 6:223–238
12. Fayaed SS, El-Shafie A, Jaafar O (2013) Reservoir-system simulation and optimization techniques. Stoch Environ Res Risk Assess 27:1751–1772
13. Fernandez C, Vega JA, Fonturbel T, Jimenez E (2008) Streamflow drought time series forecasting: a case study in a small watershed in North West Spain. Stoch Environ Res Risk Assess 23:1063–1070
14. Franses PH, Paap R (2004) Periodic time series models. Oxford University Press, Oxford
15. Gaetan C (2000) Subset ARMA model identification using genetic algorithms. J Time Ser Anal 21:559–570
16. Gladyshev EG (1961) Periodically correlated random sequences. Sov Math 2:385–388
17. Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Boston
18. Gragne A, Sharma A, Mehrotra R, Alfredsen K (2014) Improving inflow forecasting into hydropower reservoirs through a complementary modelling framework. Hydrol Earth Syst Sci 11:12063–12101
19. Hau MC, Tong H (1989) A practical method for outlier detection in autoregressive time series modelling. Stoch Hydrol Hydraul 3:241–260
20. Hendrickx F, Sauquet E (2013) Impact of warming climate on water management for the arige river basin (France). Hydrol Sci J 58(4):1–17
21. Hipel KW, McLeod AI (1994) Time series modelling of water resources and environmental systems. Elsevier, Amsterdam
22. Hyndman RJ, Koehler AB (2006) Another look at measures of forecast accuracy. Int J Forecast 22:679–688
23. Jimenez C, McLeod AI, Hippel KW (1989) Kalman filter estimation for periodic autoregressive-moving average models. Stoch Hydrol Hydraul 3:227–240
24. Koutroumanidis T, Sylaios G, Zafeiroiou E, Tsihrintzis V (2009) Genetic modeling for the optimal forecasting of hydrologic time-series: application in Nestos River. J Hydrol 368:156–164
25. Krause P, Boyle DP, Bäse F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97
26. Li WK (1988) A goodness-of-fit test in robust time series modelling. Biometrika 75:355–361
27. Li WK (2004) Diagn checks in time series. Chapman & Hall/CRC, New York
28. Lütkepohl H (2005) New introduction to multiple time series analysis. Springer, Berlin
29. Ma Y, Genton MG (2000) Highly robust estimation of the autocovariance function. J Time Ser Anal 21:663–684
30. Madsen H, Skotner C (2005) Adaptive state updating in real-time river now forecasting a combined ltering and error forecasting procedure. J Hydrol 308(1):302–312
31. Maire A, Buisson L, Biau S, Canal J, Lafaille P (2013) A multi-faceted framework of diversity for prioritizing the conservation of fish assemblages. Ecol Indic 34:450–459
32. Maronna RA, Martin RD, Yohai VJ (2006) Robust statistics: theory and methods. Wiley, New York
33. McLeod AI (1993) Parsimony, model adequacy, and periodic autocorrelation in time series forecasting. Int Stat Rev 61:387–393
34. McLeod AI (1994) Diagnostic checking periodic autoregression models with applications. J Time Ser Anal 15:221–233
35. McLeod AI, Gweon H (2013) Optimal deseasonalization for monthly and daily geophysical time series. J Environ Stat 4:1–11
36. Mishra AK, Desai VR (2005) Drought forecasting using stochastic models. Stoch Environ Res Risk Assess 19:326–339
37. Mitchell M (1996) An introduction to genetic algorithms. MIT Press, Cambridge
38. Muylaert K, Sanchez-Perez JM, Teissier S, Sauvage S, Dauta A, Vervier P (2009) Eutrohisation and its effect on dissolved Si concentrations in the garonne river (france). J Limnol 68(2):368–374
39. Noakes DJ, McLeod AI, Hipel KW (1985) Forecasting monthly riverflow time series. Int J Forecast 1:179–190
40. Oeurng C, Sauvage S, Coynel A, Maneux E, Etcheber H, Sanchez-Perez JM (2011) Fluvial transport of suspended sediment and organic carbon during flood events in a large agricultural catchment in southwest France. Hydrol Process 25:2365–2378
41. Pagano M (1978) On periodic and multiple autoregressions. Ann Stat 6:1310–1317
42. Sarnaglia AJQ, Reisen VA, Lévy-Leduc C (2010) Robust estimation of periodic autoregressive processes in the presence of additive outliers. J Multivar Anal 101:2168–2183
43. Shao Q (2007) Robust estimation for periodic autoregressive time series. J Time Ser Anal 29:251–263
44. Sivanandam SN, Deepa SN (2008) Introduction to genetic algorithms. Springer, Berlin
45. Tesfaye YG, Meerschaert MM, Anderson PL (2006) Identification of periodic autoregressive moving average models and their application to the modeling of river flows. Water Resour Res 42:1–11
46. Tisseuil C, Vrac M, Lek S, Wade A (2010) Statistical downscaling of river flows. J Hydrol 385:279–291
47. Ursu E, Duchesne P (2009) On modelling and diagnostic checking of vector periodic autoregressive time series models. J Time Ser Anal 30:70–96
48. Ursu E, Pereau JC (2014) Robust modeling of periodic vector autoregressive time series. J Stat Plan Inference 155:93–106
49. Ursu E, Turkman KF (2012) Periodic autoregressive model identification using genetic algorithm. J Time Ser Anal 33:398–405
50. Vecchia AV (1985a) Periodic autoregressive-moving average (PARMA) modeling with applications to water resources. Water Resour Bull 21:721–730
51. Vecchia AV (1985b) Maximum likelihood estimation for periodic autoregressive moving average models. Technometrics 27:375–384
52. Wang Y, Guo S, Chen H, Zhou Y (2014) Comparative study of monthly inflow prediction methods for the three gorges reservoir. Stoch Environ Res Risk Assess 28:555–570