Data management of extreme marine and coastal hydro-meteorological events

References

• Akaike , H. Information Theory and an Extension of the Maximum Likelihood Principle . Proc. 2nd Intl. Symp. Information Theory . Edited by: Petrov , B. N. and Csaki , F. pp. 267 – 281 . Budapest. : Akademia Kiado .
   Google Scholar
• Bartlett , M. S. 1950 . Periodogram Analysis and Continuous Spectra . Biometrika , 37 : 1 – 16 .
   PubMed Web of Science ®Google Scholar
• Beran , J. 1994 . Statistics for Long-Memory Processes , New York : Chapman & Hall .
   Google Scholar
• Bloomfield , P. 1992 . Trend in Global Temperature . Climatic Change , 21 : 1 – 16 .
   Web of Science ®Google Scholar
• Box , G. E. P. and Cox , D. R. 1964 . An Analysis of Transformations . J. Royal Statistical Society, Ser. B , 26 : 211 – 252 .
   Google Scholar
• Box , G. E. P. and Jenkins , G. M. 1976 . Time Series Analysis: Forecasting and Control , 2nd (edn.) , San Francisco : Holden-Day .
   Google Scholar
• Burn , D. H. and Hag Elnur , M. A. 2002 . Detection of Hydrological Trend and Variability . J. Hydrol. , 255 : 107 – 122 .
   Web of Science ®Google Scholar
• Chen , H. L. and Rao , A. R. 2002 . Testing Hydrological Time Series for Stationarity . J. Hydrol. Eng. , 7 ( 2 ) : 129 – 136 .
   Web of Science ®Google Scholar
• Dickey , D. A. and Fuller , W. A. 1979 . Distribution of the Estimators for Autoregressive Time Series with a Unit Root . J. Am. Stat. Assoc. , 74 : 423 – 431 .
   Web of Science ®Google Scholar
• Dietz , E. J. and Killeen , T. J. 1981 . A Nonparametric Multivariate Test for Monotonic Trend with Pharmaceutical Applications . J. Am. Stat. Assoc. , 76 ( 373 ) : 169 – 174 .
   Web of Science ®Google Scholar
• Douglas , E. M. , Vogel , R. M. and Kroll , C. N. 2000 . Trends in Floods and Low Flows in the United States: Impact of Spatial Correlation . J. Hydrol. , 240 : 90 – 105 .
   Web of Science ®Google Scholar
• Fuller , W. A. 1976 . Introduction to statistical time series , New York : Wiley .
   Google Scholar
• Geweke , J. and Porter-Hudak , S. 1983 . The Estimation andApplication of Long Memory Time Series Models . J. Time Ser. Anal. , 4 : 221 – 238 .
   Google Scholar
• Gimeno , R. , Manchado , B. and Minguez , R. 1999 . Stationarity Tests for Financial Time Series . Physica A , 269 : 72 – 78 .
   Google Scholar
• Gladysev , E. G. 1961 . Periodically Correlated Random Sequences . Soviet Math. Dokl. , 2 : 385 – 388 .
   Google Scholar
• Granger , C. W. J. and Joyeux , R. 1980 . An Introduction to Long- Memory Time Series Models and Fractional Differencing . J. Time Ser. Anal. , 1 : 15 – 29 .
   Google Scholar
• Hamilton , J. D. 1994 . Time Series Analysis , Princeton : Princeton University Press .
   Google Scholar
• Haslett , J. and Raftery , A. E. 1989 . Space-Time Modeling with Long-Memory Dependence: Assessing Ireland's Wind Power Resource . Applied Statistics , 38 : 1 – 50 . with Discussion
   Web of Science ®Google Scholar
• Helsel , D. R. and Hirsch , R. M. 1992 . Statistical Methods in Water Resources , Amsterdam : Elsevier .
   Google Scholar
• Hirsch , R. M. and Slack , J. R. 1984 . A Nonparametric Trend Test for Seasonal Data with Serial Dependence . Water Resources Research , 20 ( 6 ) : 727 – 732 .
   Web of Science ®Google Scholar
• Hirsch , R. M. , Slack , J. R. and Smith , R. A. 1982 . Techniques of Trend Analysis for Monthly Water Quality Data . Water Resources Research , 18 ( 1 ) : 107 – 121 .
   Web of Science ®Google Scholar
• Hosking , J. R. M. 1981 . Fractional Differencing . Biometrika , 68 : 165 – 176 .
   Web of Science ®Google Scholar
• Hurst , H. E. 1951 . Long-Term Storage Capacity of Reservoirs . Trans. ASCE , 116 : 770 – 808 .
   Google Scholar
• Hussain , S. and Elbergali , A. 1999 . Fractional Order Estimation and Testing, Application to Swedish Temperature Data . Environmetrics , 10 : 339 – 349 .
   Web of Science ®Google Scholar
• Insightful Corporation . 2001 . Analyzing Time Series and Signals, of the S-PLUS 6 forWindows Guide to Statistics , Vol. 2 , Seattle, WA : Insightful Corporation . Chap. 27
   Google Scholar
• Jain , S. and Lall , U. 2001 . Floods in a Changing Climate: Does the Past Represent the Future? . Water Res. Research , 37 ( 12 ) : 3193 – 3205 .
   Web of Science ®Google Scholar
• Karagiannis , T. , Molle , M. and Faloutsos , M. 2004 . Long-Range Dependence: Ten Years of Internet Traffic Modeling . IEEE Internet Computing , 8 ( 5 ) : 57 – 64 .
   Web of Science ®Google Scholar
• Kendall , M. G. 1938 . A New Measure of Rank Correlation . Biometrika , 30 : 81 – 93 .
   Web of Science ®Google Scholar
• Kendall , M. G. 1975 . Rank Correlation Methods , London : Griffin .
   Google Scholar
• Kundzewicz , Z. W. , Graczyk , D. , Maurer , T. , Przymusinska , I. , Radziejewski , M. , Svensson , C. and Szwed , M. 2004 . Detection of Change in World-Wide Hydrological Time Series of Maximum Annual Flow , GRDC Report 32 Koblenz, , Germany : Global Runoff Data Centre .
   Google Scholar
• Kwiatkowski , D. , Phillips , P. C. B. , Schmidt , P. and Shin , Y. 1992 . Testing the Null of Stationarity Against the Alternative of a Unit Root: How Sure areWe that Economic Time Series Have a Unit Root? . J. Econometrics , 54 : 159 – 178 .
   Web of Science ®Google Scholar
• Lee , D. and Schmidt , P. 1996 . On the Power of the KPSS Test of Stationarity Against Fractionally-Integrated Alternatives . J. Econometrics , 73 ( 1 ) : 285 – 302 .
   Web of Science ®Google Scholar
• Lettenmaier , D. P. and Wood , E. F. 1993 . Hydrological Forecasting, Handbook of Hydrology , Edited by: Maidment , D. R. New York : McGraw-Hill . Chap. 26
   Google Scholar
• Lo , A. L. 1991 . Long-Term Memory in Stock Market Prices . Econometrica , 59 ( 5 ) : 1279 – 1313 .
   Web of Science ®Google Scholar
• Mandelbrot , B. B. and Wallis , J. R. 1969a . Computer Experiments with Fractional Gaussian Noises . Water Res. Research , 5 : 228 – 267 .
   Web of Science ®Google Scholar
• Mandelbrot , B. B. and Wallis , J. R. 1969b . Robustness of the Rescaled Range R/S in the Measurement of Non-Cyclic Long-Run Statistical Dependence . Water Res. Research , 5 : 967 – 988 .
   Web of Science ®Google Scholar
• Mann , H. B. 1945 . Nonparametric Test Against Trend . Econometrica , 13 : 245 – 259 .
   Web of Science ®Google Scholar
• McLeod , A. I. 1975 . Derivation of the Theoretical Autocovariance Function of Autoregressive-Moving Average Time Series . Applied Statistics , 24 ( 2 ) : 255 – 256 .
   Web of Science ®Google Scholar
• Meade , N. and Maier , M. R. 2003 . Evidence of Long Memory in Short-Term Interest Rates . J. Forecast , 22 : 553 – 568 .
   Web of Science ®Google Scholar
• Mitosek , H. T. 2000 . On Stochastic Properties of Daily River Flow Processes . J. Hydrol. , 228 : 188 – 205 .
   Web of Science ®Google Scholar
• Montanari , A. , Rosso , R. and Taqqu , M. S. 1997 . Fractionally Differenced ARIMA Models Applied to Hydrological Time Series: Identification, Estimation, and Simulation . Water Res. Research , 33 ( 5 ) : 1035 – 1044 .
   Web of Science ®Google Scholar
• Montanari , A. , Rosso , R. and Taqqu , M. S. 2000 . A Seasonal Fractional ARIMA Model Applied to the Nile River Monthly at Aswan . Water Res. Research , 36 : 1249 – 1259 .
   Web of Science ®Google Scholar
• Newey , W. K. and West , K. D. 1987 . A Simple, Positive Semi- Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix . Econometrica , 55 : 703 – 708 .
   Web of Science ®Google Scholar
• Ooms , M. and Franses , P. H. 2001 . A Seasonal Periodic Long Memory Model for Monthly River Flows . Environmental Modelling and Software , 16 : 559 – 569 .
   Web of Science ®Google Scholar
• Priestley , M. B. 1988 . Non-Linear and Non-Stationary Time Series Analysis , London : Academic Press .
   Google Scholar
• Rao , A. R. and Bhattacharya , D. 1999 . Hypothesis Testing for Long-Term Memory in Hydrological Series . J. Hydrol , 216 ( 3/4 ) : 183 – 196 .
   Web of Science ®Google Scholar
• Said , S. E. and Dickey , D. 1984 . Testing for Unit Roots in Autoregressive Moving-Average Models with Unknown Order . Biometrika , 71 : 599 – 607 .
   Web of Science ®Google Scholar
• Schwert , G. W. 1989 . Tests for Unit Roots: A Monte Carlo Investigation . J. Business Eco. Stat. , 7 : 147 – 159 .
   Web of Science ®Google Scholar
• Shin , Y. and Schmidt , P. 1992 . The KPSS Stationarity Test as a Unit Root Test . Economics Letters , 38 : 387 – 392 .
   Web of Science ®Google Scholar
• van Belle , G. and Hughes , J. P. 1984 . Nonparametric Tests for Trend in Water Quality . Water Res. Research , 20 ( 1 ) : 127 – 136 .
   Web of Science ®Google Scholar
• van Gelder , P. H. A. J. M. 1999 . Statistical Methods for the Risk- Based Design of Civil Structures , TU Delft, , The Netherlands : Communication 00-1 on Hydraulic and Geotechnical Engineering . ISSN: 0169-6548
   Google Scholar
• von Storch , H. 1995 . Misuses of Statistical Analysis in Climate Research. Analysis of ClimateVariability: Applications of Statistical Techniques , Edited by: Storch , H. V. and Navarra , A. 11 – 26 . New York : Springer .
   Google Scholar
• Wang , W. 2006 . Stochasticity, Nonlinearity and Forecasting of Streamflow Processes , Delft : University of Technology . PhD thesis
   Google Scholar
• Zhang , X. , Harvey , K. D. , Hogg , W. D. and Yuzyk , T. R. 2001 . Trends in Canadian Streamflow . Water Res. Research , 37 ( 4 ) : 987 – 998 .
   Web of Science ®Google Scholar
• Zivot , E. and Wang , J. 2002 . Modelling Financial Time Series with S-Plus , NewYork : Springer .
   Google Scholar