Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code.

Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code.

The importance of finding a well fitted model for hydro-meteorological time series cannot be denied, the main gain of a successful approach being the possibility to explain the past and to provide informed insight for the future. Therefore, we tried to present here some techniques that can be used to build a mathematical model for time series (particularly for hydro-meteorological ones), starting from statistical tests of data analysis, passing to the empirical models, nonparametric techniques, ARIMA models and heuristic methods. Since our intention was to write a book easy to read, the theory is shortly presented and is followed by applications on real data that are the results our three years research work. We hope that this material will be useful for postgraduate students, as well as for the researchers.