Time Series Analysis: A Hydrological Prospective

Time Series Analysis: A Hydrological Prospective

Sirisha Adamala

1Applied Engineering Department, Vignan’s Foundation for Science, Technology and Research University (VFSTRU), Vadlamudi-522213, Guntur, Andhra Pradesh, India.

The analysis of time series is based on the assumption that successive values in the data file represent consecutive measurements taken at equally spaced time intervals. There are two main goals of time series analysis: (a) identifying the nature of the phenomenon represented by the sequence of observations, and (b) forecasting or predicting future values of the time series variable. Both of these goals require that the pattern of observed time series data is identified and more or less formally described. Once the pattern is established, one can interpret and integrate it with other data (i.e., Use it in the theory of the investigated phenomenon, e.g., Seasonal commodity prices). Regardless of the depth of one’s understanding and the validity of our interpretation (theory) of the phenomenon, one can extrapolate the identified pattern to predict future events. This paper discusses about how to analyze time series data, what are its goals, types of time series data, and models available to analyze time series data.

Keywords: Time series, ARIMA, Box-Jenkins, rainfall, climate, hydrology.

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How to cite this article:
Sirisha Adamala.Time Series Analysis: A Hydrological Prospective. American Journal of Scientific Research and Essays, 2016,1:4. DOI: 10.28933/adamala-ajsre-2016

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