SEASONAL STOCHASTIC SIMULATION AND TIMESERIES MODELLING - ANALYSIS OF A KARSTIC SPRING IN CENTRAL MACEDONIA, GREECE


I. Lappas
M. Lazaridou
Résumé

The objective of this paper is to find an appropriate Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model for fitting the monthly discharge of a karstic spring located at the North of the city of Serres (Agios Ioannis, Mount Menikio) by considering the minimum of Akaike Information Criterion (AIC). Box- Jenkins methodology applies models to find the best fit of a timeseries to past values of this timeseries, in order to make forecasting and consists of a four-step iterative procedure: identification, estimation, diagnostic check and forecasting. Timeseries analysis and forecasting of hydrological parameters such as spring discharge may be useful in decision making and optimum water resources usage. In this study, monthly discharge measurements are analysed. Initial data are firstly transformed to normal and stationary using differencing methods. Autocorrelation and Partial Autocorrelation functions are calculated to determine the order of Autoregressive and Moving Average parameters and residuals are then checked to show the “white noise”. The spring discharge data are forecasted based on the selected model up to 2008 and are then compared with measured values. The timeseries model SARIMA (2,1,1)(1,0,1)12 could be used in monthly discharge forecasting at a short time (upcoming one year) with a simple and explicit model structure in order to help decision m akers to establish priorities in terms of water demand management. Finally, the corr elation coefficient between the observed and fitted data is essentially high, while the absolute and relative errors are significantly low.

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  • Rubrique
  • Engineering Geology, Hydrogeology, Urban Geology
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Références
Βοx, G. and Cox, D., 1964. Αn Analysis of Transformations, J. R. Stat. Soc., Ser. Β, 26, 211-252.
Box, G. and Jenkins, G., 1976. Time Series Analysis, Forecasting and Control, Holden - Day, San
Francisco, California, U.S.A.
Koutsoyiannis, D., 2000. A generalized mathematical framework for stochastic simulation and
forecast of hydrologic timeseries, Wat. Resour. Re., 36(6), 1519-1534.
Koutsoyiannis, D. 2008. Stochastic Methods in Water Resources, National & Technical University
of Athens.
Lazaridou, M. and Papadopoulos, K., 2001a. Hydrogeological research of carbonate rocks of mounts
Menikio and Agkistro, 2nd Community Support Framework, I.G.M.E. Branch of
Thessaloniki.
Lazaridou, M. and Polizonis, E., 2001b. Quality monitoring and water resources control of Central
Macedonia, Prefecture of Serres, 2nd Community Support Framework, I.G.M.E. Branch of
Thessaloniki.
Lazaridou, M., 2010. Basins water balance. Quality parameters monitoring and protection measures
of the groundwater in Central Macedonia, 3rd Community Support Framework, I.G.M.E.
Branch of Thessaloniki.
Manakos, A. and Dimopoulos, G., 2004. Contribution of Stochastic Models to the Sustainable Water
Management. The example of Krania Elassona Karstic Aquifer in Thessaly, Proceedings of
the 10th International Conference of Greek Geological Society, Thessaloniki.
Manakos, A. and Georgiou, P., 2009. Timeseries modelling of groundwater head Using Seasonal
Stochastic Models SARIMA, Proceedings of the Common Conference of the 11th Hellenic
Hydrotechnical Society and of the 7th Conference of the Hellenic Committee of Water
Management, Volos.
Papamichail, D., 1993. Seasonal ARIMA Modelling of Acheloos River Monthly Discharge.
Proceedings of the 2nd Hydrogeological Congress, Patra.
Ripley, B.D., 1987. Stochastic Simulation, Wiley, New York.
Salas, J.D., 1992. Analysis and Modelling of Hydrologic Timeseries, Maidment, D.R., ed.,
Handbook of Hydrology, New York.
Xydas, S. and Staikopoulos, G., 1985. Serres sheet geological map, scale 1:50.000. I.G.M.E.
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