The statistical and hydrogeological analysis of the relationships between rainfall, river and piezometric level historical data can be useful to characterize the aquifers and to manage the groundwater resources. For this purpose measurements acquired every three days, relative to 1986-2009 period, concerning the Pescara river alluvial plain (Fig.1), were analyzed with several statistical methods. The alluvial bodies of the Pescara river is mainly silty-sandy. The plain aquifer is supported by Plio-Pleistocenic clayey deposits. The three wells (Fig. 2) are located in the medium-low alluvial plain. Autocorrelation and spectral univariate analysis, cross-correlation and bivariate spectral analysis have been implemented with the purpose to evaluate the memory effect, the delay of the piezometric level response to rainfall and river head/discharge impulse, and the periodical components of the time series (Mangin, 1984; Larocque et al., 1998; Polemio and Dragone, 1999).

Statistical analysis of rainfall, river head and piezometric level data of central-Adriatic alluvial aquifers.

POLEMIO MAURIZIO;
2014

Abstract

The statistical and hydrogeological analysis of the relationships between rainfall, river and piezometric level historical data can be useful to characterize the aquifers and to manage the groundwater resources. For this purpose measurements acquired every three days, relative to 1986-2009 period, concerning the Pescara river alluvial plain (Fig.1), were analyzed with several statistical methods. The alluvial bodies of the Pescara river is mainly silty-sandy. The plain aquifer is supported by Plio-Pleistocenic clayey deposits. The three wells (Fig. 2) are located in the medium-low alluvial plain. Autocorrelation and spectral univariate analysis, cross-correlation and bivariate spectral analysis have been implemented with the purpose to evaluate the memory effect, the delay of the piezometric level response to rainfall and river head/discharge impulse, and the periodical components of the time series (Mangin, 1984; Larocque et al., 1998; Polemio and Dragone, 1999).
2014
Istituto di Ricerca per la Protezione Idrogeologica - IRPI
978-88-907553-4-7
auto-crosscorrelation
spectral analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/249925
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