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Water 2017, 9(11), 850; https://doi.org/10.3390/w9110850

Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study

1
Department of Engineering and Geology “InGeo”, “G. D’Annunzio” University of Chieti-Pescara, 66013 Chieti, Italy
2
National Research Council (CNR), Research Institute for the Hydrogeological Protection (IRPI), 70126 Bari, Italy
*
Author to whom correspondence should be addressed.
Received: 6 October 2017 / Revised: 25 October 2017 / Accepted: 26 October 2017 / Published: 3 November 2017
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Abstract

In this research, univariate and bivariate statistical methods were applied to rainfall, river and piezometric level datasets belonging to 24-year time series (1986–2009). These methods, which often are used to understand the effects of precipitation on rivers and karstic springs discharge, have been used to assess piezometric level response to rainfall and river level fluctuations in a porous aquifer. A rain gauge, a river level gauge and three wells, located in Central Italy along the lower Pescara River valley in correspondence of its important alluvial aquifer, provided the data. Statistical analysis has been used within a known hydrogeological framework, which has been refined by mean of a photo-interpretation and a GPS survey. Water–groundwater relationships were identified following the autocorrelation and cross-correlation analyses. Spectral analysis and mono-fractal features of time series were assessed to provide information on multi-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical–mathematical results were interpreted through fieldwork that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools. View Full-Text
Keywords: alluvial aquifer; GPS survey; hydrological time series; autocorrelation; cross-correlation; spectral analysis; mono-fractal analysis; Central Italy alluvial aquifer; GPS survey; hydrological time series; autocorrelation; cross-correlation; spectral analysis; mono-fractal analysis; Central Italy
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Chiaudani, A.; Di Curzio, D.; Palmucci, W.; Pasculli, A.; Polemio, M.; Rusi, S. Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study. Water 2017, 9, 850.

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