The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Sergio Rusi - One of the best experts on this subject based on the ideXlab platform.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
Water, 2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract: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.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract:In this research, univariate and bivariate statistical methods were applied to rainfall, river and Piezometric Level datasets belonging to 24 years long time series (1986-2009). These methods, that 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. The 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; the spectral analysis and mono-fractal features of time series were assessed, in order to provide information on multy-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical-mathematical results were interpreted through field work that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.
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statistical analysis of rainfall river head and Piezometric Level data of central adriatic alluvial aquifers
2014Co-Authors: Alessandro Chiaudani, William Palmucci, Maurizio Polemio, Sergio RusiAbstract:1. Engineering and Geology Department "InGeo", "G. D'Annunzio" University, Chieti-Pescara (achiaudani@unich.it; william.palmucci@unich.it; s.rusi@unich.it) 2. National Research Council (CNR), Research Institute for the Hydrogeological Protection (IRPI), Bari (m.polemio@ba.irpi.cnr.it)
Alessandro Chiaudani - One of the best experts on this subject based on the ideXlab platform.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
Water, 2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract: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.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract:In this research, univariate and bivariate statistical methods were applied to rainfall, river and Piezometric Level datasets belonging to 24 years long time series (1986-2009). These methods, that 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. The 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; the spectral analysis and mono-fractal features of time series were assessed, in order to provide information on multy-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical-mathematical results were interpreted through field work that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.
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statistical analysis of rainfall river head and Piezometric Level data of central adriatic alluvial aquifers
2014Co-Authors: Alessandro Chiaudani, William Palmucci, Maurizio Polemio, Sergio RusiAbstract:1. Engineering and Geology Department "InGeo", "G. D'Annunzio" University, Chieti-Pescara (achiaudani@unich.it; william.palmucci@unich.it; s.rusi@unich.it) 2. National Research Council (CNR), Research Institute for the Hydrogeological Protection (IRPI), Bari (m.polemio@ba.irpi.cnr.it)
Maurizio Polemio - One of the best experts on this subject based on the ideXlab platform.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
Water, 2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract: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.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract:In this research, univariate and bivariate statistical methods were applied to rainfall, river and Piezometric Level datasets belonging to 24 years long time series (1986-2009). These methods, that 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. The 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; the spectral analysis and mono-fractal features of time series were assessed, in order to provide information on multy-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical-mathematical results were interpreted through field work that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.
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statistical analysis of rainfall river head and Piezometric Level data of central adriatic alluvial aquifers
2014Co-Authors: Alessandro Chiaudani, William Palmucci, Maurizio Polemio, Sergio RusiAbstract:1. Engineering and Geology Department "InGeo", "G. D'Annunzio" University, Chieti-Pescara (achiaudani@unich.it; william.palmucci@unich.it; s.rusi@unich.it) 2. National Research Council (CNR), Research Institute for the Hydrogeological Protection (IRPI), Bari (m.polemio@ba.irpi.cnr.it)
William Palmucci - One of the best experts on this subject based on the ideXlab platform.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
Water, 2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract: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.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract:In this research, univariate and bivariate statistical methods were applied to rainfall, river and Piezometric Level datasets belonging to 24 years long time series (1986-2009). These methods, that 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. The 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; the spectral analysis and mono-fractal features of time series were assessed, in order to provide information on multy-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical-mathematical results were interpreted through field work that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.
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statistical analysis of rainfall river head and Piezometric Level data of central adriatic alluvial aquifers
2014Co-Authors: Alessandro Chiaudani, William Palmucci, Maurizio Polemio, Sergio RusiAbstract:1. Engineering and Geology Department "InGeo", "G. D'Annunzio" University, Chieti-Pescara (achiaudani@unich.it; william.palmucci@unich.it; s.rusi@unich.it) 2. National Research Council (CNR), Research Institute for the Hydrogeological Protection (IRPI), Bari (m.polemio@ba.irpi.cnr.it)
Antonio Pasculli - One of the best experts on this subject based on the ideXlab platform.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
Water, 2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract: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.
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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study
2017Co-Authors: Alessandro Chiaudani, Diego Di Curzio, William Palmucci, Antonio Pasculli, Maurizio Polemio, Sergio RusiAbstract:In this research, univariate and bivariate statistical methods were applied to rainfall, river and Piezometric Level datasets belonging to 24 years long time series (1986-2009). These methods, that 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. The 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; the spectral analysis and mono-fractal features of time series were assessed, in order to provide information on multy-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical-mathematical results were interpreted through field work that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.