In this study, the statistical relations between meteorological recharge and hydrodynamic and hydrochemical behavior of the Verde spring, the main discharge of the Majella Carbonate aquifer system (central Apennine) exploited for drinking and hydroelectric purposes, were synthesized. The results allowed to identify several flow paths, characterized by different sizes, hydraulic conductivities, and distances from the spring, that get activated depending on the type (rain or snowmelt) and the amount of the inflow. In order to get a deeper insight on the Majella system groundwater flow, multiparameter daily time-series were considered, all related to the same time period (1803 days; about 5 years between 1997 and 2002) and collected in different monitoring point all over the Majella aquifer. In detail, they were analyzed: the snow cover thickness, the rainfall data, the Verde spring discharge, the electrical conductivity and temperature of the Verde spring. The raw and residual multiparameter time-series were then analyzed by the Autocorrelation Function (ACF) and Cross-Correlation Function (CCF), to investigate how the spring parameters react to the different inflows. The results obtained by the ACF and the raw and residual CCFs, together with the knowledge of the hydrogeological features of the Majella aquifer, allowed to implement a refined conceptual model. The Autocorrelation analysis showed that the variability of the spring discharge and Electrical conductivity time-series can be accounted by the combined effect of both rainfall (i.e. random component) and snowmelt (i.e. systematic component) recharge. The results obtained clearly demonstrated that the snowmelt contribution is predominant with respect to the rainfall one. The travel times in the unsaturated and saturated zones of the water moving toward the Verde spring and the aquifer recharge modes depend on the different inflows (i.e. snowmelt and rainfall), their distribution in the recharge areas, their intensity and distribution in time. In detail, the multiparameter time-series analyses allowed to identify several recharge modes related to different flow paths, that are characterized by different sizes, hydraulic conductivities and distances from the spring, in both the unsaturated and saturated zones. The level of detail obtained by the multiparameter time-series analyses is high, although below the one provided by tracer tests. In fact, this methodological approach allowed to account for small changes in the spring parameters, such as the electrical conductivity (about ± 15 S/cm) and temperature (about ± 0.1° C), that are considered meaningless. The study demonstrated that the multiparameter hydrodynamic and hydrochemical time-series analyses, related to heterogenous fractured and/or partially karst aquifer systems, can provide more detailed information about the groundwater flow and the recharge modes, without using tracer tests.

The role of snow melting and rainfall on the discharge and physico-chemical characteristics of springs: a statistical analysis in Central Apennines

Chiaudani A.;Di Curzio D.;Rusi S.
2019

Abstract

In this study, the statistical relations between meteorological recharge and hydrodynamic and hydrochemical behavior of the Verde spring, the main discharge of the Majella Carbonate aquifer system (central Apennine) exploited for drinking and hydroelectric purposes, were synthesized. The results allowed to identify several flow paths, characterized by different sizes, hydraulic conductivities, and distances from the spring, that get activated depending on the type (rain or snowmelt) and the amount of the inflow. In order to get a deeper insight on the Majella system groundwater flow, multiparameter daily time-series were considered, all related to the same time period (1803 days; about 5 years between 1997 and 2002) and collected in different monitoring point all over the Majella aquifer. In detail, they were analyzed: the snow cover thickness, the rainfall data, the Verde spring discharge, the electrical conductivity and temperature of the Verde spring. The raw and residual multiparameter time-series were then analyzed by the Autocorrelation Function (ACF) and Cross-Correlation Function (CCF), to investigate how the spring parameters react to the different inflows. The results obtained by the ACF and the raw and residual CCFs, together with the knowledge of the hydrogeological features of the Majella aquifer, allowed to implement a refined conceptual model. The Autocorrelation analysis showed that the variability of the spring discharge and Electrical conductivity time-series can be accounted by the combined effect of both rainfall (i.e. random component) and snowmelt (i.e. systematic component) recharge. The results obtained clearly demonstrated that the snowmelt contribution is predominant with respect to the rainfall one. The travel times in the unsaturated and saturated zones of the water moving toward the Verde spring and the aquifer recharge modes depend on the different inflows (i.e. snowmelt and rainfall), their distribution in the recharge areas, their intensity and distribution in time. In detail, the multiparameter time-series analyses allowed to identify several recharge modes related to different flow paths, that are characterized by different sizes, hydraulic conductivities and distances from the spring, in both the unsaturated and saturated zones. The level of detail obtained by the multiparameter time-series analyses is high, although below the one provided by tracer tests. In fact, this methodological approach allowed to account for small changes in the spring parameters, such as the electrical conductivity (about ± 15 S/cm) and temperature (about ± 0.1° C), that are considered meaningless. The study demonstrated that the multiparameter hydrodynamic and hydrochemical time-series analyses, related to heterogenous fractured and/or partially karst aquifer systems, can provide more detailed information about the groundwater flow and the recharge modes, without using tracer tests.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11564/710644
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