Like other sedimentary plains, the Po Plain in Northern Italy has largely subsided due to natural processes and human activities. Displacements of the Earth surface of hydrological origin are caused by groundwater changes, which in turn, are expected to be related to rainfall changes. In the Bologna metropolitan area (located in the Southeastern border of Po Plain), the 2010 politic decision of dismissing civil water supply from the groundwater withdrawal has provided us the opportunity to test a methodology for the retrieval of an anthropic effect in two different data sets: vertical displacements measured by continuous GNSS sites and piezometric water table fluctuations. The data sets have been analyzed by means of the Principal Component Analysis (PCA) and compared to rainfall time series from the Po Plain rain gauges. Several piezometers undergo a clear increase in the water level following the withdrawal decrease. Differently, the anthropic induced surface displacements are significantly smaller than the ones induced by rainfall. Accordingly, without a multivariate analysis such an effect on vertical displacements would have remained hidden in the raw time series. Only looking at the spatial distribution of the principal components we have highlighted that anthropic effects are local and present even in GNSS data, entailing for the 2010 case a decrease of about 4 mm/y of vertical velocity in some sites closest the withdrawal wells. Moreover, the multivariate analysis allowed us to assess that, on time scales larger than months, the rainfall-related hydrological response of vertical displacement depends on the geological setting. In the Apennines chain a water level increase causes subsidence, in agreement with the predictions of elastic models, whereas in the Po Plain it causes uplift, suggesting a dominant poro-elastic response, in agreement with the guess that the subsidence of the Po Plain is related to soil compaction. Our results suggest that in cases of the aquifers over-exploitation, a PCA analyses and the combined use of different observables such as GNSS, piezometers time series, rainfall data, geological setting allow getting a correct identification of the anthropic and natural signals.

The interaction between displacements and water level changes due to natural and anthropogenic effects in the Po Plain (Italy): The different point of view of GNSS and piezometers

Cenni N.
;
2021

Abstract

Like other sedimentary plains, the Po Plain in Northern Italy has largely subsided due to natural processes and human activities. Displacements of the Earth surface of hydrological origin are caused by groundwater changes, which in turn, are expected to be related to rainfall changes. In the Bologna metropolitan area (located in the Southeastern border of Po Plain), the 2010 politic decision of dismissing civil water supply from the groundwater withdrawal has provided us the opportunity to test a methodology for the retrieval of an anthropic effect in two different data sets: vertical displacements measured by continuous GNSS sites and piezometric water table fluctuations. The data sets have been analyzed by means of the Principal Component Analysis (PCA) and compared to rainfall time series from the Po Plain rain gauges. Several piezometers undergo a clear increase in the water level following the withdrawal decrease. Differently, the anthropic induced surface displacements are significantly smaller than the ones induced by rainfall. Accordingly, without a multivariate analysis such an effect on vertical displacements would have remained hidden in the raw time series. Only looking at the spatial distribution of the principal components we have highlighted that anthropic effects are local and present even in GNSS data, entailing for the 2010 case a decrease of about 4 mm/y of vertical velocity in some sites closest the withdrawal wells. Moreover, the multivariate analysis allowed us to assess that, on time scales larger than months, the rainfall-related hydrological response of vertical displacement depends on the geological setting. In the Apennines chain a water level increase causes subsidence, in agreement with the predictions of elastic models, whereas in the Po Plain it causes uplift, suggesting a dominant poro-elastic response, in agreement with the guess that the subsidence of the Po Plain is related to soil compaction. Our results suggest that in cases of the aquifers over-exploitation, a PCA analyses and the combined use of different observables such as GNSS, piezometers time series, rainfall data, geological setting allow getting a correct identification of the anthropic and natural signals.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3453378
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