Remote sensing methods (InSAR) provide advanced methodologies for detecting and precisely measuring ground deformations (GD) of anthropogenic origin like trend and seasonal aquifer-system response to exploitation and recharge. We developed an algorithm that relies on the decomposition and clustering analysis of time series of GD to characterize the deformative behavior over a specific area due to anthropogenic activities related to water production. The vertical movements for monitoring points (MP) derived from InSAR measurements were decomposed into their seasonal (S) and trend (T) components. S is suitable for analyzing seasonal behavior of GD induced by oscillatory phenomena like aquifer withdrawal for agricultural purposes and seasonal rainfall recharges. T is more useful for measuring the impact of anthropogenic activities with a more linear and continuous behavior in time. Subsequently, the cluster analysis groups for all the MPs, which are grouped according to their similarities in S or T components, allows to define and quantify the deformative behavior of the system and the areal extent of the phenomenon. We applied this method to different areas in Emilia-Romagna in northern Italy characterized by strong superposition between groundwater production and other anthropogenic activities such as gas /storage. We focused on identifying different behaviors of the time series related to the different activities. We compared the results form cluster analysis with ancillary info such as: water well positions, amount of fluid production, rainfall precipitation, the structural geology and the land use maps of the studied areas comparing the different seasonal behaviors related to those attributes. The analysis of the trend and seasonal component allowed us to verify our results and the reliability of this method with data from literature. The results of this work enable us to quantify and isolate the effects of water production on GD from other anthropogenic effects.

Investigation of ground movements induced by water withdrawal via cluster-analysis applied to InSAR data / Garcia Navarro, Alberto Manuel; Rocca, Vera; Eid, Celine; Benetatos, Christoforos. - (2024). ( International Association of Hydrogeologists - World Groundwater Congress 2024).

Investigation of ground movements induced by water withdrawal via cluster-analysis applied to InSAR data

Garcia Navarro, Alberto Manuel;Rocca, Vera;Eid, Celine;Benetatos, Christoforos
2024

Abstract

Remote sensing methods (InSAR) provide advanced methodologies for detecting and precisely measuring ground deformations (GD) of anthropogenic origin like trend and seasonal aquifer-system response to exploitation and recharge. We developed an algorithm that relies on the decomposition and clustering analysis of time series of GD to characterize the deformative behavior over a specific area due to anthropogenic activities related to water production. The vertical movements for monitoring points (MP) derived from InSAR measurements were decomposed into their seasonal (S) and trend (T) components. S is suitable for analyzing seasonal behavior of GD induced by oscillatory phenomena like aquifer withdrawal for agricultural purposes and seasonal rainfall recharges. T is more useful for measuring the impact of anthropogenic activities with a more linear and continuous behavior in time. Subsequently, the cluster analysis groups for all the MPs, which are grouped according to their similarities in S or T components, allows to define and quantify the deformative behavior of the system and the areal extent of the phenomenon. We applied this method to different areas in Emilia-Romagna in northern Italy characterized by strong superposition between groundwater production and other anthropogenic activities such as gas /storage. We focused on identifying different behaviors of the time series related to the different activities. We compared the results form cluster analysis with ancillary info such as: water well positions, amount of fluid production, rainfall precipitation, the structural geology and the land use maps of the studied areas comparing the different seasonal behaviors related to those attributes. The analysis of the trend and seasonal component allowed us to verify our results and the reliability of this method with data from literature. The results of this work enable us to quantify and isolate the effects of water production on GD from other anthropogenic effects.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3006034
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