4.7 Article

Hydrologically Induced Karst Deformation: Insights From GPS Measurements in the Adria-Eurasia Plate Boundary Zone

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JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
卷 123, 期 5, 页码 4413-4430

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AMER GEOPHYSICAL UNION
DOI: 10.1002/2017JB015252

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Global Positioning System; time series analysis; Alps; karsts; precipitation; hydrology

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We apply a blind source separation algorithm to the ground displacement time series recorded at continuous Global Positioning System (GPS) stations in the European Eastern Alps and Northern Dinarides. As a result, we characterize the temporal and spatial features of several deformation signals. Seasonal displacements are well described by loading effects caused by Earth surface mass redistributions. More interestingly, we highlight a horizontal, nonseasonal, transient deformation signal, with spatially variable amplitudes and directions. The stations affected by this signal reverse the sense of movement with time, implying a sequence of dilatational and compressional deformation that is oriented normal to rock fractures in karst areas. The temporal evolution of this deformation signal is correlated with the history of cumulated precipitations at monthly time scales. This transient horizontal deformation can be explained by pressure changes associated with variable water levels within vertical fractures in the vadose zones of karst systems. The water level changes required to open or close these fractures are consistent with the fluctuations of precipitation and with the dynamics of karst systems. Plain Language Summary Groundwater levels in aquifers are commonly monitored at local scales by wells. Space geodesy, however, can provide measurements of time-variable deformation associated with variable groundwater levels at mesoscales. Here we show how Global Positioning System (GPS) time series from regional networks can precisely measure spatially integrated deformation signals related to variable water levels in karst aquifers, which are an important source of drinking water worldwide. Blind source separation algorithms, as the one used in this work, help scientists to detect and precisely measure ground displacements associated with both tectonic and nontectonic processes, improving our ability to describe the space and time evolution of surface movements and the dynamics of faults and geological bodies.

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