The objective of the study is to investigate whether the small amplitude surface deformation induced by hydrological variations in karstic areas and atmospheric loading can be detected using space-borne Synthetic Aperture Radar (SAR) data. The most disturbing factor is the atmospheric noise, because the wavelengths of its time and spatial variations are comparable to the hydrologic induced deformation to be detected. Methods used to mitigate the atmospheric noise can be divided into those using SAR data, and those with external datasets. Both aim at removing the effects of the stratified atmosphere and the turbulent mixing noise. In this study we use two different methods, the Common Scene Stacking (CSS) and the Global Atmospheric Correction Online Service (GACOS). The CSS is an iterative method for the estimation of the atmospheric contribution based on the fact that interferograms sharing a common scene contain the same delay contributions. GACOS is model-based and integrates the HRES-ECMWF and the GPS to generate high resolution maps of phase delays due to atmospheric moisture. We also calculate linear regressions between interferograms and topography to remove the effect of the stratified atmosphere with a moving window approach. We apply these methods on a rugged area straddling the Friuli Venezia Giulia and Veneto regions, which hosts in its center the Cansiglio Plateau, a karst massif characterized by epigenic and hypogenic elements typical of a mature karst system. The Cansiglio Plateau has been the subject of study in several researches that, using tiltmeters and GPS, have shown that there is a surface deformation in correspondence of heavy rainy events. The standard deviation of the residuals between the displacements obtained from the DInSAR data and the GPS time series are a measure of the adequacy of the corrections. Further, we perform the principal component analysis (PCA) across the area to analyze and describe the measured displacement in space and time. The data show an previously unidentified displacement rate, consisting in a strong linear trend with opposite sign limited to two nearby areas, which are located in a seismic area, the Alpago, north of the Santa Croce lake, and in other two areas, one north-west the Belluno municipality and one south-west the Pordenone municipality. We also include the loading models provided by the EOST Loading Service, of atmospheric, ocean and hydrological loading and found that much of the deformation signal measured by GPS, therefore also of the time series of displacement corrected with the GPS reference, is due to non-tidal atmospheric loading. After removing the atmospheric and ocean components from the GPS and DInSAR time series, we find that whenever the daily rains reaches 100 mm or more there is a deformation found on both GPS and DInSAR time series.
The objective of the study is to investigate whether the small amplitude surface deformation induced by hydrological variations in karstic areas and atmospheric loading can be detected using space-borne Synthetic Aperture Radar (SAR) data. The most disturbing factor is the atmospheric noise, because the wavelengths of its time and spatial variations are comparable to the hydrologic induced deformation to be detected. Methods used to mitigate the atmospheric noise can be divided into those using SAR data, and those with external datasets. Both aim at removing the effects of the stratified atmosphere and the turbulent mixing noise. In this study we use two different methods, the Common Scene Stacking (CSS) and the Global Atmospheric Correction Online Service (GACOS). The CSS is an iterative method for the estimation of the atmospheric contribution based on the fact that interferograms sharing a common scene contain the same delay contributions. GACOS is model-based and integrates the HRES-ECMWF and the GPS to generate high resolution maps of phase delays due to atmospheric moisture. We also calculate linear regressions between interferograms and topography to remove the effect of the stratified atmosphere with a moving window approach. We apply these methods on a rugged area straddling the Friuli Venezia Giulia and Veneto regions, which hosts in its center the Cansiglio Plateau, a karst massif characterized by epigenic and hypogenic elements typical of a mature karst system. The Cansiglio Plateau has been the subject of study in several researches that, using tiltmeters and GPS, have shown that there is a surface deformation in correspondence of heavy rainy events. The standard deviation of the residuals between the displacements obtained from the DInSAR data and the GPS time series are a measure of the adequacy of the corrections. Further, we perform the principal component analysis (PCA) across the area to analyze and describe the measured displacement in space and time. The data show an previously unidentified displacement rate, consisting in a strong linear trend with opposite sign limited to two nearby areas, which are located in a seismic area, the Alpago, north of the Santa Croce lake, and in other two areas, one north-west the Belluno municipality and one south-west the Pordenone municipality. We also include the loading models provided by the EOST Loading Service, of atmospheric, ocean and hydrological loading and found that much of the deformation signal measured by GPS, therefore also of the time series of displacement corrected with the GPS reference, is due to non-tidal atmospheric loading. After removing the atmospheric and ocean components from the GPS and DInSAR time series, we find that whenever the daily rains reaches 100 mm or more there is a deformation found on both GPS and DInSAR time series.
Hydrologic induced deformation in karstic areas and atmospheric loading effects observed with DInSAR
BARTOLA, MARCO
2023
Abstract
The objective of the study is to investigate whether the small amplitude surface deformation induced by hydrological variations in karstic areas and atmospheric loading can be detected using space-borne Synthetic Aperture Radar (SAR) data. The most disturbing factor is the atmospheric noise, because the wavelengths of its time and spatial variations are comparable to the hydrologic induced deformation to be detected. Methods used to mitigate the atmospheric noise can be divided into those using SAR data, and those with external datasets. Both aim at removing the effects of the stratified atmosphere and the turbulent mixing noise. In this study we use two different methods, the Common Scene Stacking (CSS) and the Global Atmospheric Correction Online Service (GACOS). The CSS is an iterative method for the estimation of the atmospheric contribution based on the fact that interferograms sharing a common scene contain the same delay contributions. GACOS is model-based and integrates the HRES-ECMWF and the GPS to generate high resolution maps of phase delays due to atmospheric moisture. We also calculate linear regressions between interferograms and topography to remove the effect of the stratified atmosphere with a moving window approach. We apply these methods on a rugged area straddling the Friuli Venezia Giulia and Veneto regions, which hosts in its center the Cansiglio Plateau, a karst massif characterized by epigenic and hypogenic elements typical of a mature karst system. The Cansiglio Plateau has been the subject of study in several researches that, using tiltmeters and GPS, have shown that there is a surface deformation in correspondence of heavy rainy events. The standard deviation of the residuals between the displacements obtained from the DInSAR data and the GPS time series are a measure of the adequacy of the corrections. Further, we perform the principal component analysis (PCA) across the area to analyze and describe the measured displacement in space and time. The data show an previously unidentified displacement rate, consisting in a strong linear trend with opposite sign limited to two nearby areas, which are located in a seismic area, the Alpago, north of the Santa Croce lake, and in other two areas, one north-west the Belluno municipality and one south-west the Pordenone municipality. We also include the loading models provided by the EOST Loading Service, of atmospheric, ocean and hydrological loading and found that much of the deformation signal measured by GPS, therefore also of the time series of displacement corrected with the GPS reference, is due to non-tidal atmospheric loading. After removing the atmospheric and ocean components from the GPS and DInSAR time series, we find that whenever the daily rains reaches 100 mm or more there is a deformation found on both GPS and DInSAR time series.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/177858
URN:NBN:IT:UNITS-177858