Wavelet analysis of GRACE K-band range rate measurements related to Urmia Basin

نوع مقاله: مقاله تحقیقی‌ (پژوهشی‌)

نویسندگان

1 گروه مهندسی نقشه برداری، دانشگاه صنعتی اراک، اراک، ایران

2 دانشکده مهندسی و نقشه برداری دانشگاه تهران

چکیده

Space-borne gravity data from Gravity Recovery and Climate Experiment (GRACE), as well as some other in situ and remotely sensed satellite data have been used to determine water storage changes in Lake Urmia Basin (Iran). As usual, the GRACE products are derived from precise inter-satellite range rate measurements converted to different formats such as spherical harmonic coefficients and equivalent water thicknesses of juxtaposed tiles in which the corresponding mass anomalies are estimated, resulting in missing information during these time-consuming processes. In this paper, GRACE level 1B K-band range rates related to Urmia Basin are corrected for non-hydrological processes and the resulting time series are analyzed using wavelet transformation. On the one hand, direct corrected range rates are employed to make an unevenly spaced time series. In addition, the monthly mean measurements of the same type are applied to create a uniform time series. Therefore, a wavelet-based least-squares spectral analysis method is introduced to extract the general behavior of irregularly sampled time series. In addition, the classical wavelet transformation is used to analyze the monthly averaged time series. The results indicate that the extracted coarse parts of the corrected range rates have significantly changed between 2007 and 2008, which are in good agreement with the total water storage (TWS) changes modeled in Urmia Basin, as well as with the similar previous research findings. Besides, the time-frequency behavior of both TWS changes and monthly averaged range rate time series show that the extracted annual constituents, as the main parts of the signals, have mainly weakened after 2007.

کلیدواژه‌ها


عنوان مقاله [English]

Wavelet analysis of GRACE K-band range rate measurements related to Urmia Basin

نویسندگان [English]

  • Amirreza Moradi 1
  • Mohammad Ali Sharifi 2
1 Department of Surveying Engineering, Arak University of Technology, Arak, Iran
2 School of Surveying and Geomatics Engineering, College of Engineering, University of Tehran, Tehran, Iran
چکیده [English]

Space-borne gravity data from Gravity Recovery and Climate Experiment (GRACE), as well as some other in situ and remotely sensed satellite data have been used to determine water storage changes in Lake Urmia Basin (Iran). As usual, the GRACE products are derived from precise inter-satellite range rate measurements converted to different formats such as spherical harmonic coefficients and equivalent water thicknesses of juxtaposed tiles in which the corresponding mass anomalies are estimated, resulting in missing information during these time-consuming processes. In this paper, GRACE level 1B K-band range rates related to Urmia Basin are corrected for non-hydrological processes and the resulting time series are analyzed using wavelet transformation. On the one hand, direct corrected range rates are employed to make an unevenly spaced time series. In addition, the monthly mean measurements of the same type are applied to create a uniform time series. Therefore, a wavelet-based least-squares spectral analysis method is introduced to extract the general behavior of irregularly sampled time series. In addition, the classical wavelet transformation is used to analyze the monthly averaged time series. The results indicate that the extracted coarse parts of the corrected range rates have significantly changed between 2007 and 2008, which are in good agreement with the total water storage (TWS) changes modeled in Urmia Basin, as well as with the similar previous research findings. Besides, the time-frequency behavior of both TWS changes and monthly averaged range rate time series show that the extracted annual constituents, as the main parts of the signals, have mainly weakened after 2007.

کلیدواژه‌ها [English]

  • Grace
  • least squares approximation
  • time series analysis
  • wavelet transform
  • Urmia Basin
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