Determining the detailed Moho topography is crucial for understanding the Earth's geodynamic processes. Inversion of the Moho depth in the frequency-domain from gravity observations is an effective tool for this purpose. However, existing inversion methods such as the Parker-Oldenburg (P-O) and Bott-Parker (B-P) methods face challenges including non-convergence and noise amplification. We have developed a modified B-P (mB-P) method to estimate the Moho depth with variable density contrast from gravity data. The proposed method casts exponential density-based Parker’s formula into the iterative continuation theoretical framework, allowing the use of an adaptive filter that has been proven effective in iterative continuation studies. This modification retains the efficiency of the B-P method while offering improved control over solution stability. Gauss-Fast Fourier Transform was adopted to improve the precision of the forward and inverse Fourier transforms in the inversion process. Furthermore, the mathematical connection between the P-O and B-P methods was established. Specifically, the B-P method acts as a low-pass filter to reduce the downward continuation effect in the P-O method and recovers the nonlinear topography through the nonlinearity of the fitting function. Synthetic inversion tests demonstrate that the proposed method achieves superior inversion accuracy compared to the P-O and B-P methods under 3% gravity observations noise and significantly outperforms the P-O method in terms of computational efficiency. We applied the mB-P method to estimate the Moho depth beneath the Tibetan Plateau using satellite gravity data and seismic data, achieving reasonable agreement between the gravimetric model and seismic data.
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