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Insights on Terrain Roughness and Density Variations for Geoid Models and Orthometric Heights: A quantitative comparison in the Konya Closed Basin, Türkiye and Auvergne, France

Geophysical Journal International - Thu, 09/18/2025 - 00:00

SummaryRecent advancements in high-resolution Digital Elevation Models (DEMs) derived from LIDAR and satellite radar technologies have added a new dimension to the determination of height systems and geoid models. However, their benefits are limited by simplified assumptions inherited from past practices. In mountainous areas, taking into consideration of topography as the Bouguer plate or employing inaccurate terrain corrections can constitute to a problematic approach. Even though the gravity reduction procedures mentioned above have been enhanced in geoid determination studies, the Helmert orthometric heights based on them are still used in some countries such as Türkiye and Taiwan. It is inevitable that this contradiction will negatively affect geoid modeling studies that are intended to be verified or combined with GNSS/leveling data. Another issue arises by ignoring density variations of topographic masses. Through a comparative analysis, this study reviews combined and individual impacts of terrain roughness and density variations on geoid models in the Konya Closed Basin (KCB) and the Auvergne regions, with a focus on their distinctive topographical characteristics. Using 1″ DEMs of the SRTM mission and 30″ UNB_TopoDensT lateral density models, we reveal that terrain corrections in gravity reductions significantly affect geoid heights, with deviations of up to 11.9 cm in KCB and 4.2 cm in Auvergne. Incorporating lateral density models has resulted in geoid height discrepancies of up to 26.8 cm in KCB and 6.7 cm in Auvergne. A validation strategy implemented through GNSS/leveling paths showed that terrain corrections markedly improved geoid model accuracy, particularly in relation to elevation. However, the contribution of the UNB_TopoDensT model to geoid accuracy is questionable in terms of accuracy. Notably, applying density values below 2.4 g·cm⁻³ in high-altitude regions can lead to disruptive effects on geoid determination. This result is underscoring of the need on a realistic modeling of topographical densities in high elevated and rugged terrains. A further conclusion that emerged from these analyses is that gravimetric geoid models should be verified by rigorous orthometric heights, which are observed to fit them better at the 1-2 cm level, instead of the Helmert orthometric heights.

An efficient 3D inversion scheme for continental scale Magnetotelluric data

Geophysical Journal International - Thu, 09/18/2025 - 00:00

AbstractThis study introduces a novel method for performing 3D inversion of magnetotelluric (MT) data. The proposed method, referred to as the radiation boundary scheme, employs a two-step simulation strategy for the computation of both forward and adjoint responses. One of the key advantages of the scheme is its ability to handle arbitrarily shaped inversion domains, thereby optimizing the number of unknown model parameters by discarding model parameters that are not constrained by the data. Consequently, it significantly improves accuracy and computational speed as compared to traditional inversion algorithms. The effectiveness of the developed algorithm is demonstrated through a comprehensive analysis of 3D inversion using synthetic and continental-scale (SAMTEX) MT data. The method’s efficiency facilitates a detailed analysis of large-scale MT data inversion. Through numerical experiments, it is observed that using a coarse mesh for inversion, the resolution is compromised in the shallower part, resulting in inferior imaging and, consequently, affecting the estimation of resistivity value in the deeper subsurface. The detailed numerical experiments indicate that performing a fine-scale inversion on a small portion of the survey data utilizing a coarsely inverted model may run into a local minimum. Hence, caution should be exercised in employing such an approach. Instead, the investigations suggest simultaneously executing a fine-scale inversion on the entire data set. The forward/adjoint problem can be solved with a two-order higher tolerance as compared to the conventional finite-difference-based inversion algorithm. Therefore, the proposed algorithm holds significant value for the MT inversion of large data sets.