<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To estimate Moho depth, geoid, gravity anomaly, and other geopotential functionals, gravity data is needed. But, gravity survey was not collected in equal distribution in Ethiopia, as the data forming part of the survey were mainly collected on accessible roads. To determine accurate Moho depth using Global Gravity Models (GGMs) for the study area, evaluation of GGMs is needed based on the available terrestrial gravity data. Moho depth lies between 28 km and 32 km in Afar. Gravity disturbances (GDs) were calculated for the terrestrial gravity data and the recent GGMs for the study area. The model-based GDs were compared with the corresponding GD obtained from the terrestrial gravity data and their differences in terms of statistical comparison parameters for determining the best fit GGM at a local scale in Afar. The largest standard deviation (SD) (36.10 mGal) and root mean square error (RMSE) (39.00 mGal) for residual GD and the lowest correlation with the terrestrial gravity (0.61 mGal) were obtained by the satellite-only model (GO_CONS_GCF_2_DIR_R6). The next largest SD (21.27 mGal) and RMSE (25.65 mGal) for residual GD were obtained by the combined gravity model (XGM2019e_2159), which indicates that it is not the best fit model for the study area as compared with the other two GGMs. In general, the result showed that the combined models are more useful tools for modeling the gravity field in Afar than the satellite-only GGMs. But, the study clearly revealed that for the study area, the best model in comparison with the others is the EGM2008, while the second best model is the EIGEN6C4.</p>
</abstract>

To estimate Moho depth, geoid, gravity anomaly, and other geopotential functionals, gravity data is needed. But, gravity survey was not collected in equal distribution in Ethiopia, as the data forming part of the survey were mainly collected on accessible roads. To determine accurate Moho depth using Global Gravity Models (GGMs) for the study area, evaluation of GGMs is needed based on the available terrestrial gravity data. Moho depth lies between 28 km and 32 km in Afar. Gravity disturbances (GDs) were calculated for the terrestrial gravity data and the recent GGMs for the study area. The model-based GDs were compared with the corresponding GD obtained from the terrestrial gravity data and their differences in terms of statistical comparison parameters for determining the best fit GGM at a local scale in Afar. The largest standard deviation (SD) (36.10 mGal) and root mean square error (RMSE) (39.00 mGal) for residual GD and the lowest correlation with the terrestrial gravity (0.61 mGal) were obtained by the satellite-only model (GO_CONS_GCF_2_DIR_R6). The next largest SD (21.27 mGal) and RMSE (25.65 mGal) for residual GD were obtained by the combined gravity model (XGM2019e_2159), which indicates that it is not the best fit model for the study area as compared with the other two GGMs. In general, the result showed that the combined models are more useful tools for modeling the gravity field in Afar than the satellite-only GGMs. But, the study clearly revealed that for the study area, the best model in comparison with the others is the EGM2008, while the second best model is the EIGEN6C4.

Evaluation of GGMs Based on the Terrestrial Gravity Disturbance and Moho Depth in Afar, Ethiopia

Geodesy and Geodynamics Research and Development Department, Entoto Observatory and Research Centre (EORC)

Artificial Satellites

This work is licensed under the Creative Commons Attribution 4.0 International License.

To estimate Moho depth, geoid, gravity anomaly, and other geopotential functionals, gravity data is needed. But, gravity survey was not collected in equal...

Evaluation of GGMs Based on the Terrestrial Gravity Disturbance and Moho Depth in Afar, Ethiopia

Online veröffentlicht: 08. Okt. 2021

Seitenbereich: 78 - 100

DOI: https://doi.org/10.2478/arsa-2021-0007

Schlüsselwörter
global gravity model, spectral analysis, Earth’s gravity field modeling, residual gravity disturbance, gravity disturbance

© 2021 Eyasu Alemu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Evaluation of GGMs Based on the Terrestrial Gravity Disturbance and Moho Depth in Afar, Ethiopia

Online veröffentlicht: 08. Okt. 2021

Seitenbereich: 78 - 100

DOI: https://doi.org/10.2478/arsa-2021-0007

Schlüsselwörterglobal gravity model, spectral analysis, Earth’s gravity field modeling, residual gravity disturbance, gravity disturbance

© 2021 Eyasu Alemu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
global gravity model, spectral analysis, Earth’s gravity field modeling, residual gravity disturbance, gravity disturbance