EGU22-1545, updated on 15 Jan 2023
EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

A first attempt at a continental scale geothermal heat flow model for Africa

Magued Al-Aghbary1,2, Mohamed Sobh1, and Christian Gerhards1
Magued Al-Aghbary et al.
  • 1TU Bergakademie Freiberg, Institute for Geophysics and Geoinformatics, Freiberg, Germany (
  • 2Centre d'Etude et de Recherche de Djibouti, Institut des Sciences de la Terre, Djibouti City, Djibouti

Reliable and direct geothermal heat flow (GHF) measurements in Africa are sparse. It is a challenging task to create a map that reflects the GHF and covers the African continent in in its entirety.

We approached this task by training a random forest regression algorithm. After carefully tuning the algorithm's hyperparameters, the trained model relates the GHF to various geophysical and geological covariates that are considered to be statistically significant for the GHF. The covariates are mainly global datasets and models like Moho depth, Curie depth, gravity anomalies. To improve the predictions, we included some regional datasets. The quality and reliability of the datasets are assessed before the algorithm is trained.

The model's performance is validated against Australia, which has a large database of GHF measurements. The predicted GHF map of Africa shows acceptable performance indicators and is consistent with existing recognized GHF maps of Africa.

How to cite: Al-Aghbary, M., Sobh, M., and Gerhards, C.: A first attempt at a continental scale geothermal heat flow model for Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1545,, 2022.