EGU21-166
https://doi.org/10.5194/egusphere-egu21-166
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Using the coupled machine learning-evolutionary optimization algorithms and climate change projection models to assess the distribution of groundwater-origin aufeis in the North-East of Northern Hemisphere and their dynamic in a changing climate

Olga Makarieva1,2, Aiding Kornejady3, Andrey Shikhov4, Esmaeil Silakhori3, Nataliia Nesterova1,2, Abbas Goli Jirandeh3, Andrey Ostashov2, Hadi Alizadeh3, and Anastasiya Zemlyanskova1,2
Olga Makarieva et al.
  • 1St. Petersburg State University, Institute of Earth Sciences, Department of Land Hydrology, St. Petersburg, Russian Federation (omakarieva@gmail.com)
  • 2North-East Permafrost Station, Melnikov Permafrost Institute, Magadan, Russia
  • 3Spatial Sciences Innovators Consulting Engineering Company, Tehran, Iran
  • 4Perm State University, Perm, Russia

How to cite: Makarieva, O., Kornejady, A., Shikhov, A., Silakhori, E., Nesterova, N., Goli Jirandeh, A., Ostashov, A., Alizadeh, H., and Zemlyanskova, A.: Using the coupled machine learning-evolutionary optimization algorithms and climate change projection models to assess the distribution of groundwater-origin aufeis in the North-East of Northern Hemisphere and their dynamic in a changing climate, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-166, https://doi.org/10.5194/egusphere-egu21-166, 2021.

This abstract has been withdrawn on 11 Mar 2021.