M.Sc. Georgy Ayzel

Kontakt

Universität Potsdam,
Institut für Erd- und Umweltwissenschaften

M.Sc. Georgy Ayzel
Haus 1, Raum 1.29

Karl-Liebknecht-Str. 24-25
14476 Potsdam-Golm
E-Mail:
ayzel@uni-potsdam.de
Telefon:
+49 331 977 6454
Fax:
+49 331 977 2092
M.Sc. Georgy Ayzel

 

  • Biografie
  • Forschung
  • Publikationen

Biografie

Sept. 2006 - Jul. 2011
Specialist in Hydrology (Moscow State University, Russia)
Nov. 2011 - Oct. 2014
Candidate of Science (Institute of Water Problems, Moscow, Russia)
Nov. 2014 - Mar. 2017
Researcher (Institute of Water Problems, Moscow, Russia)
Apr. 2017 - Present
PhD candidate at University of Potsdam (Geo.X "Geo Data Science" project fellow)

Forschung

Hydrological modeling

Using LSM model SWAP for hydrological modeling and model parameters regionalization studies for tens of Russian and MOPEX (USA) basins. Implementation of widely-used lumped conceptual hydrological models — HBV, GR4J, SIMHYD — for daily runoff simulations for three large basins of the Russian Arctic (Nadym, Pur, and Taz rivers).

Machine learning

Implementation of regression-based machine learning techniques for data-driven rainfall-runoff and snow formation modeling. Development of runoff post-processing procedure based on coupling hydrological models outputs and machine learning algorithms.

Software development

Development and distribution of Lumped Hydrological Models Playground (LHMP) and Modern Modelling and Forecasting System (MORS) in a reproducible way via git and docker-containers. Gridded Daily Runoff Dataset (GDRD) development and its evaluation for prediction in ungauged basins. For more information, please refer to github.com/hydrogo.

Publikationen

  1. Gusev, E.M., Ayzel, G.V. & Nasonova, O.N. Runoff evaluation for ungauged watersheds by SWAP model. 1. Application of artificial neural networks. Water Resour (2017) 44: 169. doi:10.1134/S0097807817020038
  2. Gusev, E.M., Nasonova, O.N., Dzhogan, L.Y., Ayzel G.V. Simulating the formation of river runoff and snow cover in the northern West Siberia. Water Resour (2015) 42: 460. doi:10.1134/S0097807815040065
  3. Nasonova, O.N., Gusev, E.M. & Ayzel, G.V. Optimizing land surface parameters for simulating river runoff from 323 MOPEX-watersheds. Water Resour (2015) 42: 186. doi:10.1134/S0097807815020104
  4. Gusev, E.M., Nasonova, O.N., Dzhogan, L.Y., Ayzel, G.V. Scenario prediction of changes in water balance components of the Olenek and Indigirka rivers in the context of possible climate change in the region of the Republic of Sakha (Yakutia). Water Resour (2014) 41: 748. doi:10.1134/S0097807814030099
  5. Chalov, S.R., Esin, E.V. & Aizel, G.V. Geological factors governing ichthyofauna formation in rivers of Semlyachikskii volcanic region (Eastern Kamchatka). Water Resour (2014) 41: 242. doi:10.1134/S0097807814020043
  6. Gusev, E.M., Nasonova, O.N., Dzhogan, L.Y., Aizel, G.V. Modeling streamflow of the Olenek and Indigirka rivers using land surface model SWAP. Water Resour (2013) 40: 535. doi:10.1134/S0097807813030056

Biografie

Sept. 2006 - Jul. 2011
Specialist in Hydrology (Moscow State University, Russia)
Nov. 2011 - Oct. 2014
Candidate of Science (Institute of Water Problems, Moscow, Russia)
Nov. 2014 - Mar. 2017
Researcher (Institute of Water Problems, Moscow, Russia)
Apr. 2017 - Present
PhD candidate at University of Potsdam (Geo.X "Geo Data Science" project fellow)

Forschung

Hydrological modeling

Using LSM model SWAP for hydrological modeling and model parameters regionalization studies for tens of Russian and MOPEX (USA) basins. Implementation of widely-used lumped conceptual hydrological models — HBV, GR4J, SIMHYD — for daily runoff simulations for three large basins of the Russian Arctic (Nadym, Pur, and Taz rivers).

Machine learning

Implementation of regression-based machine learning techniques for data-driven rainfall-runoff and snow formation modeling. Development of runoff post-processing procedure based on coupling hydrological models outputs and machine learning algorithms.

Software development

Development and distribution of Lumped Hydrological Models Playground (LHMP) and Modern Modelling and Forecasting System (MORS) in a reproducible way via git and docker-containers. Gridded Daily Runoff Dataset (GDRD) development and its evaluation for prediction in ungauged basins. For more information, please refer to github.com/hydrogo.

Publikationen

  1. Gusev, E.M., Ayzel, G.V. & Nasonova, O.N. Runoff evaluation for ungauged watersheds by SWAP model. 1. Application of artificial neural networks. Water Resour (2017) 44: 169. doi:10.1134/S0097807817020038
  2. Gusev, E.M., Nasonova, O.N., Dzhogan, L.Y., Ayzel G.V. Simulating the formation of river runoff and snow cover in the northern West Siberia. Water Resour (2015) 42: 460. doi:10.1134/S0097807815040065
  3. Nasonova, O.N., Gusev, E.M. & Ayzel, G.V. Optimizing land surface parameters for simulating river runoff from 323 MOPEX-watersheds. Water Resour (2015) 42: 186. doi:10.1134/S0097807815020104
  4. Gusev, E.M., Nasonova, O.N., Dzhogan, L.Y., Ayzel, G.V. Scenario prediction of changes in water balance components of the Olenek and Indigirka rivers in the context of possible climate change in the region of the Republic of Sakha (Yakutia). Water Resour (2014) 41: 748. doi:10.1134/S0097807814030099
  5. Chalov, S.R., Esin, E.V. & Aizel, G.V. Geological factors governing ichthyofauna formation in rivers of Semlyachikskii volcanic region (Eastern Kamchatka). Water Resour (2014) 41: 242. doi:10.1134/S0097807814020043
  6. Gusev, E.M., Nasonova, O.N., Dzhogan, L.Y., Aizel, G.V. Modeling streamflow of the Olenek and Indigirka rivers using land surface model SWAP. Water Resour (2013) 40: 535. doi:10.1134/S0097807813030056