Geo-Hydroinformatics

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Dr. Mehdi H. Afshar

I obtained a Bachelor of Science (BSc) in Water Engineering and Master of Science (MSc) in Water Resources Engineering from Urmia University in Iran. Subsequently, I got a Doctor of Philosophy (PhD) in Civil Engineering – Water Resources from the Middle East Technical University (METU) in Turkey (dissertation download link). 
I served as an Assistant Professor at Middle East Technical University in Ankara, Turkey (Jan 2022 – Aug 2023). Prior to this, I worked as a Post-Doctoral Researcher at the John Innes Centre in Norwich, UK (Apr 2021 – Dec 2021) and The University of Manchester in the UK (Aug 2019 – Sep 2020). My main research interest is related to coupling statistical-, machine learning-, and process-based models to improve the accuracy of prediction models in estimation of different variables influencing water-food security.
Since August 2023, I have been contributing as a Research Associate at the Technical University of Hamburg (TUHH), Germany. Within TUHH, my current focus revolves around advancing soil health and understanding the intricate relationship between soil parameters and climate change scenarios. I am deeply engaged in the development of pioneering solutions aimed at predicting the state and changes in soil functions on a global scale. My work predominantly centers on continental Europe, where I delve into concepts of soil degradation, soil salinization, and overall soil health. A significant portion of my research aligns with the Horizon Europe project AI4SoilHealth (please click here for more information).

Contact

Dr. Mehdi H. Afshar
Hamburg University of Technology
Institute of Geo-Hydroinformatics B-9
Am Schwarzenberg-Campus 3 (E)
21073 Hamburg, Germany
Email: mehdi.afshar(at)tuhh(dot)de
Phone: +49 40 42878 2878
Website: www.tuhh.de/ghi

Journal Papers
  • Afshar, M.H., Sorman, A.U., Tosunoglu, F. (2023) Three-dimensional copula framework for early warning of agricultural droughts using meteorological drought and vegetation health conditions, Hydrological Sciences Journal, https://doi.org/10.1080/02626667.2024.2326187.
  • Corcoran, E., Afshar, M.H., Curceac, S., Lashkari, A., Raza, M.M., Ahnert, S., Mead, A., Morris, R. (2023) Current Data and Modelling Bottlenecks for Predicting Crop Yields in the United Kingdom, Frontiers in Sustainable Food Systems, https://doi.org/10.3389/fsufs.2023.1023169.
  • Afshar, M.H., Bulut, B., Duzenli, E., Amjad, M., Yilmaz, M.T. (2022) Global spatiotemporal consistency between meteorological and soil moisture drought indices, Agricultural and Forest Meteorology 316, 108848, https://doi.org/10.1016/j.agrformet.2022.108848. 
  • Afshar, M.H., Al-Yaari, A., Yilmaz, M.T. (2021) Comparative evaluation of microwave L-band VOD and optical NDVI for agriculture drought detection over central Europe, Remote Sensing, 13 (7), 1251, https://doi.org/10.3390/rs13071251.
  • Afshar, M.H., Foster, T., Higginbottom, T.P., Parkes, B., Hufkens, K., Mansabdar, S., Ceballos, F., Kramer, B (2021). Improving performance of index insurance using crop models and phenological monitoring, Remote Sensing, 13 (5), 924, https://doi.org/10.3390/rs13050924.
  • Afshar, M.H., Sorman, AU., Tosunoglu, F., Bulut, B., Yilmaz, M.T., DanandehMehr, A. (2020) Climate change impact assessment on mild and extreme drought events using copulas over Ankara, Turkey, Theoretical and Applied Climatology, https://doi.org/10.1007/s00704-020-03257-6. 
  • DanandehMehr, A., Sorman, AU., Kahya, E., Afshar, M.H. (2020) Climate change impacts on meteorological drought using SPI and SPEI: case study of Ankara, Turkey, Hydrological Sciences, 65(2): 254-268, https://doi.org/10.1080/02626667.2019.1691218. 
  • Afshar, M.H, Yilmaz, MT, Crow. W.T. (2019) Impact of rescaling methods in simple fusion of soil moisture products, Water Resources Research, 55 (9): 7804-7825, https://doi.org/10.1029/2019WR025111. 
  • Bulut, B., Yilmaz, MT., Afshar, M.H, Sorman, AU., Yucel, I., Cosh, M.H., Simsek, O. (2019) Evaluation of remotely-sensed and model-based soil moisture products according to different soil type, vegetation cover, and climate regime using station-based observations over Turkey, Remote Sensing, 11(16): 1875, https://doi.org/10.3390/rs11161875. 
  • Afshar, M.H, Yilmaz, MT. (2017) The added utility of nonlinear methods compared to linear methods in rescaling soil moisture products, Remote sensing of environment (196): 224-237, https://doi.org/10.1016/j.rse.2017.05.017.  
  • Afshar, M.H, Sorman, AU, Yilmaz, MT. (2016) Conditional copula-based spatial–temporal drought characteristics analysis, Water 8(10): 246, https://doi.org/10.3390/w8100426. 
  • Montaseri, M., Afshar, M.H, Bozorg-Haddad, O. (2015) Optimization of Stormwater Treatment Measure Using MUSIC-GA (Case Study: Canberra City, Australia), Water Resources Management, 29(13): 4649-4665, https://doi.org/s11269-015-1082-z. 
Selected Conference & Proceedings
  • Afshar, M.H., Hassani, A., Aminzadeh, M., Borrelli, P., Panagos, P., Robinson, D.A., Shokri, N. (2024) AI-driven insights into soil health and soil degradation in Europe in the face of climate and anthropogenic challenges, EGU General Assembly 2024, Vienna, Austria. https://doi.org/10.5194/egusphere-egu24-9512
  • Vogelbacher, A., Aminzadeh, M., Afshar, M. H., Shokri, N. (2024) Groundwater influence on the frequency of heatwaves: A global perspective, EGU General Assembly 2024, Vienna, Austria. https://doi.org/10.5194/egusphere-egu24-10493
  • Afshar, M.H., Foster, T., Higginbottom, T.P., Parkes, B., Hufkens, K., Mansabdar, S., Ceballos, F., Kramer, B. (2021). Overcoming basis risk in agricultural index insurance using crop simulation modeling and satellite crop phenology, EGU General Assembly 2021. Vienna, Austria. https://doi.org/10.5194/egusphere-egu21-9534
  • Afshar, M.H., Foster, T., Parkes, B., Hufkens, K., Ceballos, F., Kramer, B. (2020). Improving performance of index insurance using crop models and phenological monitoring, EGU General Assembly 2020. Vienna, Austria. https://doi.org/10.5194/egusphere-egu2020-10675
  • Onen, A., Afshar, M.H., Bulut, B. (2020). Short Term Hydrological Forecasting for a Cascade Dam System: A Case Study of Euphrates Basin in Turkey, EGU General Assembly 2020. Vienna. Austria. https://doi.org/10.5194/egusphere-egu2020-19883