Martin Parisot | hydrogeology | Editorial Board Member

Published on by Environmental Scientists

Dr. Martin Parisot | hydrogeology | Editorial Board Member

Inria Center at Bordeaux University | France

Dr. Martin Parisot is a dedicated junior researcher at INRIA whose work integrates advanced mathematical modeling with computational techniques to address complex challenges in geophysical and environmental fluid dynamics. His research bridges kinetic theory, hydrodynamic limits, hyperbolic systems, and dispersive phenomena to develop unified models capable of describing multi-scale water-related processes with exceptional precision. He contributes significantly to the formulation and analysis of shallow-water, congested-flow, and wave-propagation models, emphasizing entropy principles, asymptotic preservation, and structure-preserving numerical schemes. His expertise includes innovative coupling strategies, weakly dispersive approximations, and adaptive numerical methods that enhance the reliability of simulations for free-surface flows, groundwater interactions, and large-scale oceanic dynamics. Parisot’s scientific output has earned substantial recognition, reflected in 434 citations, an h-index of 11, and an i10-index of 13, highlighting the broad impact of his contributions. His publications cover diverse themes such as hydrodynamic model derivation, interface coupling techniques, dispersive approximations of Euler equations, kinetic equations for swarm behavior, and numerical schemes applicable to low-Froude regimes. He has collaborated widely on interdisciplinary projects involving coastal risk assessment, storm surge modeling, renewable marine energy, sediment transport, and unified modeling of geophysical flows, offering analytical depth and computational advances that support environmental forecasting and engineering innovation. In addition to his research activities, he has guided emerging scholars and contributed to editorial and scientific committee roles, as well as the organization of conferences in applied mathematics. Through sustained contributions to modeling and numerical analysis, Parisot continues to advance the understanding and prediction of complex geophysical systems, reinforcing his role in the progression of environmental and computational fluid dynamics research.

Featured Publications

Fernandez-Nieto, E. D., Parisot, M., Penel, Y., & Sainte-Marie, J. (2018). A hierarchy of dispersive layer-averaged approximations of Euler equations for free surface flows. Communications in Mathematical Sciences, 16(5), 1169–1202.

Godlewski, E., Parisot, M., Sainte-Marie, J., & Wahl, F. (2018). Congested shallow water model: Roof modeling in free surface flow. ESAIM: Mathematical Modelling and Numerical Analysis, 52(5), 1679–1707.

Parisot, M., & Vila, J.-P. (2016). Centered-potential regularization for the advection upstream splitting method. SIAM Journal on Numerical Analysis, 54(5), 3083–3104.

Parisot, M. (2019). Entropy-satisfying scheme for a hierarchy of dispersive reduced models of free surface flow. International Journal for Numerical Methods in Fluids, 91(10), 509–531.

Lachowicz, M., Leszczyński, H., & Parisot, M. (2017). Blow-up and global existence for a kinetic equation of swarm formation. Mathematical Models and Methods in Applied Sciences, 27(06), 1153–1175.

 

Fatemeh Avazpour | Hydrology | Best Researcher Award

Published on by Environmental Scientists

Dr. Fatemeh Avazpour | Hydrology | Best Researcher Award

Yazd University | Iran

Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management.

Profiles: Scopus 

Featured Publications

Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica.

Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal.

Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science.

Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research.

Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.