Matthieu Le Lay

738 total citations
24 papers, 464 citations indexed

About

Matthieu Le Lay is a scholar working on Water Science and Technology, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Matthieu Le Lay has authored 24 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Water Science and Technology, 20 papers in Global and Planetary Change and 7 papers in Atmospheric Science. Recurrent topics in Matthieu Le Lay's work include Hydrology and Watershed Management Studies (23 papers), Flood Risk Assessment and Management (17 papers) and Hydrology and Drought Analysis (15 papers). Matthieu Le Lay is often cited by papers focused on Hydrology and Watershed Management Studies (23 papers), Flood Risk Assessment and Management (17 papers) and Hydrology and Drought Analysis (15 papers). Matthieu Le Lay collaborates with scholars based in France, Switzerland and Indonesia. Matthieu Le Lay's co-authors include G.‐M. Saulnier, Sylvie Galle, Thibault Mathevet, F. Garavaglia, Joël Gailhard, Isabelle Braud, Charles Perrin, Rémy Garçon, Dominique Thiéry and P Nicolle and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Resources Research and Geophysical Research Letters.

In The Last Decade

Matthieu Le Lay

22 papers receiving 438 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matthieu Le Lay France 11 399 362 109 105 30 24 464
Daniela Biondi Italy 11 281 0.7× 256 0.7× 153 1.4× 102 1.0× 27 0.9× 24 369
Marcus Buechel United Kingdom 7 251 0.6× 302 0.8× 144 1.3× 78 0.7× 29 1.0× 12 396
Lionel Berthet France 8 522 1.3× 454 1.3× 213 2.0× 116 1.1× 29 1.0× 16 578
Tanja Euser Netherlands 4 409 1.0× 328 0.9× 196 1.8× 76 0.7× 24 0.8× 7 465
Sebastian Gnann United Kingdom 13 314 0.8× 235 0.6× 124 1.1× 68 0.6× 25 0.8× 16 390
Tara Razavi Canada 7 432 1.1× 409 1.1× 212 1.9× 104 1.0× 22 0.7× 7 524
Thomas Nester Austria 7 361 0.9× 448 1.2× 60 0.6× 139 1.3× 24 0.8× 10 534
Paolo Reggiani Germany 8 211 0.5× 251 0.7× 60 0.6× 127 1.2× 35 1.2× 17 350
Cong Jiang China 12 214 0.5× 277 0.8× 78 0.7× 70 0.7× 24 0.8× 26 367
Eric Sprokkereef Netherlands 7 239 0.6× 246 0.7× 95 0.9× 94 0.9× 25 0.8× 14 310

Countries citing papers authored by Matthieu Le Lay

Since Specialization
Citations

This map shows the geographic impact of Matthieu Le Lay's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthieu Le Lay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthieu Le Lay more than expected).

Fields of papers citing papers by Matthieu Le Lay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthieu Le Lay. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthieu Le Lay. The network helps show where Matthieu Le Lay may publish in the future.

Co-authorship network of co-authors of Matthieu Le Lay

This figure shows the co-authorship network connecting the top 25 collaborators of Matthieu Le Lay. A scholar is included among the top collaborators of Matthieu Le Lay based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthieu Le Lay. Matthieu Le Lay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Thirel, Guillaume, Lila Collet, François Rousset, et al.. (2025). Future streamflow along the French part of the Meuse River – a closer look at uncertainties. SPIRE - Sciences Po Institutional REpository. 111(1).
2.
Évin, Guillaume, et al.. (2024). Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings. Hydrology and earth system sciences. 28(1). 261–281. 7 indexed citations
3.
Metref, Sammy, Emmanuel Cosme, Matthieu Le Lay, & Joël Gailhard. (2023). Snow data assimilation for seasonal streamflow supply prediction in mountainous basins. Hydrology and earth system sciences. 27(12). 2283–2299. 4 indexed citations
4.
5.
Berthet, Lionel, et al.. (2019). Cohérence des prévisions et place de l'expertise : les nouveaux défis pour la prévision des crues. La Houille Blanche. 105(1). 5–12. 5 indexed citations
6.
Garavaglia, F., et al.. (2018). Tailor-made spatial patterns for hydrological model parameters combining regionalisation methods. Biogeosciences (European Geosciences Union). 1 indexed citations
7.
Garavaglia, F., Matthieu Le Lay, Rémy Garçon, et al.. (2017). Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach. Hydrology and earth system sciences. 21(8). 3937–3952. 50 indexed citations
8.
Lay, Matthieu Le, et al.. (2017). Impact of mesoscale spatial variability of climatic inputs and parameters on the hydrological response. Journal of Hydrology. 553. 13–25. 15 indexed citations
9.
Lay, Matthieu Le, Rémy Garçon, Joël Gailhard, & F. Garavaglia. (2015). ASSESSMENT OF THE WATER BALANCE OVER FRANCE USING REGIONALIZED TURC-PIKE FORMULA FOR OPERATIONAL HYDROLOGY. AGU Fall Meeting Abstracts. 2015. 1 indexed citations
10.
Garavaglia, F., et al.. (2014). Definition and sensitivity of the conceptual MORDOR rainfall-runoff model parameters using different multi-criteria calibration strategies. AGU Fall Meeting Abstracts. 2014. 1 indexed citations
11.
Nicolle, P, Raji Pushpalatha, Charles Perrin, et al.. (2014). Benchmarking hydrological models for low-flow simulation and forecasting on French catchments. Hydrology and earth system sciences. 18(8). 2829–2857. 98 indexed citations
12.
Nicolle, P, Raji Pushpalatha, Charles Perrin, et al.. (2013). Benchmarking hydrological models for low-flow simulation and forecasting on French catchments. 5 indexed citations
13.
Mathevet, Thibault, et al.. (2012). Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts. EGU General Assembly Conference Abstracts. 2808. 3 indexed citations
14.
Bonnifait, Laurent, Guy Delrieu, Matthieu Le Lay, et al.. (2009). Distributed hydrologic and hydraulic modelling with radar rainfall input: Reconstruction of the 8–9 September 2002 catastrophic flood event in the Gard region, France. Advances in Water Resources. 32(7). 1077–1089. 55 indexed citations
15.
Lay, Matthieu Le, et al.. (2008). Model representation of the Sudanian hydrological processes: Application on the Donga catchment (Benin). Journal of Hydrology. 363(1-4). 32–41. 21 indexed citations
16.
17.
Lay, Matthieu Le, Sylvie Galle, G.‐M. Saulnier, & Isabelle Braud. (2007). Exploring the relationship between hydroclimatic stationarity and rainfall‐runoff model parameter stability: A case study in West Africa. Water Resources Research. 43(7). 21 indexed citations
18.
Braud, Isabelle, et al.. (2006). Multi-criteria assessment of the Representative Elementary Watershed approach on the Donga catchment (Benin) using a downward approach of model complexity. Hydrology and earth system sciences. 10(3). 427–442. 26 indexed citations
19.
Lay, Matthieu Le & Sylvie Galle. (2005). How changing rainfall regimes may affect the water balance : a modelling approach in West Africa. IAHS-AISH publication. 203–210. 10 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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