Pierre‐André Garambois

2.3k total citations
63 papers, 1.2k citations indexed

About

Pierre‐André Garambois is a scholar working on Global and Planetary Change, Water Science and Technology and Ecology. According to data from OpenAlex, Pierre‐André Garambois has authored 63 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Global and Planetary Change, 46 papers in Water Science and Technology and 22 papers in Ecology. Recurrent topics in Pierre‐André Garambois's work include Flood Risk Assessment and Management (52 papers), Hydrology and Watershed Management Studies (46 papers) and Hydrology and Sediment Transport Processes (22 papers). Pierre‐André Garambois is often cited by papers focused on Flood Risk Assessment and Management (52 papers), Hydrology and Watershed Management Studies (46 papers) and Hydrology and Sediment Transport Processes (22 papers). Pierre‐André Garambois collaborates with scholars based in France, Brazil and United States. Pierre‐André Garambois's co-authors include Jérôme Monnier, Hélène Roux, Kévin Larnier, Denis Dartus, David Labat, Adrien Paris, Stéphane Calmant, Michael Durand, Rodrigo Cauduro Dias de Paiva and Daniel Medeiros Moreira and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Resources Research and Geophysical Research Letters.

In The Last Decade

Pierre‐André Garambois

58 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pierre‐André Garambois France 22 910 852 381 186 177 63 1.2k
Silvia Barbetta Italy 20 898 1.0× 899 1.1× 438 1.1× 366 2.0× 202 1.1× 61 1.3k
Jérôme Monnier France 18 524 0.6× 461 0.5× 281 0.7× 75 0.4× 200 1.1× 53 809
Paolo Mignosa Italy 24 753 0.8× 430 0.5× 180 0.5× 154 0.8× 503 2.8× 59 1.8k
Ali Ercan United States 17 345 0.4× 292 0.3× 132 0.3× 198 1.1× 137 0.8× 68 771
Xilin Xia United Kingdom 18 1.0k 1.1× 655 0.8× 117 0.3× 402 2.2× 588 3.3× 41 1.5k
Yves Secretan Canada 16 184 0.2× 247 0.3× 280 0.7× 101 0.5× 158 0.9× 48 790
Xia Zhao China 14 447 0.5× 186 0.2× 98 0.3× 235 1.3× 222 1.3× 28 963
Ryota TSUBAKI Japan 14 378 0.4× 219 0.3× 416 1.1× 123 0.7× 75 0.4× 65 712
P. Brufau Spain 16 384 0.4× 220 0.3× 207 0.5× 68 0.4× 412 2.3× 40 1.2k
Seung Oh Lee South Korea 14 352 0.4× 278 0.3× 338 0.9× 122 0.7× 101 0.6× 79 891

Countries citing papers authored by Pierre‐André Garambois

Since Specialization
Citations

This map shows the geographic impact of Pierre‐André Garambois'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 Pierre‐André Garambois with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre‐André Garambois more than expected).

Fields of papers citing papers by Pierre‐André Garambois

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pierre‐André Garambois. 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 Pierre‐André Garambois. The network helps show where Pierre‐André Garambois may publish in the future.

Co-authorship network of co-authors of Pierre‐André Garambois

This figure shows the co-authorship network connecting the top 25 collaborators of Pierre‐André Garambois. A scholar is included among the top collaborators of Pierre‐André Garambois 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 Pierre‐André Garambois. Pierre‐André Garambois 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.
2.
Moreira, Daniel Medeiros, Fabrice Papa, Alice César Fassoni‐Andrade, et al.. (2025). Widespread and Exceptional Reduction in River Water Levels Across the Amazon Basin During the 2023 Extreme Drought Revealed by Satellite Altimetry and SWOT. Geophysical Research Letters. 52(11). 1 indexed citations
3.
Garambois, Pierre‐André, et al.. (2025). A distributed hybrid physics–AI framework for learning corrections of internal hydrological fluxes and enhancing high-resolution regionalized flood modeling. Hydrology and earth system sciences. 29(15). 3589–3613. 1 indexed citations
4.
5.
Larnier, Kévin, Pierre‐André Garambois, Jérôme Monnier, et al.. (2024). Improving river networks hydrological-hydraulic models with SWOT and multi-satellite data. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
6.
Bouclier, Robin, et al.. (2024). Reduction of the shallow water system by an error aware POD-neural network method: Application to floodplain dynamics. Computer Methods in Applied Mechanics and Engineering. 428. 117094–117094. 4 indexed citations
7.
Garambois, Pierre‐André, et al.. (2024). Adjoint-based sensitivity analysis and assimilation of multi-source data for the inference of spatio-temporal parameters in a 2D urban flood hydraulic model. Journal of Hydrology. 643. 131885–131885. 3 indexed citations
8.
9.
Brigode, Pierre, et al.. (2022). How can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models?. Hydrology and earth system sciences. 26(22). 5793–5816. 34 indexed citations
10.
Fleischmann, Ayan Santos, Rodrigo Cauduro Dias de Paiva, Walter Collischonn, et al.. (2020). Trade‐Offs Between 1‐D and 2‐D Regional River Hydrodynamic Models. Water Resources Research. 56(8). 25 indexed citations
11.
Garambois, Pierre‐André, Stéphane Calmant, Pascal Finaud‐Guyot, et al.. (2019). Wavelet‐Based River Segmentation Using Hydraulic Control‐Preserving Water Surface Elevation Profile Properties. Geophysical Research Letters. 46(12). 6534–6543. 14 indexed citations
12.
Larnier, Kévin, Jérôme Monnier, & Pierre‐André Garambois. (2019). Discharge and bathymetry estimations of rivers from SWOT like data. EGU General Assembly Conference Abstracts. 7439. 1 indexed citations
13.
Durand, Michael, et al.. (2018). A first estimate of the expected distribution of SWOT river discharge accuracy. AGUFM. 2018. 1 indexed citations
14.
Roux, Hélène, et al.. (2018). Using a multi-hypothesis framework to improve the understanding of flow dynamics during flash floods. Hydrology and earth system sciences. 22(10). 5317–5340. 15 indexed citations
15.
Garambois, Pierre‐André, et al.. (2017). Physical basis for river segmentation from water surface observables. AGUFM. 2017. 2 indexed citations
16.
Paris, Adrien, Rodrigo Cauduro Dias de Paiva, Joécila Santos da Silva, et al.. (2016). Stage‐discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin. Water Resources Research. 52(5). 3787–3814. 119 indexed citations
17.
Gleason, Colin J., Michael Durand, & Pierre‐André Garambois. (2016). Forward to the Future: Estimating River Discharge with McFLI. AGU Fall Meeting Abstracts. 2016. 1 indexed citations
18.
Durand, Michael, Colin J. Gleason, David M. Bjerklie, et al.. (2016). Including stage-dependent roughness coefficient in algorithms to estimate river discharge from remotely sensed water elevation, width, and slope. AGU Fall Meeting Abstracts. 2016. 1 indexed citations
19.
Durand, Michael, Laurence Smith, Colin J. Gleason, et al.. (2014). Assessing SWOT discharge algorithms performance across a range of river types. AGUFM. 2014. 1 indexed citations
20.
Pavelsky, Tamlin M., K. Andreadis, Jerad Bales, et al.. (2012). RECENT PROGRESS IN DEVELOPMENT OF SWOT RIVER DISCHARGE ALGORITHMS. ESASP. 710. 112. 3 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Silvia Barbetta Breakdown of academic impact, for papers by Jérôme Monnier Breakdown of academic impact, for papers by Paolo Mignosa Breakdown of academic impact, for papers by Ali Ercan Breakdown of academic impact, for papers by Xilin Xia Breakdown of academic impact, for papers by Yves Secretan Breakdown of academic impact, for papers by Xia Zhao Breakdown of academic impact, for papers by Ryota TSUBAKI Breakdown of academic impact, for papers by P. Brufau Breakdown of academic impact, for papers by Seung Oh Lee
Rankless by CCL
2026