Research scientist (chargé de recherche) at INRAE in Biostatistics and Spatial Processes (BioSP) team.
Domaine St. Paul, 228 route de l'Aérodrome, 84914 Avignon (France).
Researcher ID: https://orcid.org/0000-0002-8182-0152
I study the spatiotemporal statistics of weather at the local scale, their linkages with climate, and their impacts on eco-, hydro-, and agro-systems.
- Space-time geostatistics.
- Stochastic weather generators.
- Statistical meteorology.
- Environmental Sensor Networks (ESNs) for local scale and in-situ weather monitoring.
- Statistical enhancement (quality-check, filtering, interpolation, gap-filling) of ESN data.
- Characterization and simulation of rainfall space-time bevahior, with focus on orographic effects and intermittency.
- Hydro-meteorology and soil water resources.
This line of research aims at better understanding how topography and atmospheric circulation interact to generate the steep gradients of precipitation observed in high tropical islands. It encompasses three aspects:
- Rainfall observation at high resolution (<1km, 10 min) to assess sub-daily rain fluctuations.
- Rainfall mapping at daily resolution to characterize spatial rainfall patterns.
- Stochastic rainfall generation to explore the space-time variability of rainfall over Pacific islands, and to investigate the links between the vertical structure of the atmosphere and orographic rain enhancement.
This line of research aims at leveraging recent developments in the field of multivariate geostatistics and SPDE-based geostatistical modeling to design new stochastic weather generators able to:
- Simulate the joint fluctuations of a large number of climate variables (e.g. temperature, precipitation, solar radiation, wind).
- Simulate synthetic weather at daily resolution and on large grids (e.g. across all France at 8 km x 8 km resolution).
- Simulate weather scenarios in a changing climate, with application to stochastic downscaling of climate projections.
This line of research aims at combining field observations and (geo-)statistical data enhancement to improve the space-time description of the hydro-meteorological variables used to run hydrological models of fast respondig watersheds such as urban or mountain catchments. A special attention is paid to the intermittency of hydrometeorological variables, in particular precipitation and stream flow. Two aspects are investigated:
- Enhancing observations from local networks of weather stations (distance between stations 100 m - 10 km) using stochastic gap-filling and interpolation in order to produce high resolution 2D+time reconstructions of meteorological variables (e.g. precipitation, temperature, solar radiation, wind) used as input for hydrology modeling.
- Combining in-situ stream intermittence observations and regional scale hydro-climatic projections through ML regression in view of evaluating the evolution of stream intermittence in a changing climate.
- Peleg N, Torelló-Sentelles H, Mariethoz G, Benoit L, Leitão J, Marra F (PrePrint), Brief communication: the potential use of low-cost acoustic sensors in short-term urban flood warnings, Natural Hazards and Earth System Sciences Discussions, https://doi.org/10.5194/nhess-2022-257.
- Benoit L, Sichoix L, Nugent A, Lucas M, Giambelluca T (2022), Stochastic daily rainfall generation on tropical islands with complex topography, Hydrology and Earth System Sciences, 26, 2113–2129, https://doi.org/10.5194/hess-26-2113-2022.
- Nussbaumer R, Bauer S, Benoit L, Mariethoz G, Liechti F, Schmid B (2021), Quantifying year-round nocturnal bird migration with a fluid dynamics model, Journal of the Royal Society Interface, 18, 20210194, https://doi.org/10.1098/rsif.2021.0194.
- Michelon A, Benoit L, Beria H, Ceperley N, Schaefli B (2021), Benefits from high-density rain gauge observations for hydrological response analysis in a small alpine catchment, Hydrology and Earth System Sciences, 25, 2301-2325, https://doi.org/10.5194/hess-25-2301-2021.
- Benoit L (2021), Radar and rain gauge data fusion based on disaggregation of radar imagery, Water Resources Research, 27, e2020WR027899, https://doi.org/10.1029/2020WR027899.
- Benoit L, Lucas M, Tseng H, Huang Y-F, Tsang Y-P, Nugent A, Giambelluca T, Mariethoz G (2021), High space-time resolution observation of extreme orographic rain gradients in a Pacific Island catchment, Frontiers in Earth Science: Hydrosphere, 8, 546246, https://doi.org/10.3389/feart.2020.546246.
- Benoit L, Vrac M, Mariethoz G (2020), Nonstationary stochastic rain type generation: accounting for climate drivers, Hydrology and Earth System Sciences, 24, 2841-2854, https://doi.org/10.5194/hess-24-2841-2020.
- Nussbaumer R, Benoit L, Mariethoz G, Liechti F, Bauer S, Schmid B (2019), A geostatistical approach to estimate high resolution nocturnal bird migration densities from a weather radar network, Remote Sensing, 11, 2233, https://doi.org/10.3390/rs11192233.
- Benoit L, Gourdon A, Vallat R, Irarrazaval I, Gravey M, Lehmann B, Prasicek G, Graff D, Herman F, Mariethoz G (2019), A high-resolution image time series of the Gorner Glacier – Swiss Alps – derived from repeated UAV surveys, Earth System Science data, 11, 579-588, https://doi.org/10.5194/essd-11-579-2019.
- Benoit L, Vrac M, Mariethoz G (2018), Dealing with non-stationarity in sub-daily stochastic rainfall models, Hydrology and Earth System Sciences, 22, 5919–5933, https://doi.org/10.5194/hess-22-5919-2018.
- Benoit L, Allard D, Mariethoz G (2018), Stochastic Rainfall Modeling at Sub-kilometer Scale, Water Resources Research, 54, 4108-4130, https://doi.org/10.1029/2018WR022817.
- Benoit L, Mariethoz G (2017), Generating synthetic rainfall with geostatistical simulations, Wiley Interdisciplinary Reviews: Water, https://doi.org/10.1002/wat2.1199.
- Lombardi D, Benoit L, Camelbeeck T, Martin O, Meynard C, Thom C (2016), Bimodal pattern of seismicity detected at the ocean margin of an Antarctic ice shelf, Geophysical Journal International, 206, 1375–1381, https://doi.org/10.1093/gji/ggw214.
- Benoit L, Dehecq A, Pham H-T, Vernier F, Trouve E, Moreau L, Martin O, Thom C, Pierrot-Deseilligny M, Briole P (2015), Multi-method monitoring of Glacier d’Argentiere dynamics, Annals of Glaciology, 56, 118-128, https://doi.org/10.3189/2015AoG70A985.
- Benoit L, Briole P, Martin O, Thom C, Malet JP, Ulrich P (2015), Monitoring landslide displacements with the Geocube wireless network of low-cost GPS, Engineering Geology, 195, 111-121, https://doi.org/10.1016/j.enggeo.2015.05.020.
- Benoit L, Briole P, Martin 0, Thom C (2014), Real-time deformation monitoring by a wireless network of low-cost GPS, Journal of Applied Geodesy, 119–128, https://doi.org/10.1515/jag-2013-0023.
Most of the software related to the above papers is open-source and freely available in my GitHub repository: https://github.com/LionelBenoit
Since 2021: Research scientist at INRAE-BioSP (Avignon, France).
2015-2019: Research assistant at University of Lausanne - IDYST (Lausanne, Switzerland).
2011-2014: PhD student at the French mapping agency (IGN) - LASTIG (Saint-Mandé, France) and Ecole Normale Supérieure de Paris - Laboratoire de Géologie (Paris, France).
2008-2010: Engineering School student at Ecole Nationale des Sciences Géographiques (Champs-sur-Marne, France).