Sylvain Massuel

Dr. Sylvain Massuel


Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 March 2009 in Water Resources Research
Verified
Journal Article
Closed access
PDF file
GFG. Favreau
G. Favreau
BCB. Cappelaere
B. Cappelaere
SMSylvain Massuel
Sylvain Massuel
MLM. Leblanc
M. Leblanc
MBM. Boucher
M. Boucher
CLChristian Leduc
Christian Leduc

1 April 2008 in Global and Planetary Change
Verified
Journal Article
Closed access
MLMarc J. Leblanc
Marc J. Leblanc
GFGuillaume Favreau
Guillaume Favreau
SMSylvain Massuel
Sylvain Massuel
STSarah O. Tweed
Sarah O. Tweed
MLMaud Loireau
Maud Loireau
BCBernard Cappelaere
Bernard Cappelaere

20 August 2018 in Hydrology and Earth System Sciences
Verified
Journal Article
Open access
PDF file
Andrew OgilvieAndrew Ogilvie
Andrew Ogilvie
GBGilles Belaud
Gilles Belaud
SMSylvain Massuel
Sylvain Massuel
MMMark Mulligan
Mark Mulligan
PGPatrick Le Goulven
Patrick Le Goulven
RCRoger Calvez
Roger Calvez
Hydrometric monitoring of small water bodies (1–10 ha) remains rare, due to their limited size and large numbers, preventing accurate assessments of their agricultural potential or their cumulative influence in watershed hydrology. Landsat imagery has shown its potential to support mapping of small water bodies, but the influence of their limited surface areas, vegetation growth, and rapid flood dynamics on long-term surface water monitoring remains unquantified. A semi-automated method is developed here to assess and optimize the potential of multi-sensor Landsat time series to monitor surface water extent and mean water availability in these small water bodies. Extensive hydrometric field data (1999–2014) for seven small reservoirs within the Merguellil catchment in central Tunisia and SPOT imagery are used to calibrate the method and explore its limits. The Modified Normalised Difference Water Index (MNDWI) is shown out of six commonly used water detection indices to provide high overall accuracy and threshold stability during high and low floods, leading to a mean surface area error below 15 %. Applied to 546 Landsat 5, 7, and 8 images over 1999–2014, the method reproduces surface water extent variations across small lakes with high skill (R2 = 0.9) and a mean root mean square error (RMSE) of 9300 m2. Comparison with published global water datasets reveals a mean RMSE of 21 800 m2 (+134 %) on the same lakes and highlights the value of a tailored MNDWI approach to improve hydrological monitoring in small lakes and reduce omission errors of flooded vegetation. The rise in relative errors due to the larger proportion and influence of mixed pixels restricts surface water monitoring below 3 ha with Landsat (Normalised RMSE = 27 %). Interferences from clouds and scan line corrector failure on ETM+ after 2003 also decrease the number of operational images by 51 %, reducing performance on lakes with rapid flood declines. Combining Landsat observations with 10 m pansharpened Sentinel-2 imagery further reduces RMSE to 5200 m2, displaying the increased opportunities for surface water monitoring in small water bodies after 2015.

1 August 2012 in Journal of Hydrology
Verified
Journal Article
Closed access
JPJ. Perrin
J. Perrin
FSFerrant Sylvain
Ferrant Sylvain
SMSylvain Massuel
Sylvain Massuel
BDB. Dewandel
B. Dewandel
Jean Christophe MaréchalJean Christophe Maréchal
Jean Christophe Maréchal
SAS. Ahmed
S. Ahmed

21 October 2004 in Hydrological Processes
Verified
Journal Article
Closed access
PDF file
LSL. Séguis
L. Séguis
BCB. Cappelaere
B. Cappelaere
GMG. Milési
G. Milési
CPChristophe Peugeot
Christophe Peugeot
SMSylvain Massuel
Sylvain Massuel
GFG. Favreau
G. Favreau

1 March 2011 in Agricultural Water Management
Verified
Journal Article
Closed access
BGBiju George
Biju George
Hector MalanoHector Malano
Hector Malano
BDBrian Davidson
Brian Davidson
PHPetra Hellegers
Petra Hellegers
LBLuna Bharati
Luna Bharati
SMSylvain Massuel
Sylvain Massuel