Zobrazeno 1 - 10
of 120
pro vyhledávání: '"Ricci, Sophie"'
Autor:
Nguyen, Thanh Huy, Piacentini, Andrea, Ricci, Sophie, Cassan, Ludovic, Munier, Simon, Bonassies, Quentin, Rodriguez-Suquet, Raquel
A chained hydrologic-hydraulic model is implemented using predicted runoff from a large-scale hydrologic model (namely ISBA-CTRIP) as inputs to local hydrodynamic models (TELEMAC-2D) to issue forecasts of water level and flood extent. The uncertainti
Externí odkaz:
http://arxiv.org/abs/2405.00567
Autor:
Nguyen, Thanh Huy, Ricci, Sophie, Piacentini, Andrea, Emery, Charlotte, Suquet, Raquel Rodriguez, Luque, Santiago Peña
Publikováno v:
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 3163-3167
In spite of astonishing advances and developments in remote sensing technologies, meeting the spatio-temporal requirements for flood hydrodynamic modeling remains a great challenge for Earth Observation. The assimilation of multi-source remote sensin
Externí odkaz:
http://arxiv.org/abs/2403.14394
Monte Carlo (MC) sampling is a popular method for estimating the statistics (e.g. expectation and variance) of a random variable. Its slow convergence has led to the emergence of advanced techniques to reduce the variance of the MC estimator for the
Externí odkaz:
http://arxiv.org/abs/2306.10800
Autor:
Nguyen, Thanh Huy, Ricci, Sophie, Piacentini, Andrea, Bonassies, Quentin, Suquet, Raquel Rodriguez, Luque, Santiago Peña, Marlis, Kevin, David, Cédric
Publikováno v:
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 1525-1528
The challenges in operational flood forecasting lie in producing reliable forecasts given constrained computational resources and within processing times that are compatible with near-real-time forecasting. Flood hydrodynamic models exploit observed
Externí odkaz:
http://arxiv.org/abs/2306.10059
Autor:
Nguyen, Thanh Huy, Ricci, Sophie, Piacentini, Andrea, Simon, Ehouarn, Suquet, Raquel Rodriguez, Luque, Santiago Peña
Publikováno v:
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 1595-1598
Owing to advances in data assimilation, notably Ensemble Kalman Filter (EnKF), flood simulation and forecast capabilities have greatly improved in recent years. The motivation of the research work is to reduce comprehensively the uncertainties in the
Externí odkaz:
http://arxiv.org/abs/2306.08466
Autor:
Nguyen, Thanh Huy, Ricci, Sophie, Piacentini, Andrea, Simon, Ehouarn, Suquet, Raquel Rodriguez, Luque, Santiago Peña
Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation (DA) strategies incorporating various types of observations; many are derived from spatial Earth Observation. This paper focuses on the assimi
Externí odkaz:
http://arxiv.org/abs/2304.01058
Autor:
Nguyen, Thanh Huy, Ricci, Sophie, Piacentini, Andrea, Suquet, Raquel Rodriguez, Blanchet, Gwendoline, Luque, Santiago Pena, Kettig, Peter
Publikováno v:
Proceedings of the 28th TELEMAC-MASCARET User Conference 2022
Ensemble data assimilation in flood forecasting depends strongly on the density, frequency and statistics of errors associated with the observation network. This work focuses on the assimilation of 2D flood extent data, expressed in terms of wet surf
Externí odkaz:
http://arxiv.org/abs/2211.07272
Autor:
Nguyen, Thanh Huy, Ricci, Sophie, Piacentini, Andrea, Fatras, Christophe, Kettig, Peter, Blanchet, Gwendoline, Luque, Santiago Pena, Baillarin, Simon
Publikováno v:
IOP Conf. Ser.: Earth Environ. Sci., 1136 (2023)
As the severity and occurrence of flood events tend to intensify with climate change, the need for flood forecasting capability increases. In this regard, the Flood Detection, Alert and rapid Mapping (FloodDAM) project, funded by Space for Climate Ob
Externí odkaz:
http://arxiv.org/abs/2205.08471
Autor:
Nguyen, Thanh Huy, Ricci, Sophie, Fatras, Christophe, Piacentini, Andrea, Delmotte, Anthéa, Lavergne, Emeric, Kettig, Peter
Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation. Such an approach combines in-situ gauge measurements with numerical hydrodynamic models to correct the hydraulic states and reduce the uncert
Externí odkaz:
http://arxiv.org/abs/2109.08487
Autor:
Nguyen, Thanh Huy, Delmotte, Anthéa, Fatras, Christophe, Kettig, Peter, Piacentini, Andrea, Ricci, Sophie
Publikováno v:
Proceedings of the 27th TELEMAC-MASCARET User Conference 2021
Relevant comprehension of flood hazards has emerged as a crucial necessity, especially as the severity and the occurrence of flood events intensify with climate changes. Flood simulation and forecast capability have been greatly improved thanks to ad
Externí odkaz:
http://arxiv.org/abs/2109.07470