Urban surface water flood modelling–a comprehensive review of current models and future challenges
Urbanisation is an irreversible trend as a result of social and economic development. Urban
areas, with high concentration of population, key infrastructure, and businesses, are …
areas, with high concentration of population, key infrastructure, and businesses, are …
Ensemble flood forecasting: Current status and future opportunities
Ensemble flood forecasting has gained significant momentum over the past decade due to
the growth of ensemble numerical weather and climate prediction, expansion in high …
the growth of ensemble numerical weather and climate prediction, expansion in high …
An extended SEIR model with vaccination for forecasting the COVID-19 pandemic in Saudi Arabia using an ensemble Kalman filter
In this paper, an extended SEIR model with a vaccination compartment is proposed to
simulate the novel coronavirus disease (COVID-19) spread in Saudi Arabia. The model …
simulate the novel coronavirus disease (COVID-19) spread in Saudi Arabia. The model …
Evaluation and machine learning improvement of global hydrological model-based flood simulations
T Yang, F Sun, P Gentine, W Liu, H Wang… - Environmental …, 2019 - iopscience.iop.org
A warmer climate is expected to accelerate global hydrological cycle, causing more intense
precipitation and floods. Despite recent progress in global flood risk assessment, the …
precipitation and floods. Despite recent progress in global flood risk assessment, the …
Flood modeling and prediction using earth observation data
The ability to map floods from satellites has been known for over 40 years. Early images of
floods were rather difficult to obtain, and flood map** from satellites was thus rather …
floods were rather difficult to obtain, and flood map** from satellites was thus rather …
Accounting for uncertainties in compound flood hazard assessment: The value of data assimilation
Compound flood hazard assessment (CFHA) and modeling are prone to various sources of
uncertainty including model structure, model parameters, input/forcing data, and those …
uncertainty including model structure, model parameters, input/forcing data, and those …
[HTML][HTML] A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions
Q Zhou, S Teng, Z Situ, X Liao, J Feng… - Hydrology and Earth …, 2023 - hess.copernicus.org
An accurate and rapid urban flood prediction model is essential to support decision-making
for flood management. This study developed a deep-learning-technique-based data-driven …
for flood management. This study developed a deep-learning-technique-based data-driven …
[HTML][HTML] Evaluation of data assimilation strategies on improving the performance of crop modeling based on a novel evapotranspiration assimilation framework
Recently, data assimilation (DA) has garnered significant attention. Integration of DA
approaches and crop models could diminish model uncertainties and improve the precision …
approaches and crop models could diminish model uncertainties and improve the precision …
Improvement of flood extent representation with remote sensing data and data assimilation
Flood simulation and forecast capability have been greatly improved, thanks to the
advances in data assimilation (DA). Such an approach combines in situ gauge …
advances in data assimilation (DA). Such an approach combines in situ gauge …
Dual State‐Parameter Assimilation of SAR‐Derived Wet Surface Ratio for Improving Fluvial Flood Reanalysis
TH Nguyen, S Ricci, A Piacentini… - Water Resources …, 2022 - Wiley Online Library
Flooding is one of the most devastating natural hazards to which our society worldwide must
adapt, especially as its severity and occurrence tend to increase with climate changes. This …
adapt, especially as its severity and occurrence tend to increase with climate changes. This …