Historical and future changes in global flood magnitude - evidence from a model-observation investigation

Xuan Do, Hong; Zhao, Fang; Westra, Seth; Leonard, Michael; Gudmundsson, Lukas; Eric Stanislas Boulange, Julien; Chang, Jinfeng; Ciais, Philippe; Gerten, Dieter; Gosling, Simon N.; M�ller Schmied, Hannes; Stacke, Tobias; Telteu, Camelia Eliza; Wada, Yoshihide

doi:10.5194/hess-24-1543-2020

All Outputs (3)

How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change (2020)
Journal Article

© 2020, The Author(s). Importance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating o... Read More about How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change.

Using Recurrent Neural Network for Intelligent Prediction of Water Level in Reservoirs (2020)
Conference Proceeding

© 2020 IEEE. Water resources management over long term has faced a great challenge due to the increasing demands on water from a growing number of population and a huge variance of water usage in different time and place. Therefore, a new time series... Read More about Using Recurrent Neural Network for Intelligent Prediction of Water Level in Reservoirs.

Historical and future changes in global flood magnitude - evidence from a model-observation investigation (2020)
Journal Article

© Author(s) 2020. To improve the understanding of trends in extreme flows related to flood events at the global scale, historical and future changes of annual maxima of 7 d streamflow are investigated, using a comprehensive streamflow archive and six... Read More about Historical and future changes in global flood magnitude - evidence from a model-observation investigation.