All Outputs (5)

Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales (2020)
Journal Article
Lange, S., Volkholz, J., Geiger, T., Zhao, F., Vega, I., Veldkamp, T., …Frieler, K. (2020). Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales. Earth's Future, 8(12), Article e2020EF001616. https://doi.org/10.1029/2020EF001616

©2020. The Authors. The extent and impact of climate-related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure... Read More about Projecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales.

How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change (2020)
Journal Article
Krysanova, V., Zaherpour, J., Didovets, I., Gosling, S. N., Gerten, D., Hanasaki, N., …Wada, Y. (2020). How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change. Climatic Change, 163, 1353–1377. https://doi.org/10.1007/s10584-020-02840-0

© 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)
Presentation / Conference Contribution
Zhang, J., Zhang, Z., Weng, Y., Gosling, S., Yang, H., Yang, C., …Ma, Q. (2020). Using Recurrent Neural Network for Intelligent Prediction of Water Level in Reservoirs. . https://doi.org/10.1109/COMPSAC48688.2020.0-108

© 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.

Global Heat Uptake by Inland Waters (2020)
Journal Article
Vanderkelen, I., Lipzig, N. P. M., Lawrence, D. M., Droppers, B., Golub, M., Gosling, S. N., …Thiery, W. (2020). Global Heat Uptake by Inland Waters. Geophysical Research Letters, 47(12), Article e2020GL087867. https://doi.org/10.1029/2020GL087867

©2020. The Authors. Heat uptake is a key variable for understanding the Earth system response to greenhouse gas forcing. Despite the importance of this heat budget, heat uptake by inland waters has so far not been quantified. Here we use a unique com... Read More about Global Heat Uptake by Inland Waters.

Historical and future changes in global flood magnitude - evidence from a model-observation investigation (2020)
Journal Article
Xuan Do, H., Zhao, F., Westra, S., Leonard, M., Gudmundsson, L., Eric Stanislas Boulange, J., …Wada, Y. (2020). Historical and future changes in global flood magnitude - evidence from a model-observation investigation. Hydrology and Earth System Sciences, 24(3), 1543-1564. https://doi.org/10.5194/hess-24-1543-2020

© 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.