Adrian Holt
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View article: Revolutionizing Flood Forecasting with a Generalized Deep Learning Model
Revolutionizing Flood Forecasting with a Generalized Deep Learning Model Open
The domain of spatial flood prediction is dominated by hydrodynamic models, which, while robust and adaptable, are often constrained by computational requirements and slow processing times. To address these limitations, the integration of …
View article: Generation of harmonised pluvial flood hazard maps through decentralised analytics
Generation of harmonised pluvial flood hazard maps through decentralised analytics Open
Increasing extreme weather events pose significant challenges in hydrology, requiring tools for preparedness and prediction of intense rainfall impacts, especially flash floods. Current risk reduction measures for pluvial flood risk manage…
View article: Will it run?—A proof of concept for smoke testing decentralized data analytics experiments
Will it run?—A proof of concept for smoke testing decentralized data analytics experiments Open
The growing interest in data-driven medicine, in conjunction with the formation of initiatives such as the European Health Data Space (EHDS) has demonstrated the need for methodologies that are capable of facilitating privacy-preserving da…
View article: Synthetic rainfall data generator development through decentralised model training
Synthetic rainfall data generator development through decentralised model training Open
Recent heavy rainfall-induced flood events, for example in Germany, Australia and USA, have highlighted the relevance of countermeasures in saving human lives and preventing property damage. Newly introduced ML-based flood forecasting meth…