|
|
|
|
|
Paul Muñoz, Johanna Orellana-Alvear, Jörg Bendix, Jan Feyen and Rolando Célleri
Worldwide, machine learning (ML) is increasingly being used for developing flood early warning systems (FEWSs). However, previous studies have not focused on establishing a methodology for determining the most efficient ML technique. We assessed FEWSs wi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lorenzo Alfieri, Francesco Dottori, Richard Betts, Peter Salamon and Luc Feyen
Knowledge on the costs of natural disasters under climate change is key information for planning adaptation and mitigation strategies of future climate policies. Impact models for large scale flood risk assessment have made leaps forward in the past few ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Paul Muñoz, Rolando Célleri, Jan Feyen
Pág. 1 - 13
A laser-optical disdrometer served as reference to assess the absolute percent bias of calculated rainfall intensity using the data of different-resolution tipping-bucket rain gauges classically applied by climatologists and hydrologists in the Andean re...
ver más
|
|
|
|
|
|
|
|
|
|
|
Christine Szpilka, Kendra Dresback, Randall Kolar, Jesse Feyen and Jindong Wang
This research details the development and validation of an updated constituent tidal database for the Western North Atlantic, Caribbean and Gulf of Mexico (WNAT) region, referred to as the EC2015 database. Regional databases, such as EC2015, provide much...
ver más
|
|
|
|
|
|
|
|
|
|
|
R. F. Vázquez, J. Feyen, J. Berlamont
Pág. 315 - 328
|
|
|
|
|
|