Visualizing flood forecasting uncertainty: some current European EPS platforms-COST731 working group 3

TL;DR: This chapter provides an entry point to recent developments in geological modeling methods, helps researchers in the field to better consider uncertainties, and supports the integration of geological observations and knowledge in geophysical interpretation, modeling and inverse approaches.

TL;DR: There is a need to not only improve technical aspects of flood forecasting, but also to bridge the gap between scientific research and hydrometeorological model development, and real‐world flood management using probabilistic ensemble forecasts, especially through effective communication.

TL;DR: One of the key features of the Delft-FEWS operational forecasting platform is its flexibility in integrating (third-party) models and data, and the available approaches to linking models and accessing data are highlighted.

TL;DR: In this paper, the authors present a variety of research opportunities, including the development of automated quality-control algorithms for the myriad of data used in operational streamflow forecasts, data assimilation, and ensemble forecasting techniques that allow for forecaster input, methods for using humangenerated weather forecasts quantitatively, and quantification of human interference in the hydrologic cycle.

TL;DR: In this paper, the experiences of conceptual runoff modelling at the Swedish Meteorological and Hydrological Institute are surnmarized in the present work and the basic philosophy and the methodology when developing...

TL;DR: The LISFLOOD model as discussed by the authors is an example of a physically based model written using the PCRaster GIS environment, it simulates river discharge in a drainage basin as a function of spatial data on topography, soils and land cover.

TL;DR: The PREVAH components introduced here support a modelling task from pre-processing the data over the actual model calibration and validation to visualising and interpreting the results (post-processing).

TL;DR: In this article, the mesoscale Alpine Programme Demonstration of Probabilistic Hydrological and Atmospheric Simulation of Flood Events (MAP D-PHASE) is a forecast demonstration project aiming at demonstrating recent improvements in the operational use of end-to-end forecasting system consisting of atmospheric models, hydrological prediction systems, nowcasting tools and warnings for end-users.