Abstract A novel Bayesian Hierarchical Network Model (BHNM) for ensemble forecasts of
daily streamflow is presented that uses the spatial dependence induced by the river network …

The modeling of sub-daily extreme rainfall has long constituted a challenge for hydrologists
in view of the limited availability of data, both in time and space. In this context, the scale …

Flood frequency analysis at large scales, essential for the development of flood risk maps, is
hindered by the scarcity of gauge flow data. Suitable methods are thus required to predict …

Accurate flood risk assessment requires a comprehensive understanding of flood sensitivity
to regional drivers and climate factors. This paper presents the scaling of floods (duration …

Unprecedented rainfall events are defined as rainfall events that have extremely high
magnitude with low probability of occurrence. Although such events have occurred in the …

Maximum flows are often estimated from flood frequency analysis, by means of the statistical
fitting of a theoretical probability distribution to maximum annual flow data. However …

Quantifying and attributing the tendency of flood events to demonstrate clustering in time
and space is crucial for flood risk assessments. We analyse the temporal (TC) and spatial …

This study utilized a max-stable process (MSP) model with a dependence structure defined
via a non-Euclidean distance metric, with the goal of modelling extreme flood data on a river …

Abstract Intensity-duration-frequency (IDF) relationships are frequently required for hydraulic
design and risk assessment in small catchments. Nonetheless, the usual scarcity of subdaily …

This study presents how Extreme Value Analysis (EVA) can be used to predict future
extreme hydrological events and how dynamic-programming based change point detection …