A novel ensemble-based conceptual-data-driven approach

In our latest paper, we propose a novel framework for ensemble-based streamflow simulations. This framework develops a conceptual-data-driven approach (CDDA) that integrates a hydrological model (HM) with a data-driven model (DDM) into a hybrid modelling approach.

Continue reading “A novel ensemble-based conceptual-data-driven approach”

A novel method for downsizing the model parameter ensemble

Imagine you could use only three parameter sets of a hydrological model to represent the modelling uncertainty in the flood frequency analysis. Imagine how many more input scenarios could be then analysed at a lower computational cost. This study assists you in selecting such three parameter sets that could be assumed as representative for the full parameter ensemble.

Continue reading “A novel method for downsizing the model parameter ensemble”

The latest work is now in open discussion of NHESS

Representative ensemble for simulation of extreme floods

This work proposes methods for reducing the computational requirements of hydrological simulations for the estimation of very rare floods that occur on average less than once in 1000 years. These methods enable the analysis of long time streamflow series (here for example 10 000 years) at low computational costs with representing modelling uncertainty. They are to be used within continuous simulation frameworks with long input time series and are readily transferable to similar simulation tasks.

Continue reading “The latest work is now in open discussion of NHESS”