Modelling techniques valid for ordinary hydrological conditions are often inadequate for catastrophic runoff conditions, as the majority of the parameters included in the modelling schemes are not necessarily applicable to flood conditions. To overcome this problem, using a stochastic self-training procedure (SSTP) is proposed. The procedure is based on the real water balance equation and the s...

Abstract. Despite showing great success of applications in many commercial fields, machine learning and data science models generally show limited scientific including hydrology (Karpatne et al., 2017). The approach is often criticized for its lack interpretability physical consistency. This has led to the emergence new modelling paradigms, such as theory-guided (TGDS) physics-informed learning...

The Hydrological Recursive Model (HRM), a conceptual rainfall-runoff model, was applied for local and regional simulation of hourly discharges in the transnational Alzette River basin (Luxembourg-France-Belgium). The model was calibrated for a range of various sub-basins with a view to analysing its ability to reproduce the variability of basin responses during flood generation. The regionaliza...

The study presents investigations of the runoff from snow and ice, carried out in the high alpine basin of the Rhône river at Sion (3371 km2, 491 -4634 m a.s.l.). Using satellite remote sensing data, features like the snow coverage in the whole basin, the gradually decreasing snow coverage on glaciers and the area of exposed ice have been mapped. The periodical monitoring of the basin is based ...

The paper outlines recent and ongoing research addressing the quantification of river flood frequencies at ungauged sites across Britain. The approach is one of modelling continuous time series of catchment runoff. Model parameters are established where data permit: the spatial generalisation to ungauged sites is effected by relating model parameters to widely available catchment properties whi...

Global freshwater resources are sensitive to changes in climate, land cover and population density and distribution. The Land-surface Processes and eXchanges Dynamic Global Vegetation Model is a recent development of the Lund-Potsdam-Jena model with improved representation of fire-vegetation interactions. It allows simultaneous consideration of the effects of changes in climate, CO2 concentrati...

In the 1980s, there were numerous claims, based on estimates of the correlation dimension, that the variability of various geophysical processes, in particular rainfall, is generated by a low-dimensional deterministic chaos. Due to a recent attempt (Sivakumar et ai, 2001) to revive the same approach and with claims of an analogous result for the rainfall-runoff process, we think it is necessary...

This paper reviews non-probabilistic approaches of modelling uncertainty, particularly in flood forecasting and introduces a fuzzy set theory-based method for treating precipitation uncertainty in rainfall-runoff modelling, which allows the temporal and/or spatial disaggregation of precipitation. The results of the fuzzy set theory-based method are compared with the probabilistic approach using...