Stochastic hydrology offers efficient tools for characterizing processes in hydroclimatic systems, e.g., for hydrologic design, hydroclimatic systems modeling and forecasting, and water resources management. Theory and application of stochastic processes enables a faithful and consistent representation of natural processes that in many cases outperforms outcomes of physically based models. Stochastic modelling offers the means to mimic the variability of processes in space and time, and to characterize the inherent uncertainty in probabilistic terms. For example, this allows to simulate synthetic space-time fields reproducing the characteristics of the process – the main statistical properties across multiple spatial and temporal scales – for assessing the hydrological impact in a complex and changing environment.
This session calls for papers developing and discussing stochastics tools to systematically deal with uncertainty, constant or sudden change, and space-time variability, for characterization or simulation (including disaggregation) purposes of hydroclimatic variables such as precipitation, temperature, streamflow, or soil properties. Contributions are invited, for instance, on the improvement of stochastic modeling in hydrology, innovative techniques for identifying model structure, calibrating parameters, assessing uncertainties, etc. (see also the Unsolved Problems in Hydrology UPHs 1-4 and 5-8 identified by Blöschl et al., 2019, which are related to time-variability and change and space-variability and scaling, respectively).