RoGeR v3.0.5 – a process-based hydrological toolbox model in Python

Abstract

Abstract. Although water availability and water quality are equally important for effective water resources management at various spatial and temporal scales, to date, a combined representation of soil water balance components and water quality components in Python is not available. The new RoGeR toolbox contains models that can be used for not only the quantification of hydrological processes, fluxes and stores, but also solute transport processes based on StorAge selection (SAS). This study presents the code structure and functionalities of RoGeR developed as a scientific model toolbox following defined open-source software guidelines. RoGeR uses five different computational backends covering just-in-time compilation, parallelism and graphical processing units (GPUs) that might be used for optimizing computational performance. We show that graphical processing unit computing has the greatest potential to improve computation time and energy usage, especially for large modelling experiments. A simple modelling experiment highlights the capabilities of the new RoGeR model toolbox. We simulated the soil water balance, stable water isotope (18O) transport, and corresponding travel time distributions of the Eberbaechle catchment, Germany, for a 3-year period. Due to the current limitations of a variety of process components, further development of RoGeR as a scientific software is needed. Future modifications are easily possible due to the open software architecture of RoGeR.