Open science for an interactive exploration of fluvial futures

Managing densely populated fluvial areas and adapting to climate-change present major challenges for sustainable development. To democratise the decision-making process it is desired that stakeholders and planning professionals can evaluate common interventions by straightforward access to intervention plans, source data, and model code. We aimed at the creation of an interactive environment based on free and open-source models and software packages for intervention planning and evaluation. This provides benefits as a) the model implementation and therefore scientific reasoning is visible and transparent b) the application of the entire workflow is not hampered by e.g. licensing issues of software tools used c) the approach can be applied to other areas as well. We build upon RiverScape, which is implemented in the spatio-temporal modelling environment PCRaster. RiverScape is a Python package to parameterise and evaluate common interventions in integrated river management, such as floodplain lowering, groyne lowering, main dike raising or roughness smoothing. Effects of selected measures can be evaluated with respect to changes in biodiversity, flood risk, stakeholder involvement and implementation costs. We developed a set of Jupyter Notebooks integrating explanatory text, user-defined parameterisation of measures, execution of RiverScape code, and interactive visualisation of spatial data. The Notebooks can be executed using any standard web-browser. The Riverscape model, Jupyter Notebooks, input and example data for the Waal River (Netherlands) are accessible from a public Github repository. The entire modelling environment can be easily installed using conda, a free Python package manager. Our Jupyter Notebooks provide an innovative interactive working and teaching environment that integrate modules from different disciplinary backgrounds, allowing to interactively create own measures, evaluate them in isolation, and interpret the results.