Towards FAIR hydrological modeling with HydroMT

Abstract

Hydrological models are crucial to understand water systems and perform impact assessment studies. However, these models require a lot of accurate data, especially if the model is spatially distributed. However, sufficiently accurate datasets while available, for example from earth-observations, need to be converted into model-specific, sometimes idiosyncratic, file formats. Therefore, hydrological models require various steps to process raw input data to model data which, if done manually, makes the process time consuming and hard to reproduce. Hence, there is a clear need for automated model instance setup for increased transparency and reproducibility in hydrological modeling. HydroMT (Hydro Model Tools) is an open-source Python package (https://github.com/Deltares/hydromt) that aims to make the process of building hydrological model instances and analyzing their results automated and reproducible. Compared to many other packages for automated model instance setup, HydroMT is data- and model-agnostic, meaning that data sources can easily be interchanged without additional coding and the generic model interface can be used for different model software. This makes it possible to reuse workflows to prepare input from different datasets or for different model software that require the same parameter (e.g. Manning roughness derived from land use maps) and thereby supporting controlled model intercomparison and sensitivity experiments.  In this contribution we show the application of HydroMT for flood hazard modeling using the distributed hydrological Wflow model and the reduced-physics hydrodynamic SFINCS model, both open-source models. We use HydroMT to setup a controlled and reproducible model experiment. We test the sensitivity of both models to various data sources used- and assumptions taken in the model instance building process and compare the skill to simulate peak discharge. Using this application, we discuss the merits and limitations of HydroMT and next steps toward FAIR hydrological modeling.