Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating Model‐Agnostic and Model‐Specific Configuration Steps in Applications of Large‐Domain Hydrologic Models

Abstract

Despite the proliferation of computer‐based research on hydrology and water resources, such research is typically poorly reproducible. Published studies have low reproducibility due to incomplete availability of data and computer code, and a lack of documentation of workflow processes. This leads to a lack of transparency and efficiency because existing code can neither be quality controlled nor reused. Given the commonalities between existing process‐based hydrologic models in terms of their required input data and preprocessing steps, open sharing of code can lead to large efficiency gains for the modeling community. Here, we present a model configuration workflow that provides full reproducibility of the resulting model instantiations in a way that separates the model‐agnostic preprocessing of specific data sets from the model‐specific requirements that models impose on their input files. We use this workflow to create large‐domain (global and continental) and local configurations of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model connected to the mizuRoute routing model. These examples show how a relatively complex model setup over a large domain can be organized in a reproducible and structured way that has the potential to accelerate advances in hydrologic modeling for the community as a whole. We provide a tentative blueprint of how community modeling initiatives can be built on top of workflows such as this. We term our workflow the “Community Workflows to Advance Reproducibility in Hydrologic Modeling” (CWARHM; pronounced “swarm”).

Predicting Hydrological Change in an Alpine Glacierized Basin and Its Sensitivity to Landscape Evolution and Meteorological Forcings

“…While obtaining a similar level of knowledge and conceptual understanding at a larger scale is challenging due to both computational demands and data limitations, advances in large‐scale hydrological models provide the opportunity to include process representation over large domains. For example, the SUMMA modeling framework allows the testing of different process‐representation (Clark et al., 2015) and has been applied from local to continental scales (Knoben et al., 2022). For cold regions, such as the interior mountain of western Canada, the recent development of the MESH model showcases the importance, and the possibilities, of including snow, frozen ground and glacier process representations even over large basins (Wheater et al., 2022).…”

The Impact of Meteorological Forcing Uncertainty on Hydrological Modeling: A Global Analysis of Cryosphere Basins

“…The workflow coupling SUMMA and mizuRoute is introduced in Knoben, Clark, et al (2022). The codes and model configurations such as the structure of SUMMA (e.g., modelDecisions.txt) are open access at https:// zenodo.org/record/6968609 (Knoben, Marsh, & Tang, 2022).…”

“…The preparation of DEM, land cover, and soil class data (including downloading, processing, remapping from regular grids to basin GRUs, etc.) are detailed in Knoben, Clark, et al (2022). Gridded data are remapped to basin GRUs using area-weighted averaging.…”