Many papers have advised on careful consideration of the approaches and methods we choose for our hydrological modelling studies as they potentially affect our modelling results and conclusions. However, there is no common and consistently updated guidance on what good modelling practice is and how it has evolved in recent years. While many useful practices such as model benchmarking, controlled model comparisons, developing scripted workflows, carefully selecting calibration periods and methods, or testing the impact of subjective modelling decisions along the modelling chain exist, none of these can be considered common practice yet.
This session therefore intends to provide a platform for a visible and ongoing discussion on what ought to be the current standard(s) for an appropriate modelling protocol that considers uncertainty in all its facets and promotes transparency in the quest for robust and reliable results. We aim to bring together, highlight and foster work that develops, applies, or evaluates procedures for a trustworthy modelling workflow or that investigates good modelling practices for particular aspects of the modelling chain. We invite research that aims to improve the scientific basis of modelling and puts good modelling practice in focus again. This might include (but is not limited to) contributions addressing the following key questions:
1. The theoretical side of model application, centered around the question: “is my model any good?” (e.g., benchmarking, robust calibration/evaluation and controlled model comparison);
2. The practical side of model application, centered around the question: “how do I ensure my modeling work is efficient, reproducible and transparent?” (e.g., novel modelling protocols or workflows, examples of adopting the FAIR principles);
3. The social side of model application, centered around the question: “how do I communicate my model’s strengths and weaknesses?” (e.g., investigation of subjective choices along the modeling chain and communication of model outputs and uncertainties);
4. The future of model application, centered around our main question: “where are we today, and where do we want to be tomorrow?” (i.e., overviews of the current state of modeling, and visions for the future).
Vazken Andréassian