Understanding the limitations of Gassmann's fluid substitution model using explainable ML
This work follows several ideas presented in Feigl, M., Roesky, B., Herrnegger, M., Schulz, K., & Hayashi, M. (2022). Learning from mistakes—Assessing the performance and uncertainty in process-based models. Hydrological Processes, 36( 2), e14515. https://doi.org/10.1002/hyp.14515