Probabilistic Inverse Modeling: An Application in Hydrology. (arXiv:2210.06213v1 [cs.LG])

The astounding success of these methods has made it imperative to obtain more
explainable and trustworthy estimates from these models. In hydrology, basin
characteristics can be noisy or missing, impacting streamflow prediction. For
solving inverse problems in such applications, ensuring explainability is
pivotal for tackling issues relating to data bias and large search space. We
propose a probabilistic inverse model framework that can reconstruct robust
hydrology basin characteristics from dynamic input weather driver and
streamflow response data. We address two …

application arxiv hydrology modeling