Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment

Parameters describing slow flow remained essentially constant over the range of subhourly to daily scales considered here, while parameters describing quick flow converged toward increasingly precise and stable estimates as the data resolution approached the characteristic time scale of these faster processes. These results are consistent with theoretical expectations based on numerical error analysis and data-averaging considerations.

Additional diagnostics confirmed the improved ability of the more complex models to reproduce distinct signatures in the observed data. More broadly, this study provides insights into the information content of hydrological data and, by advocating careful attention to robust numericostatistical analysis and stringent process-oriented diagnostics, furthers the utilization of dense-resolution data and experimental insights to advance hypothesis-based hydrological modeling at the catchment scale.