edu.ucar.opensky::articles:17156 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-26T13:35:23.247593 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7s46t70 Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment 2011-05-11T00:00:00Z publication https://n2t.org/ark:/85065/d7s46t70 https://doi.org/10.1029/2010WR009525 Kavetski, D. author Fenicia, F. author Clark, Martyn P. author UCAR/NCAR - Library publisher This study presents quantitative and qualitative insights into the time scale dependencies of hydrological parameters, predictions and their uncertainties, and examines the impact of the time resolution of the calibration data on the identifiable system complexity. Data from an experimental basin (Weierbach, Luxembourg) is used to analyze four conceptual models of varying complexity, over time scales of 30 min to 3 days, using several combinations of numerical implementations and inference equations. Large spurious time scale trends arise in the parameter estimates when unreliable time-stepping approximations are employed and/or when the heteroscedasticity of the model residual errors is ignored. Conversely, the use of robust numerics and more adequate (albeit still clearly imperfect) likelihood functions markedly stabilizes and, in many cases, reduces the time scale dependencies and improves the identifiability of increasingly complex model structures. 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. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication An edited version of this paper was published by AGU. Copyright 2010 American Geophysical Union. None eng geoscientificInformation