On the importance of discharge observation uncertainty when interpreting hydrological model performance

作者：Jerom Aerts, Jannis Hoch, Gemma Coxon, Nick van de Giesen, Rolf Hut · 发表于：Hydrology and earth system sciences · 年份：2024 · DOI：10.5194/hess-28-5011-2024 · 被引用次数：4 · 研究领域：Hydrology and Watershed Management Studies、Flood Risk Assessment and Management、Hydrological Forecasting Using AI

Abstract. For users of hydrological models, the suitability of models can depend on how well their simulated outputs align with observed discharge. This study emphasizes the crucial role of factoring in discharge observation uncertainty when assessing the performance of hydrological models. We introduce an ad hoc approach, implemented through the eWaterCycle platform, to evaluate the significance of differences in model performance while considering the uncertainty associated with discharge observations. The analysis of the results encompasses 299 catchments from the Catchment Attributes and MEteorology for Large-sample Studies Great Britain (CAMELS-GB) large-sample catchment dataset, addressing three practical use cases for model users. These use cases involve assessing the impact of additional calibration on model performance using discharge observations, conducting conventional model comparisons, and examining how the variations in discharge simulations resulting from model structural differences compare with the uncertainties inherent in discharge observations. Based on the 5th to 95th percentile range of observed flow, our results highlight the substantial influence of discharge observation uncertainty on interpreting model performance differences. Specifically, when comparing model performance before and after additional calibration, we find that, in 98 out of 299 instances, the simulation differences fall within the bounds of discharge observation uncertainty. This und...