Abstract
Abstract Introduction Conceptual hydrological models are useful tools to support catchment water management. However, the identifiability of parameters and structural uncertainties in conceptual rainfall-runoff modeling prove to be a difficult task. Here, we aim to evaluate the performance of a conceptual semi-distributed rainfall-runoff model, HBV-light, with emphasis on parameter identifiability, uncertainty, and model structural validity. Results The results of a regional sensitivity analysis (RSA) show that most of the model parameters are highly sensitive when runoff signatures or combinations of different objective functions are used. Results based on the generalized likelihood uncertainty estimation (GLUE) method further show that most of the model parameters are well constrained, showing higher parameter identifiability and lower model uncertainty when runoff signatures or combined objective functions are used. Finally, the dynamic identifiability analysis (DYNIA) shows different types of parameter behavior and reveals that model parameters have a higher identifiability in periods where they play a crucial role in representing the predicted runoff. Conclusions The HBV-light model is generally able to simulate the runoff in the Pailugou catchment with an acceptable accuracy. Model parameter sensitivity is largely dependent upon the objective function used for the model evaluation in the sensitivity analysis. More frequent runoff observations would substantially increase the knowledge on the rainfall-runoff transformation in the catchment and, specifically, improve the distinction of fast surface-near runoff and interflow components in their contribution to the total catchment runoff. Our results highlight the importance of identifying the periods when intensive monitoring is critical for deriving parameter values of reduced uncertainty.
Highlights
Conceptual hydrological models are useful tools to support catchment water management
Among the objective functions based on runoff signatures, Time to peak (SPT) has the highest
Several main conclusions can be drawn from this study: 1. The results of regional sensitivity analysis (RSA) show that model parameter sensitivity is largely dependent upon the objective function used for the model evaluation in the sensitivity analysis
Summary
Conceptual hydrological models are useful tools to support catchment water management. We aim to evaluate the performance of a conceptual semi-distributed rainfall-runoff model, HBV-light, with emphasis on parameter identifiability, uncertainty, and model structural validity. Hydrological signatures are defined as hydrologic response characteristics that provide insight into the hydrologic functional behavior of catchments (Sawicz et al, 2011). Such response characteristics are often indicative of a specific watershed and how its response differs from others; examples include common descriptors of the hydrograph shape such as the runoff duration curve and the time to peak flow (Shamir et al, 2005). Different objective functions judge the goodness of a certain parameter set by different aspects and, a model’s success at simulating runoff may be better quantified by using several evaluation measures (Dawson et al, 2007) and the so-called Pareto optimality, which describes solutions in which an objective function cannot be improved without decreasing other objective functions
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