Abstract
Abstract. Rainfall–runoff modelling has long been a special subject in hydrological sciences, but identifying behavioural parameters in ungauged catchments is still challenging. In this study, we comparatively evaluated the performance of the local calibration of a rainfall–runoff model against regional flow duration curves (FDCs), which is a seemingly alternative method of classical parameter regionalisation for ungauged catchments. We used a parsimonious rainfall–runoff model over 45 South Korean catchments under semi-humid climate. The calibration against regional FDCs was compared with the simple proximity-based parameter regionalisation. Results show that transferring behavioural parameters from gauged to ungauged catchments significantly outperformed the local calibration against regional FDCs due to the absence of flow timing information in the regional FDCs. The behavioural parameters gained from observed hydrographs were likely to contain intangible flow timing information affecting predictability in ungauged catchments. Additional constraining with the rising limb density appreciably improved the FDC calibrations, implying that flow signatures in temporal dimensions would supplement the FDCs. As an alternative approach in data-rich regions, we suggest calibrating a rainfall–runoff model against regionalised hydrographs to preserve flow timing information. We also suggest use of flow signatures that can supplement hydrographs for calibrating rainfall–runoff models in gauged and ungauged catchments.
Highlights
A standard method to predict daily streamflow is to employ a rainfall–runoff model that conceptualises catchment functional behaviours, and simulate synthetic hydrographs from atmospheric drivers (Wagener and Wheater, 2006; Blöschl et al, 2013)
The predictive performance was closely related to the input–output consistency (Fig. 3b), which was measured by the Pearson correlation coefficient between the current precipitation index (CPI) and the observed flows
We assumed that the hydrograph calibration under the Monte Carlo framework, which was assisted by the shuffled complex evolution (SCE) optimisation, was able to acceptably identify the behavioural parameters under given data quality
Summary
A standard method to predict daily streamflow is to employ a rainfall–runoff model that conceptualises catchment functional behaviours, and simulate synthetic hydrographs from atmospheric drivers (Wagener and Wheater, 2006; Blöschl et al, 2013). It is difficult to know whether the parameters optimised toward maximising hydrograph reproducibility are unique to represent actual catchment behaviours, since multiple parameter sets possibly show similar predictive performance (Beven, 2006, 1993). This low uniqueness of the optimal parameter set, namely the equifinality problem in conceptual hydrological modelling, can become a significant uncertainty source when extrapolating the optimal parameters to ungauged catchments (Oudin et al, 2008)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
