This study aims to regionalize a rainfall-runoff model within the mountainous Geum River catchment, Korea. A version of the Probability Distributed Moisture model is applied to 19 gauged sub-catchments. A Monte Carlo based method is used for the calibration and validation of the model using three objective functions targeting overall performance, as well as low and high flow regimes specifically. A set of multivariate regression models linking model parameters and catchment characteristics is developed. The regionalised and locally calibrated models are compared using the leave-one-out cross-validation method. The validation results show that the regionalised model has equal or better performance than the locally calibrated model at 12 (for high flow model), 10 (for low flow model) and 10 catchments (for overall flow regime model) respectively. This study shows the potential of the regionalisation of the Probability Distributed Moisture model within the Geum River region. The results show that the suggested regionalized models for high and low flow regimes are better than a single model for the overall flow regime model. It is expected that this approach can usefully support water resource management in comparable ungauged mountainous, monsoon-affected catchments.
- Korean catchments
- rainfall runoff model
- ungauged catchment
ASJC Scopus subject areas
- Civil and Structural Engineering
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- Department of Architecture & Civil Engineering - Senior Lecturer
- Research Unit for Water, Environment and Infrastructure Resilience (WEIR)
- Water Innovation and Research Centre (WIRC)
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Institute for Mathematical Innovation (IMI)
- Centre for Infrastructure, Geotechnical and Water Engineering Research (IGWE)
Person: Research & Teaching