Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective

Kue Bum Kim, Hyun-Han Kwon, Dawei Han

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Abstract

The typical framework of the climate change impact assessment on water resources relies on plausible scenarios obtained from global climate models (GCMs) and hydrological models (HMs). Although regional climate models (RCMs) can better simulate local climate at a high-resolution grid, the direct use of model outputs from RCMs is not recommended as inputs for HMs due to systematic error. Existing studies have focused on the bias correction (BC) of climate model outputs without considering uncertainties/biases in hydrological modeling. In this regard, this study proposed an integrated framework that combines the BC of RCM precipitation and the simulated flow from the rainfall-runoff model, considering the underlying uncertainty in the parameters of the distribution function. The regional climate model, HadRM3, and the conceptual rainfall-runoff model, HYMOD, are employed. Observed daily precipitation, evapotranspiration, and discharge time series over the Thorverton catchment are compiled from the UK Meteorological Office. To examine the effectiveness of the combined strategy, four different BC approaches have been explored to reduce systematic biases in the flow simulated through the HMs using the RCM precipitation as input. Here, BCs of RCM and HM outputs have been applied under the condition that the bias-corrected ensembles should be within the range of the observed climate variability. The four BC models are considered: aathe RCM precipitation and flow are corrected by preserving their natural variabilities (Case-4). From a hydrological perspective, the Case-4 model showed the best performance among the four cases in terms of correcting the bias and the spread of the flow ensemble.
Original languageEnglish
Article number127261
JournalJournal of Hydrology
Volume604
Early online date9 Dec 2021
DOIs
Publication statusPublished - 1 Jan 2022

Bibliographical note

Funding Information:
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI 2018-07010. This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No. 2019R1A2C2087944).

Publisher Copyright:
© 2021 The Authors

Research Groups and Themes

  • Water and Environmental Engineering

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