Reduction of the uncertainties in the hydrological projections in Korean river basins using dynamically downscaled climate projections

Liying Qiu,Yeon-Woo Choi,Deg-Hyo Bae,Seon-Ho Kim,Jeong-Bae Kim,Eun-Soon Im

doi:10.1007/s00382-022-06201-8

Abstract

How the value of higher-resolution climate variables dynamically downscaled can affect the hydrological impact assessment has been a long standing issue. This study investigates the potential benefit of high-resolution climate data locally tailored over South Korea in terms of the reduction of uncertainties in hydrological projections. For this purpose, a large ensemble consisting of three Global Climate Model (GCM) projections and their dynamical downscaling products in different resolutions (i.e., 20 and 5 km), and four bias correction (BC) methods is fed into a semi-distributed hydrological model (HM) customized over Korean river basins. The in-depth comparison among the 45-members hydrological simulations proves the benefit in using high-resolution Regional Climate Model (RCM) for the runoff projections. While this study acknowledges the necessity of BC to remove the systematic bias in climate simulations, it is found that the high-resolution dynamical downscaling can significantly narrow the spread brought with different BC methods, thus reducing the uncertainty in the projected hydrological change. The projected runoff changes for both the mean of wet season and the high flows indicate that there will be an intensified runoff, especially for the extremes, over South Korea under the warming. Altogether, this study provides a valuable exploration of uncertainty reduction in hydrological projections from the perspective of resolution effect of dynamical downscaling, which is meaningful for hydroclimate studies and climate change impact assessment.

Highlights

One of the most critical impacts of climate change that needs deep understanding and profound planning is the change in the Earth’s hydrological cycle
We use the multi-model, multi-resolution climate simulation ensemble to feed hydrological model (HM) in combination with different bias correction (BC) methods to project the streamflow change in South Korea at the end of the 21st century
Three CMIP5 Global Climate Model (GCM) are downscaled into WRF20 and WRF05, and four BC

Summary

Introduction

One of the most critical impacts of climate change that needs deep understanding and profound planning is the change in the Earth’s hydrological cycle. Almost all of the physical processes included in the hydrological cycle, e.g., precipitation, evapotranspiration, infiltration, runoff, and routing, will be affected by the increasing temperature and relevant water vapor change, either directly or indirectly (Held and Soden 2006). Such changes in the water cycle should be carefully studied because they may impact the entire environment or even cause severe disasters. The reliable hydrological projections under global warming are urgently needed for the timely planning of water resource management and mitigation of the possible damages (Sun et al 2017)

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