Climate Change and Climate Variability

Oral Abstract

Uncertainty and Its Temporal Evolution of Climate Change Impacts on Hydrology for the Hanjiang River Watershed

Author(s)

• MS

  Mingxi Shen

  postgraduate
  State Key Laboratory of Water Resources & Hydropower Engineering Science, Wuhan University
• JC

  Jie Chen

  professor
  State Key Laboratory of Water Resources & Hydropower Engineering Science, Wuhan University

The uncertainty of climate change impacts on hydrology has been given lots of attention during the last decade. General Circulation Models (GCMs) are usually considered as the dominated uncertainty source, followed by downscaling methods. Most studies focused on quantifying the uncertainty of climate change impacts on hydrology for a specific period or a few (two or three) continuous periods, while the evolution of uncertainty in time has been given less attention, especially the contribution of different uncertainty sources. This study aims at comparing the contribution of GCMs and downscaling methods to the overall uncertainty of climate change impacts on hydrology, especially its evolution in time. The study was conducted at the Hanjiang River watershed, where serves as the water source for the middle route of the South-to-North Water Diversion Project in China. Twenty GCMs under two greenhouse gas emission scenarios over a period of 2021-2100 and different types of downscaling methods were used. The temporal evolution of uncertainty was expressed in terms of 51 future periods of 30 years. Hydrological simulations were carried out using a lumped, conceptual, rainfall-runoff model. Future climatic and hydrological regimes were compared to those in the reference period (1971-2000) using a set of metrics including mean and extreme. The results show that the major uncertainty consistently comes from the choice of a GCM, while downscaling techniques contributed significantly to some climatic and hydrological metrics. The uncertainties of climate change impacts on mean, high and low flow related to GCM all increase significantly and show a linear trend. However, the significant trend was not observed for the uncertainty of downscaling methods. Overall, this study further emphasizes the importance of using multi-GCMs and downscaling methods for studying the climate change impacts on hydrology. Additionally, the temporal evolution of uncertainty should be given great attention.