Simulation and Prediction of the Impact of Climate Change Scenarios on Runoff of Typical Watersheds in Changbai Mountains, China

Abstract

Simulating the hydrological process of a river basin helps to understand the evolution of water resources in the region and provides scientific guidance for water resources allocation policies between different river basins and water resources management within the river basin. This paper provides a scientific basis for the sustainable development of regional water resources and an accurate grasp of the future change trend of runoff by analyzing the hydrological process response of runoff in typical watersheds in Changbai Mountains, China, to climate change. The applicability of the HEC-HMS (The Hydrologic Engineering Center’s-Hydrologic Modeling System) hydrological model in the watershed is verified by calibrating and verifying the daily rainfall-runoff process in the watershed during the wet season from 2006 to 2017. The daily rainfall data of the two scenarios SSP2-4.5 and SSP5-8.5 under the BCC-CSM2-MR model in the 2021–2050 CMIP6 plan were downscaled and interpolated to in-basin stations to generate future daily precipitation series to predict runoff response to future climate change. The daily rainfall data of the two scenarios were downscaled and interpolated to the stations in the basin to generate future daily rainfall series to predict the runoff response under future climate changes. The average certainty coefficient of the HEC-HMS model for daily runoff simulation reached 0.705; the rainfall in the basin under the two climate scenarios of SSP2-4.5 and SSP5-8.5 in the next 30 years (2021–2050) will generally increase, and rainfall will be more evenly distributed in the future; the outlet flow of the basin will increase during the wet season (June–September) in the next 30 years, but it is lower than the historically measured value; the peak flow of the future will appear at most in August and September. The peak flow current time mostly appears in July and August. The time of peak occurrence has been delayed.