An Ensemble Climate-Hydrology Modeling System for Long-Term Streamflow Assessment in a Cold-Arid Watershed

Abstract

Climate change can bring about substantial alternatives of temperature and precipitation in the spatial and temporal patterns. These alternatives would impact the hydrological cycle and cause flood or drought events. This study has developed an ensemble climate-hydrology modeling system (ECHMS) for long-term streamflow assessment under changing climate. ECHMS consists of multiple climate scenarios (two global climate models (GCMs) and four representative concentration pathways (RCPs) emission scenarios), a stepwise-cluster downscaling method and semi-distributed land use-based runoff process (SLURP) model. ECHMS is able to reflect the uncertainties in climate scenarios, tackle the complex relationships (e.g., nonlinear/linear, discrete/continuous) between climate predictors and predictions without functional assumption, and capture the combination of snowmelt– and rainfall–runoff process with a simplicity of operation. Then, the developed ECHMS is applied to Kaidu watershed for analyzing the changes of streamflow during the 21st century. Results show that by 2099, the temperature increment in Kaidu watershed is mainly contributed by the warming in winter and spring. The precipitation will increase obviously in spring and autumn and decrease in winter. Multi-year average streamflow would range from 105.6 to 113.8 m3/s across all scenarios during the 21st century with an overall increasing trend. The maximum average increasing rate is 2.43 m3/s per decade in October and the minimum is 0.26 m3/s per decade in January. Streamflow change in spring is more sensitive to climate change due to its complex runoff generation process. The obtained results can effectively identify future streamflow changing trends and help manage water resources for decision makers.

Keywords

• climate change
• Kaidu watershed
• SLURP
• stepwise cluster
• streamflow