Predicting Ili River streamflow change and identifying the major drivers with a novel hybrid model

Abstract

Study region: Ili River, the main river in the Lake Balkhash basin. Study focus: This study introduces a novel hybrid model by coupling the Soil and Water Assessment Tool (SWAT) hydrological model with machine learning algorithms. It aims to simulate and forecast the streamflow of the Ili River, clearly delineating the roles of meteorological factors and anthropogenic factors in the process of streamflow change. New hydrological insights for the region: During the period 1960–2020, the contribution of climate change to streamflow variation was 104.59%-113.07%, the contribution of land use ranged from −10.75% to −4.59%, and the impact of reservoir construction was −2.27%. The predictive outcomes of the hybrid model indicate that, under the SSP2–4.5 and SSP5–8.5 scenarios, the streamflow of the Ili River is projected to increase by 12.8% and 14.3% respectively in the future period (2021–2100), in comparison to the historical period (1960–2020). The warming and humidification from 2021 to 2100 will lead to changes in the streamflow components of the Ili River, with a decrease in the proportion of groundwater flow and an increase in the proportion of surface flow. The results of this study provide a reference for the rational utilization and scientific management of water resources in the Ili River Basin.

Keywords

• Hydro-climate change
• Streamflow prediction
• SWAT
• Machine learning
• Ili River