In alpine areas in Northwest China, such as the Tianshan Mountains, the lack of climate data (because of scarce meteorological stations) makes it difficult to assess the impact of climate change on runoff. The main contribution of this study was to develop an integrated method to assess the impact of climate change on runoff in data-scarce high mountains. Based on reanalysis products, this study firstly downscaled climate data using machine learning algorithms, then developed a Batch Gradient Descent Linear Regression to calculate the contributions of temperature and precipitation to runoff. Applying this method to six mountainous basins originating from the Tianshan Mountains, we found that climate changes in high mountains are more significant than in lowlands. In high mountains, the runoff changes are mainly affected by temperature, whereas in lowlands, precipitation contributes more than temperature to runoff. The contributions of precipitation and temperature to runoff changes were 20% and 80%, respectively, in the Kumarik River. The insights gained in this study can guide other studies on climate and hydrology in high mountain basins. © 2022 by the authors.
