The runoff changes are controlled by combined effects of multiple regional environmental factors in the alpine hilly region of Northwest China

The imbalance between the water supply and demand in arid and semiarid regions is becoming increasingly serious due to global warming and human activities. It is of great significance to reveal the variation characteristics of runoff and its main controlling factors for the sustainable management of regional water resources. However, few previous studies have considered the integrated effects of multiple control factors on runoff variation at different periodic scales. We collected meteorological and hydrological data from 1960 to 2019 in the Huangshui watershed and explored the correlation degree between runoff and regional environment factors such as precipitation (P), potential evaporation (ET0), mean temperature (T), normalized difference vegetation index (NDVI). The wavelet coherence indicates that there was a high degree of positive phase consistency between runoff changes and P, ET0, T and NDVI at an approximately 12-month period scale, with lag times of approximately 1, 2, 1 and 0 months, respectively. The P was the single factor most closely related to runoff, and its combined with ET0 dominated the runoff change during the whole study period. The Budyko frame combined with elastic coefficient analysis showed that the climate change were the main reasons for the increase in annual runoff in change period I (1981-1990), and changes in the underlying surface due to human activities and vegetation variation was the main reason for the decrease in runoff in change period II (1991-2019). The wetter climate brought more rainfall input but this did not make runoff appear an obvious upward trend. Therefore, for alpine regions with sensitive and fragile ecological environment, the balance between human water consumption, vegetation ecological water demand, and precipitation should be weighed. The combination of wavelet coherence analysis and Budyko framework is helpful to better determine the potential driving factors of regional runoff change.