地表径流
环境科学
水文学(农业)
气候变化
降水
干旱
水资源
径流曲线数
植被(病理学)
潜在蒸发
干旱指数
归一化差异植被指数
水循环
分水岭
蒸散量
驱动因素
自然地理学
中国
地理
生态学
气象学
地质学
病理
机器学习
生物
考古
医学
岩土工程
计算机科学
作者
Yafan Zuo,Jianhong Chen,Sha Lin,Kangning He
标识
DOI:10.1016/j.scitotenv.2022.160835
摘要
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.
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