环境科学
蒸散量
地表径流
气候变化
植被(病理学)
水流
降水
绿化
水循环
分水岭
水资源
水文学(农业)
生态水文学
水平衡
气候学
生态系统
地理
流域
生态学
气象学
地质学
医学
地图学
岩土工程
病理
机器学习
计算机科学
生物
作者
Zhihong Song,Jun Xia,Gangsheng Wang,Dunxian She,Chen Hu,Shilong Piao
标识
DOI:10.1016/j.jhydrol.2023.129519
摘要
China leads the world in vegetation greening and accounts for one-fourth of the global net increase in leaf area over the past two decades. However, it remains elusive on the relative importance of vegetation greening and climate change on China's hydrological cycle due to the lack of observational-based constraints on notorious model uncertainties. Here, we developed a process-based distributed hydrological model that couples a nonlinear runoff generation mechanism with a remotely-sensed evapotranspiration (ET) module. This model could well capture the spatiotemporal patterns of the main hydrological components (runoff, ET, and soil moisture) at grid scale and streamflow at watershed scale during 1982–2012 over the mainland China. We show that the changes in climatic factors (precipitation and potential ET) dominated hydrologic change at the national scale, with climate induced runoff decrease by 7.6 mm year−1 compared to 0.6 mm year−1 caused by vegetation change. Vegetation effect was primarily notable in water-limited regions as a higher correlation between vegetation contribution to runoff change and absolute leaf area index (LAI) trend in water-limited regions (r = 0.52, p < 0.01) than energy-limited regions (r = 0.19, p < 0.01). Our results highlight the significance of region-dependent differential measures for sustainable water resources management and climate change adaptation under a changing climate.
科研通智能强力驱动
Strongly Powered by AbleSci AI