State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China; Institute of Water Sciences, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China.
Joint Innovation Center for Modern Forestry Studies, College of Forestry, Nanjing Forestry University, Nanjing 210037, China.
Sci Total Environ. 2024 Nov 25;953:176174. doi: 10.1016/j.scitotenv.2024.176174. Epub 2024 Sep 12.
While large-scale vegetation greening in China has substantially influenced global vegetation dynamics, the specific impact of this restoration on water use efficiency (WUE) remained inadequately understood. This study employed both the Geodetector and structural equation modeling (SEM) methods, utilizing the Lund-Potsdam-Jena (LPJ) Global Dynamic Vegetation Model, to explore the contributions of various driving factors to China's potential vegetation WUE from 1982 to 2019. The results indicated: (1) there existed considerable further potential for vegetation recovery nationwide. Among them, the Loess Plateau, Inner Mongolia Plateau, and northern Xinjiang had relatively high potential for vegetation recovery. This potential was further amplified by the significant prospects for enhancing WUE in these areas; (2) The application of the Geodetector method revealed that the normalized difference vegetation index (NDVI) explained over 40 % of the variation in potential vegetation WUE in China, exerting a greater influence than climatic factors. In arid/semi-arid regions, precipitation (PRE), NDVI, and vapor pressure deficit (VPD) significantly influenced WUE. Temperature (TEM) was the dominant factor affecting WUE in humid and humid/semi-humid regions; (3) Utilizing the SEM analysis method, it was evident that NDVI exerted the most substantial direct positive influence on potential vegetation WUE in China, whereas VPD and PRE had notable negative impacts. In arid/semi-arid regions, PRE emerged as the primary determinant of WUE. Conversely, in regions where water resources were not limiting, TEM and VPD exerted a more pronounced influence on potential vegetation WUE. This indicated that while vegetation restoration generally enhanced potential vegetation WUE, other factors such as PRE, TEM, and VPD played critical roles in different climatic zones, shaping the regional variations in WUE.
在中国，大规模的植被绿化极大地影响了全球植被动态，但这种恢复对水利用效率（WUE）的具体影响仍未得到充分理解。本研究采用地理探测器和结构方程模型（SEM）方法，利用 Lund-Potsdam-Jena（LPJ）全球动态植被模型，探讨了各种驱动因素对 1982 年至 2019 年中国潜在植被 WUE 的贡献。结果表明：（1）全国范围内仍有相当大的植被恢复潜力。其中，黄土高原、内蒙古高原和北疆地区具有较高的植被恢复潜力，这些地区的 WUE 也有很大的提高潜力；（2）地理探测器方法的应用表明，归一化差异植被指数（NDVI）解释了中国潜在植被 WUE 变化的 40%以上，比气候因素的影响更大。在干旱/半干旱地区，降水（PRE）、NDVI 和水汽压亏缺（VPD）显著影响 WUE。在湿润和湿润/半湿润地区，温度（TEM）是影响 WUE 的主要因素；（3）利用 SEM 分析方法，发现 NDVI 对中国潜在植被 WUE 有最直接的正向影响，而 VPD 和 PRE 有显著的负向影响。在干旱/半干旱地区，PRE 是 WUE 的主要决定因素。相反，在水资源不短缺的地区，TEM 和 VPD 对潜在植被 WUE 的影响更为明显。这表明，尽管植被恢复普遍提高了潜在植被 WUE，但 PRE、TEM 和 VPD 等其他因素在不同气候区起着关键作用，塑造了 WUE 的区域变化。
