# Climate, CO2, and Anthropogenic Drivers of Accelerated Vegetation Greening in the Haihe River Basin
###### Abstract
In addition, aforestation data have been adopted in several studies to emphasize the great contribution of ecological restoration projects to vegetation greening in China's wooded lands [20; 21; 22]. However, these studies only used forestry investment or afforestation areas to conduct statistical analyses and did not estimate the vegetation change in the future. As a result, in this study, we used the NTL dataset and afforestation areas to capture inconspicuous human activities and vegetation management programs, respectively. The contribution analysis of vegetation dynamics that divide the entire impact into climate change and human activities has been a major concern for hydrologists and ecologists [7; 23; 24]. Some studies have taken human activities as a residue part after deducting climate impacts from the whole impacts [25]. [PERSON] et al. [11] used a multiple correlation regression method to determine the response of NDVI to climatic factors, and discrepancies between the observed and predicted NDVI values were considered as residuals. If the residuals were significant, fluctuations in the NDVI values were caused by anthropogenic activities, rather than climate. [PERSON] et al. [26] utilized multiple linear regression to evaluate the impact of climate factors on the variations in NDVI changes in the Three Gorges Reservoir Region of China; in this method, the remaining fraction (one minus \(R^{2}\)) was treated as human-induced NDVI variations. However, these methods consider human activities and their effects indirectly, and some uncertainty errors are incorrectly included in the contribution of the human part, which could lead to an overestimation in this part. Recently, it was recognized that socioeconomic/fundamental natural environmental indicators should be introduced in attribution analysis frameworks [18; 21; 23]. [PERSON] et al. [18] built a structural equation model (SEM) to detect the connection between the NDVI fluctuations and natural and anthropogenic factors in Jiangsu Province, China. The individual and combined effects of the elements on the target were quantified using SEM. However, the variables in the study were calculated by subtracting two years' data, which may not be representative of the long-term situation. Meanwhile, the prediction of the target variable through SEM with latent variables was difficult, and the authors did not consider the influence of CO\({}_{2}\) on the variations in NDVI. Therefore, prediction and attribution analysis will be more complicated when comprehensively integrating climate change, human activities, and CO\({}_{2}\). The Haihe River Basin (HRB), covering Beijing-Tianjin-Hebei (Jing-Jin-Ji) provinces, is a major economic center in China. However, water resources in most sub-basins are attenuated [27; 28; 29]. Water shortage, in particular, has hindered the social and economic development of this region. To address this issue, the South-to-North Water Diversion (SNWD) Project was developed to satisfy human water demand by transferring water from the Yangtze River to the HRB. Simultaneously, the accompanying ecological restoration projects, such as the Beijing-Tianjin Sand Source Control Program [30], has exacerbated the water resource conflict between nature and humans [31]. The purpose of vegetation restoration is to mitigate soil erosion and combat climate change by increasing carbon storage through afforestation. Nevertheless, it has reduced surface runoff [32], and will affect the planning and implementation of the East Route of the SNWD. Therefore, distinguishing vegetation restoration caused by natural climate, elevated CO\({}_{2}\) concentration, anthropogenic ecological restoration, and social and economic development is vital. More importantly, this can help determine the intensity of ecological restoration projects, along with the extent of water diversion projects, particularly in developed areas that have a large population.