Abstract
Water use efficiency (WUE) is a central parameter for linking carbon and water exchange processes in terrestrial ecosystems. The Beijing-Tianjin Sand Source Region (BTSSR) in China has undergone tremendous vegetation restoration and climate change. Understanding the WUE responses to climate change and human activity and their relative contributions to the trends and inter-annual variations (IAVs) in WUE is necessary to improve water use efficiency and strengthen water resource management. The evapotranspiration (ET) dataset based on the model tree ensemble (MTE) algorithm which was a machine learning approach using flux-tower ET measurements and the GLASS GPP dataset, as well as the variance decomposition method, were used to analyze the spatiotemporal changes in water use efficiency and inherent water use efficiency (IWUE) and the impacts of climate change and human activities. The results showed that the annual WUE and IWUE exhibited significantly increase in most regions of the BTSSR. The trend of human activity played the most important role in the increases of WUE and IWUE, with relative contributions of 88.2% and 85.9%, respectively, followed by the IAV of human activity for WUE (6.1%) and the trend of climate change (8.7%) for IWUE. The contribution of IAV to climate change was relatively small. Moreover, WUE and IWUE were all positively correlated with precipitation and temperature in most regions. Our results indicated that ecological restoration projects had significantly improved water use efficiency in BTSSR and may decrease the water burden in the BTSSR.
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