Publications

Yu, X; Yang, HB; Li, SE; Yang, DW (2019). An Improved Conceptual Model Quantifying the Effect of Climate Change and Anthropogenic Activities on Vegetation Change in Arid Regions. REMOTE SENSING, 11(18), 2110.

Abstract
Vegetation shows a greening trend on the global scale in the past decades, which has an important effect on the hydrological cycle, and thus quantitative interpretation of the causes for vegetation change is of great benefit to understanding changes in ecology, climate, and hydrology. Although the Donohue13 model, a simple conceptual model based on gas exchange theory, provides an effective tool to interpret the greening trend, it cannot be used to evaluate the impact from land use and land cover change (LULCC) on the regional scale, whose importance to vegetation change has been demonstrated in a large number of studies. Hence, we have improved the Donohue13 model by taking into account the change in vegetation cover ratio due to LULCC, and applied this model to the Yarkand Oasis in the arid region of northwest China. The estimated change trend in leaf area index (LAI) is 1.20%/year from 2001 to 2017, which accounts for approximately half of the observed (2.31%/year) by the moderate resolution imaging spectroradiometer (MODIS). Regarding the causes for vegetation greening, the contributions of: (1) LULCC; (2) atmospheric CO2 concentration; and (3) vapor pressure deficit were: (1) 88.3%; (2) 40.0%; and (3) -28.3%, respectively, which reveals that the largest contribution was from LULCC, which is probably driven by increased total water availability in whole oasis with a constant transpiration in vegetation area. The improved Donohue13 model, a simple but physics-based model, can partially explain the impact of factors related to climate change and anthropogenic activity on vegetation change in arid regions. It can be further combined with the Budyko hypothesis to establish a framework for quantifying the changes in coupled response of vegetation and hydrological processes to environment changes.

DOI:
10.3390/rs11182110

ISSN: