Jinjun Han, Jianping Wang, Chuntao Zhao, Chao Yue, Zhaofeng Liu
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引用次数: 0
Abstract
The desertification in the Qaidam Basin has significantly impacted the ecological environment and human livelihood. Amidst the backdrop of anomalous climate warming, predicting the dynamic changes and future trends of desertification within the basin is imperative. In this study, we employ a variety of spatio-temporal statistical analyses to examine the evolutionary trend and driving forces of desertification from 2000 to 2021, integrating vegetation coverage (FVC) indices with climatic factors. Furthermore, a predictive model for desertification was developed, utilizing 6th international coupled model comparison programme (CMIP6) model data coupled with a multivariate pixel-based regression approach. The results indicate a 13% reduction, equivalent to 35,766 km2, in the area of severe desertification in the Qaidam Basin from 2000 to 2021. Both non-desertification and mild desertification increased by 7%, indicating a notable reduction in the severity of desertification processes. However, compared to the period from 2000 to 2010, the pace of desertification reversal slowed down between 2011 and 2021, corresponding to the waning upward trend in temperature and precipitation in the upper basin. The desertification prediction model revealed that under the SSP1-26, SSP3-70, SSP2-45, and SSP5-85 scenarios, the vegetation coverage is projected to decline at rates of 0.004/10a, 0.003/10a, 0.002/10a, and 0.002/10a, respectively, from 2015 to 2100. This suggests that desertification in the basin is likely to worsen over time, with greater radiative forcing leading to more pronounced desertification effects. Future FVC projections suggest that desertification mitigation in the Qaidam Basin will plateau around 2040 and then worsen, particularly in the northeast Qilian Mountains. This trend may be due to glacier melting from ongoing climate warming, leading to reduced regional water resources.
期刊介绍:
Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.