Spatial–Temporal Variation Characteristics of Water Bodies and Their Climatic Drivers Over the Qinghai–Tibet Plateau in 2002-2020

Abstract

The spatial–temporal characteristics of water bodies and their response to climatic factors are significant for the study of the water budget and the ecological environment. As Asia's water tower, the Qinghai–Tibet Plateau (QTP) has abundant surface water bodies, whose distribution and duration are sensitive to climate change. In this article, the surface water of the QTP in the recent 20 years was extracted from Landsat series TM/ETM+/OLI data combined with the Joint Research Centre of European Commission water body dataset. In addition, the temporal and spatial variation characteristics of the surface water area over the QTP were analyzed, and the climatic factors driving its dynamic change were explored based on 13 climatic variables. Results showed the following: First, from 2002 to 2020, the area of permanent water body in QTP increased from about 46 300 km2 to about 54 700 km2, showing the characteristics of increase in the north and decrease in the south. The area of seasonal water area decreased from about 8900 km2 to about 6600 km2, which were characterized by increase in the west and decrease in the east. Second, with 13 climatic variables reflecting the overall, seasonal, and extreme values of climate changes, the annual total precipitation had the strongest effect on the permanent water area over the total QTP, and the autumn mean air temperature was most relevant with the seasonal water area. Third, the predicted permanent water area of the QTP showed a trend of first slow and then fast increasing during 2021–2025, and expanded by 294 km2 in 2025 compared with 2021, whereas the seasonal water area first increased by 131 km2 and then decreased by 203 km2. These results will help provide important references for water resource management and ecological environment protection in QTP.

Keywords

• Climate change
• landsat series data
• Qinghai–Tibet Plateau (QTP)
• spatiotemporal variation analysis
• surface water body extraction