Under the global warming, as the typical arid region of Central Asia, the Xinjiang Uygur Autonomous Region (Xinjiang) has been experienced the remarkable warming and increased precipitation based on large previous studies. The arid and semiarid ecosystem of Xinjiang is very sensitive and vulnerable to climate change and water resource variations. However, the sparse and highly unevenly distributed in-situ stations in this region provide limited data for understanding of the soil moisture variations. In this study, the spatial and temporal changes and variations of soil moisture were explored at annual and seasonal time scales during the period of 2000–2017. The soil moisture data are from the Global Land Data Assimilation System (GLDAS) models, including four GLDAS 1 models: CLM, Mosaic, VIC and Noah 2.7 and one GLDAS 2.1 model: Noah 3.3. Major results show that 1) Noah 3.3 and VIC have the significant positive trends of annual soil moisture with the values of 2.64°mm/a and 0.98°mm/a. The trend of CLM is significant negative. The other two models Mosaic and Noah 2.7 have the weak positive trends. The temporal variations of seasonal soil moisutre are similar the annual soil moisture for each of the model. 2) For the spatial characteristics of the soil mositure variations, CLM displays the negative trends over large part of Xinjiang. Mosaic and VIC have the similar spatial characteristics of the linear trends. Noah 3.3 has the significant positive trends over almost Xinjiang which is different with Noah 2.7. All the five models have the positive trends over KLM. Our results have a better understanding of the soil moisture variations across Xinjiang, and they also enhance the reconginzing of the complex hydrological circulation in the arid regions.
Scopus Subject Areas
- Earth and Planetary Sciences(all)
- GLDAS product
- linear trend
- soil moisture
- spatial and temporal variation