Temporal and Spatial Variations of Soil Moisture Over Xinjiang Based on Multiple GLDAS Datasets

Zengyun Hu,Xi Chen,Qiming Zhou,Gang Yin,Yaoming Li

doi:10.3389/feart.2021.654848

Abstract

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.

Highlights

As one of the key hydrological variables, soil moisture plays a fundamental role in the complex physical processes, such as infiltration, rainfall-evapotranspiration-runoff circulation, photosynthesis, and groundwater recharge (Ford et al, 2015; Amani et al, 2017; Orth and Seneviratne, 2017; Dari et al, 2019; Gu et al, 2019a)
We only explored the temporal and spatial variations of the soil moisture over Xinjiang using multiple Global Land Data Assimilation System (GLDAS) datasets
In recent study (Supplementary Figure S3 in Hu et al, 2019b), it was proved that Noah, Variable Infiltration Capacity (VIC), Mosaic had the positive linear trends of soil moisture in Xinjiang except the Community Land Model (CLM) model which are similar with the result of this study

Summary

Introduction

As one of the key hydrological variables, soil moisture plays a fundamental role in the complex physical processes, such as infiltration, rainfall-evapotranspiration-runoff circulation, photosynthesis, and groundwater recharge (Ford et al, 2015; Amani et al, 2017; Orth and Seneviratne, 2017; Dari et al, 2019; Gu et al, 2019a). Compared with the in-situ measurements, model output of soil moisture has the advantages with the high spatial and temporal resolutions which have been widely employed in regional and global researches to explore different climate and hydrological processes, such as analyzing the historical and future variations of moisture (Cheng et al, 2015; Chen et al, 2016), monitoring the dry and wet changes (Robinson et al, 2016; Hu et al, 2019a), improving the hydrological model simulations (He et al, 2017), and explaining the dynamics of land-atmosphere interactions (Gerken et al, 2015; May et al, 2015)

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Discussion

Conclusion