Understanding shallow soil moisture variation in the data-scarce area and its relationship with climate change by GLDAS data

利用GLDAS数据了解数据匮乏地区浅层土壤湿度变化及其与气候变化的关系

阅读:1

Abstract

Quantitatively evaluating the spatiotemporal variation of soil moisture (SM) and its causes can help us to understand regional eco-hydrological processes. However, the complicated geographical environment and the scarce observation data make it difficult to evaluate SM in Northwest China. Selecting the Tarim River Basin (TRB) as a typical representative of the data-scarce area in Northwest China, we conducted an integrated approach to quantitatively assess the spatiotemporal variation of shallow soil moisture (SSM) and its responses to climate change by gathering the earth system data product. Results show that the low-value of SSM distributes in Taklamakan Desert while the high-value basically distributes in the Pamirs and the southern foothill of Tianshan Mountains, where the land types are mostly forest, grassland, and farmland. Annual average SSM of these three land types present a significant increasing trend during the study period. SM at 0-10 cm of all land types are positively correlated to precipitation in spring and autumn, and SM at 0-10 cm in the forest, grassland, and farmland are positively correlated with temperature in winter. SSM presents in-phase relation with precipitation whereas it presents anti-phase relation with temperature, with the significant resonance periods about 6-8 years and 2-3 years which mainly distribute from 1970s to early 1990s and 1960s respectively. The time lags of SSM relative to temperature change are longer than its lags relative to precipitation change, and the lags vary from different land types.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。