Microwave soil moisture dynamics and response to climate change in Central Asia and Xinjiang Province, China, over the last 30 years

Xinwu Li; Xizhang Gao; Jingkai Wang; Huadong Guo

doi:10.1117/1.JRS.9.096012

11 September 2015 Microwave soil moisture dynamics and response to climate change in Central Asia and Xinjiang Province, China, over the last 30 years

Xinwu Li, Xizhang Gao, Jingkai Wang, Huadong Guo

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 096012 (September 2015). https://doi.org/10.1117/1.JRS.9.096012

Abstract

In this study, an analytical methodology based on four typical statistical analysis methods was proposed to understand soil moisture (SM) dynamics and their response to climate change in Central Asia and Xinjiang over 30 years using the essential climate variable-soil moisture dataset and the Climate Research Unit (CRU) dataset. The results are as follows: (1) In general, the SM of the study area decreased significantly over the last 30 years. The significant warming trend dominated the soil desiccation. (2) The soil desiccation trend is more severe in Central Asia than in Xinjiang, while the SM in Xinjiang has increased gradually since 2004. The trends of soil desiccation in Central Asia and Xinjiang consistently and negatively feedback to the significant warming trend. (3) The SM for all five countries of Central Asia distinctly decreased. The significant increase in temperature dominated the soil desiccation in the other four countries of Central Asia except for Kyrgyzstan, while precipitation had no significant impact on SM. (4) The regions with drying and warming trends and with drying and cooling trends (∼89% of the total area) were largely distributed in major agricultural areas; these trends are unfavorable to the sustainable development of agriculture.

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Xinwu Li, Xizhang Gao, Jingkai Wang, and Huadong Guo "Microwave soil moisture dynamics and response to climate change in Central Asia and Xinjiang Province, China, over the last 30 years," Journal of Applied Remote Sensing 9(1), 096012 (11 September 2015). https://doi.org/10.1117/1.JRS.9.096012

Published: 11 September 2015

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