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

Zuo, Jingping; Xu, Jiang; Li, Weihong; Yang, Dongyang

doi:10.1371/journal.pone.0217020

Cited by 6 publications

(2 citation statements)

References 43 publications

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“…The root zone soil moisture (RSM) data used in this study are from the Global Land Data Assimilation System (GLDAS). GLDAS combines satellite and ground meteorological observation data [56][57][58]. And several studies have showed that the simulated soil moisture from GLDAS have good correlation and consistency with ground-based soil moisture [59].…”

Section: Study Area and Datamentioning

confidence: 99%

Analysis of Vegetation Vulnerability Dynamics and Driving Forces to Multiple Drought Stresses in a Changing Environment

Wei

Huang

et al. 2022

Remote Sensing

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Quantifying changes in the vulnerability of vegetation to various drought stresses in different seasons is important for rational and effective ecological conservation and restoration. However, the vulnerability of vegetation and its dynamics in a changing environment are still unknown, and quantitative attribution analysis of vulnerability changes has been rarely studied. To this end, this study explored the changes of vegetation vulnerability characteristics under various drought stresses in Xinjiang and conducted quantitative attribution analysis using the random forest method. In addition, the effects of ecological water transport and increased irrigation areas on vegetation vulnerability dynamics were examined. The standardized precipitation index (SPI), standardized precipitation-evapotranspiration index (SPEI), and standardized soil moisture index (SSMI) represent atmospheric water supply stress, water and heat supply stress, and soil water supply stress, respectively. The results showed that: (1) different vegetation types responded differently to water stress, with grasslands being more sensitive than forests and croplands in summer; (2) increased vegetation vulnerability under drought stresses dominated in Xinjiang after 2003, with vegetation growth and near-surface temperature being the main drivers, while increased soil moisture in the root zone was the main driver of decreased vegetation vulnerability; (3) vulnerability of cropland to SPI/SPEI/SSMI-related water stress increased due to the rapid expansion of irrigation areas, which led to increasing water demand in autumn that was difficult to meet; and (4) after ecological water transport of the Tarim River Basin, the vulnerability of its downstream vegetation to drought was reduced.

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Section: Study Area and Datamentioning

confidence: 99%

Analysis of Vegetation Vulnerability Dynamics and Driving Forces to Multiple Drought Stresses in a Changing Environment

Wei

Huang

et al. 2022

Remote Sensing

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“…Northwest China is rich in natural resources with an extremely vulnerable ecological environment due to its limited water resources [6,7]. Under the background of global warming, the climate change in Northwest China has presented a warm-wet trend during the past decades [4,6,9]. The significant increases in precipitation are mainly due to the increases in summer precipitation.…”

Section: Introductionmentioning

confidence: 99%

Downscaling Precipitation in the Data-Scarce Inland River Basin of Northwest China Based on Earth System Data Products

Zuo

Chen

et al. 2019

Atmosphere

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Precipitation is a key climatic variable that connects the processes of atmosphere and land surface, and it plays a leading role in the water cycle. However, the vast area of Northwest China, its complex geographical environment, and its scarce observation data make it difficult to deeply understand the temporal and spatial variation of precipitation. This paper establishes a statistical downscaling model to downscale the monthly precipitation in the inland river basin of Northwest China with the Tarim River Basin (TRB) as a typical representation. This method combines polynomial regression and machine learning, and it uses the batch gradient descent (BGD) algorithm to train the regression model. We downscale the monthly precipitation and obtain a dataset from January 2001 to December 2017 with a spatial resolution of 1 km × 1 km. The results show that the downscaling model presents a good performance in precipitation simulation with a high resolution, and it is more effective than ordinary polynomial regression. We also investigate the temporal and spatial variations of precipitation in the TRB based on the downscaling dataset. Analyses illustrate that the annual precipitation in the southern foothills of the Tianshan Mountains and the North Kunlun Mountains showed a significant upward trend during the study periods, while the annual precipitation in the central plains presented a significant downward trend.

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Spatio-temporal changes in global root zone soil moisture from 1981 to 2017

Luo,

Li,

Yang

et al. 2023

Journal of Hydrology

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

Cited by 6 publications

References 43 publications

Analysis of Vegetation Vulnerability Dynamics and Driving Forces to Multiple Drought Stresses in a Changing Environment

Analysis of Vegetation Vulnerability Dynamics and Driving Forces to Multiple Drought Stresses in a Changing Environment

Downscaling Precipitation in the Data-Scarce Inland River Basin of Northwest China Based on Earth System Data Products

Spatio-temporal changes in global root zone soil moisture from 1981 to 2017

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