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Large-scale monitoring of soil moisture using Temperature Vegetation Quantitative Index (TVQI) and exponential filtering: A case study in Beijing

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Listed:
  • Zhao, Ziyang
  • Wang, Hongrui
  • Qin, Daoqing
  • Wang, Cheng

Abstract

In this study, to understand the variation trend of soil moisture in Beijing, surface soil moisture retrieval, deep soil moisture estimation and spatiotemporal distribution characteristics from 2013 to 2014 were analyzed. The results showed that the Temperature Vegetation Quantitative Index (TVQI), which was modified from the TVDI by the quantitative dry edge and wet edge, is effective for predicting surface soil moisture. The coefficient of determination (R2), root man squared error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE) of the TVQI increased by 0.2, 0.3%, and 4.6, respectively, compared to those of the TVDI. Moreover, the TVQI is closely related to cumulative precipitation within 1 month, as the correlation is the highest in this time interval. The accuracy of surface soil moisture retrieval was good, with relative error (RE), R2, and NSE values of 6%, 0.9 and 0.7, respectively. The deep soil moisture estimations performed well at both 20 cm and 40 cm, with an average R2 above 0.9, an average RE below 0.1 and an average NSE above 0.7. However, the prediction accuracy decreased as the soil depth increased. Topt, the best characteristic time length of the exponential filter, was significantly related to the soil bulk density, while the precipitation meteorological condition had little effect. Moreover, the average Topt of all stations can be used instead of the Topt of each station. Beijing, the study area, is dry throughout the year, with soil moisture reaching a minimum in May and a maximum in July. The changes in soil moisture at 10 cm, 20 cm and 40 cm were consistent, and soil moisture increased with soil depth. Furthermore, the variation trends of soil moisture were high in the east and low in the west. Not only is this study important for understanding soil moisture variation trends; it also provides a preliminary reference for water management in Beijing.

Suggested Citation

  • Zhao, Ziyang & Wang, Hongrui & Qin, Daoqing & Wang, Cheng, 2021. "Large-scale monitoring of soil moisture using Temperature Vegetation Quantitative Index (TVQI) and exponential filtering: A case study in Beijing," Agricultural Water Management, Elsevier, vol. 252(C).
    • Handle: RePEc:eee:agiwat:v:252:y:2021:i:c:s037837742100161x
    DOI: 10.1016/j.agwat.2021.106896
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    References listed on IDEAS

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    1. Zhang, Biao & Fu, Zetian & Wang, Jieqiong & Zhang, Lingxian, 2019. "Farmers’ adoption of water-saving irrigation technology alleviates water scarcity in metropolis suburbs: A case study of Beijing, China," Agricultural Water Management, Elsevier, vol. 212(C), pages 349-357.
    2. Zhao, Ziyang & Wang, Hongrui & Wang, Cheng & Li, Wangcheng & Chen, Hao & Deng, Caiyun, 2020. "Changes in reference evapotranspiration over Northwest China from 1957 to 2018: Variation characteristics, cause analysis and relationships with atmospheric circulation," Agricultural Water Management, Elsevier, vol. 231(C).
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