Retrieval of a High-Precision Drought Monitoring Index by Using GNSS-Derived ZTD and Temperature

Potential evapotranspiration (PET) is a key parameter for calculating drought monitoring index that is generally difficult to obtain. In addition, PET has low spatial resolution and can only be obtained at a site-based point. Therefore, retrieving PET with high precision, high spatial resolution, an...

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Veröffentlicht in:IEEE journal of selected topics in applied earth observations and remote sensing 2021, Vol.14, p.8730-8743
Hauptverfasser: Zhao, Qingzhi, Ma, Yongjie, Li, Zufeng, Yao, Yibin
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Sprache:eng
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Zusammenfassung:Potential evapotranspiration (PET) is a key parameter for calculating drought monitoring index that is generally difficult to obtain. In addition, PET has low spatial resolution and can only be obtained at a site-based point. Therefore, retrieving PET with high precision, high spatial resolution, and less meteorological data becomes the focus of this article. In this article, a high-precision and high-spatial-resolution drought monitoring (HDM) model was established to accurately calculate PET by using the zenith troposphere delay (ZTD) derived from global navigation satellite system and temperature (T). The initial PET value was calculated by using the PET periodical model based on Penman-Monteith (PM) derived PET. The PET difference (DET) between the PM and periodic model was then calculated, and a multiple linear regression model was established to fit DET by using the ZTD and T differences at meteorological stations. To improve the spatial resolution of the calculated PET, a spherical harmonic function was applied to fit the coefficients of these stations. The HDM-derived PET at grid points was eventually obtained by using the fitted coefficients and ZTD/T. The HDM-derived PET and standardized precipitation evapotranspiration index (SPEI) were compared with those from the Thornthwaite (TH) and revised TH models over the loess plateau area with the PM-derived PET and SPEI as references. Comparison results highlight the excellent performance of the proposed HDM model and the Pearson's correlations of SPEI between the HDM and PM models all exceeded 0.96 under different month scales.
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2021.3106703