Abstract
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 paper. In this paper, 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 (GNSS) and temperature (T). The initial PET value was calculated by using the PET periodical model based on PenmanMonteith (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 evapotransporation index (SPEI) were compared with those from the Thornthwaite (TH) and revised TH (RTH) models over the loess plateau (LP) area with the PM-derived PET and SPEI as references. Comparison results highlight the excellent performance of the proposed HDM model and the Pearsons correlations of SPEI between the HDM and PM models all exceeded 0.96 under different month scales.
Highlights
Drought destroys natural environments and social economies [1] and monitoring its initiation and evolution across time and space is critical [2]
global navigation satellite system (GNSS)-derived zenith troposphere delay (ZTD) was collected from the Crustal Movement Observation Network of China (CMONOC), whereas Precipitable Water Vapor (PWV), T, and pressure (P) data were obtained from ERA-Interim with the spatial-temporal resolutions of monthly and 0.125°×0.125°, respectively
CMONOC comprises more than 260 GNSS stations that are mainly used for continuous earthquake prediction [23], geodesy [24], and weather radiosonde with a root mean square (RMS) of 19.1 mm from 2011 to 2017 [26]
Summary
Drought destroys natural environments and social economies [1] and monitoring its initiation and evolution across time and space is critical [2]. To better reflect drought conditions, Vicente-Serrano et al proposed SPEI, which considers the impact of both potential evapotranspiration (PET) and precipitation on drought, accumulates the values of precipitation and PET, and reflects the characteristics of drought at different time scales [7] Given these benefits, SPEI has been widely used all over the world for drought monitoring. A spherical harmonic function was introduced to fit the model coefficients, and the expression of the HDM model differed at arbitrary locations within the LP area This model can obtain high-precision PET values while using a limited number of meteorological parameters, thereby effectively improving its accuracy in calculating SPEI and further expanding the application of GNSS in drought monitoring
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