Estimation and Spatiotemporal Distribution of Soil Heat Flux over the Qinghai–Tibetan Plateau

Soil heat flux (G) is one of the key factors affecting the surface energy balance over the Qinghai–Tibetan Plateau. Estimation and analysis of its spatiotemporal distribution can provide reference basis for research on surface energy balance in the Qinghai–Tibetan Plateau. In this paper, the applicability and accuracy of the Surface Energy Balance Algorithm for Land (SEBAL) model were evaluated by combining the model inversion data with observation data over the Qinghai–Tibetan Plateau from 2003 to 2018 based on Moderate-Resolution Imaging Spectroradiometer (MODIS), the China regional surface meteorological element driven dataset, and the 1-km all-weather surface temperature dataset from western China. We found that the SEBAL model had high accuracy for inverting G over the Qinghai–Tibetan Plateau. Accordingly, G values were inverted using remote-sensing data and the spatiotemporal distribution characteristics of G in the region were analyzed during 2003–2018. The results showed the following. (1) The mean value of G showed a fluctuating downward trend over a multiyear period, with the maximum valley value appearing in 2011 and the maximum peak value in 2016. The mean value of G demonstrated a fluctuating downward trend in every season except in winter. The mean value ranges of G in different seasons showed the following trend: Summer ＞ spring ＞ autumn ＞ winter, the fluctuation in the mean value of G corresponded to this order in magnitude. (2) The spatial distribution characteristics of the mean value of G exhibited obvious spatial heterogeneity, with the overall trend being highest in the northern Qaidam Basin and its surrounding areas, relatively high in the southwestern Ngari region, and generally lower in most other areas. The spatial distribution characteristics of the mean value of G in each season generally aligned with the overall spatial distribution characteristics. (3) In the central and southeastern regions, the mean value of G mainly showed an increasing trend, while in the northern, western, and southwestern regions, the mean value of G mainly showed a decreasing trend. Among all seasons, the proportion of areas with an increasing trend in G was highest in winter and lowest in summer, while the proportion of areas with a decreasing trend was highest in summer and lowest in winter. The results of this study demonstrate the applicability of the SEBAL model for inverting G and enriching the studies on the surface energy balance over the Qinghai–Tibetan Plateau.