Abstract
Understanding the spatial and temporal variations of evapotranspiration (ET) is vital for water resources planning and management and drought monitoring. The development of a satellite remote sensing technique is described to provide insight into the estimation of ET at a regional scale. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to calculate the actual ET on a daily scale from Landsat-8 data and daily ground-based meteorological data in the upper reaches of Huaihe River on 20 November 2013, 16 April 2015 and 23 March 2018. In order to evaluate the performance of the SEBAL model, the daily SEBAL ET (ETSEBAL) was compared against the daily reference ET (ET0) from four theoretical methods: the Penman-Monteith (P-M), Irmak-Allen (I-A), the Turc, and Jensen-Haise (J-H) method, the ETMOD16 product from the MODerate Resolution Imaging Spectrometer (MOD16) and the ETVIC from Variable Infiltration Capacity Model (VIC). A linear regression equation and statistical indices were used to model performance evaluation. The results showed that the daily ETSEBAL correlated very well with the ET0, ETMOD16, and ETVIC, and bias between the ETSEBAL with them was less than 1.5%. In general, the SEBAL model could provide good estimations in daily ET over the study region. In addition, the spatial-temporal distribution of ETSEBAL was explored. The variation of ETSEBAL was significant in seasons with high values during the growth period of vegetation in March and April and low values in November. Spatially, the daily ETSEBAL values in the mountain area were much higher than those in the plain areas over the study region. The variability of ETSEBAL in this study area was positively correlated with elevation and negatively correlated with surface reflectance, which implies that elevation and surface reflectance are the important factors for predicting ET in this study area.
Highlights
Surface evapotranspiration (ET) as a crucial part of energy transfer, has an important impact on the growth and development of plant roots [1,2]
The results showed that the daily ETSEBAL correlated very well with the ET0, ETMOD16, and ETVIC, and bias between the ETSEBAL with them was less than 1.5%
Evapotranspiration values obtained using the Surface Energy Balance Algorithm for Land (SEBAL) model (ETSEBAL), Variable Infiltration Capacity Model (VIC) model (ETVIC), four theoretical (P-M, I-A, Turc, and J-H) methods (ET0) and remote sensing ET (ETMOD16) for eight stations on 20 November 2013 over the study region are shown in Table 5, and comparisons for ETSEBAL are made with ET0, ETVIC and ETMOD16 (Table 6)
Summary
Surface evapotranspiration (ET) as a crucial part of energy transfer, has an important impact on the growth and development of plant roots [1,2]. Sensitivity of P-M method in estimating ET with climatic variables for different climate regions in India was examined by Debnath [10], and results showed that the sensitivity of ET to the climate variables had considerable spatial and temporal variation. This method requires a full climate dataset that is not always available at all weather stations, especially in most of the developing countries. Using the water balance method, Liu et al [11] calculated the reference annual ET for 35 global river basins to evaluate the performance of nine products in ET estimation. Due to the difficulties in gathering all of the necessary climate variables, and the sparse network of point observations can present serious limitations for these methods
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