An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing

Abstract

s u m m a r yAn accurate estimation of evapotranspiration (ET) is crucial to better understand the water budget and improve related studies. Satellite remote sensing provides an unprecedented opportunity to map the spatiotemporal distribution of ET. However, ET values from barren or sparsely vegetated areas in arid regions are often assumed to be zero in typical ET products because of their low values. In addition, separating ET into soil evaporation (E s ) and vegetation transpiration (E c ) is difficult. To address these challenges, we developed an ET product (MOD3T) based on a three-temperature model and thermal remote sensing, specifically Moderate Resolution Imaging Spectroradiometer (MODIS) data. MOD3T has a spatial resolution of 1 km and a temporal resolution of 8 days. All input parameters except air temperature were obtained from MODIS datasets. Validation in two adjacent arid river basins in northwestern China showed that the mean absolute errors (mean absolute percent errors) between the MOD3T and flux tower ET were 0.71 mm d À1 (18.5%) and 0.16 mm d À1 (24.9%) for a densely vegetated area and sparsely vegetated sandy desert, respectively. The error between the MOD3T and water balance ET was 24 mm y À1 (8.1%). The E c /ET or E s /ET of MOD3T was comparable to the observed stable oxygen and hydrogen isotopes. Unlike the MODIS ET (MOD16), MOD3T could not provide continuous ET values (as 70% of the MOD16 area lacked data) but exhibited relatively low uncertainty, particularly in cold seasons. Therefore, MOD3T can provide ET, E s and E c estimates for arid regions within acceptable ranges.

Interpolation of Instantaneous Air Temperature Using Geographical and MODIS Derived Variables with Machine Learning Techniques

“…The results obtained in the present work, especially for RF and RFRK, represent an important improvement with respect to the models based on the adiabatic lapse rate or on the hydrostatic equilibrium of the atmosphere and can be of great help for the improvement of the estimation of the real evapotranspiration, on a regional scale. Traditionally, the temperature at the time of the passage of the satellites, required by most methods, has been obtained using mechanical interpolation techniques, as the Inverse Distance Weighting [76] or models based on the hydrostatic equilibrium of the atmosphere from the values provided by the MODIS MOD07 product [77], which in addition to presenting a lower accuracy than that obtained for RFRK in this work, have the disadvantage of having a spatial resolution of 5 km.…”

Spatiotemporal Changes in Evapotranspiration from an Overexploited Water Resources Basin in Arid Northern China and Their Implications for Ecosystem Management

“…Specifically, MOD16 assumed that ET was zero in sparsely vegetated and barren regions and did not provide ET components, i.e., Es and Ec [25,26]. The MOD3T was estimated based on a three-temperature (3T) model (Equation (2)) and MODIS products (version 5), such as land surface albedo and temperature, vegetation indices and the fraction of absorbed photosynthetically active radiation (FPAR) [27,28]. A detailed description of the 3T model can be found in Xiong et al [28].…”

“…The MOD3T was estimated based on a three-temperature (3T) model (Equation (2)) and MODIS products (version 5), such as land surface albedo and temperature, vegetation indices and the fraction of absorbed photosynthetically active radiation (FPAR) [27,28]. A detailed description of the 3T model can be found in Xiong et al [28]. The MOD3T datasets were used to perform the spatiotemporal analysis of ET in sparsely vegetated areas and to assess water use efficiency (WUE), represented by Ec/ET, for farmland.…”

Uncertainty caused by resistances in evapotranspiration

“…In addition to identifying the uncertainty from resistance parameterizations, the influence of the model structure on ET estimation has been investigated (e.g., Ershadi et al, 2015;Zhao et al, 2015). To avoid the issue of parameterizing 30 resistances, some methods have been proposed to estimate ET without such parameterization, such as the three-temperature (3T) model (Qiu et al, 2006;Xiong et al, 2015;Wang et al, 2016), the Priestley-Taylor method (Priestley and Taylor, 1972), the triangle or trapezoidal method (Price, 1990;Long and Singh, 2012), and the surface-renewal method (Paw U et al, 1995). By eliminating calculation of resistances or local calibration of resistance parameterization, these methods require Hydrol.…”