Publications

Wang, YP; Li, R; Min, QL; Fu, YF; Wang, Y; Zhong, L; Fu, YY (2019). A three-source satellite algorithm for retrieving all-sky evapotranspiration rate using combined optical and microwave vegetation index at twenty AsiaFlux sites. REMOTE SENSING OF ENVIRONMENT, 235, 111463.

Abstract
Evapotranspiration (ET) composed of transpiration from vegetation (ETveg) and evaporation from soil (ETsoil) and interception water (ETint) is a crucial process for driving global water and energy cycle. In this study, a three-source satellite ET algorithm is developed for estimating instantaneous ET rate (ETcal) under clear and non-rainy cloudy sky conditions and is validated at 20 AsiaFlux sites of multiple vegetation types (evergreen and deciduous forests, croplands and grasslands) in East Asia. The ET algorithm is completely independent from ground-based measurements and thus has the potential to be used on regional scale. All-sky surface net radiation flux is derived from satellite products. Satellite optical Normalized Difference Vegetation Index (NDVI) is used to partition the surface available energy into vegetated area and bare soil area. Satellite microwave Emissivity Difference Vegetation Index (EDVI), an indicator of vegetation water content, is utilized to estimate canopy resistance and transpiration from vegetation. Evaporation components from canopy interception water and soil surface are estimated based on Priestley-Taylor method. The estimated evaporation fraction (EF) for all sites can produce a small absolute bias of less than 0.03 (or 8.1%) with a good determination coefficient (R-2) larger than 0.42 when validated against the corrected in-situ measured EF on instantaneous and long-term mean scales. Instantaneous ETcal under all sky conditions are found to have a R-2 of 0.61, a bias of 16.5 Wm(-2) (13.7%) and a root mean square error (RMSE) of 63.6 Wm(-2) (52.5%) over all sites, respectively. The performances of this algorithm are better achieved on 16-day (R-2 = 0.66, RMSE = 44.1 Wm(-2)) and monthly (R-2 = 0.70, RMSE = 39.1 Wm(-2)) scales. More importantly, EDVI-based ET method is able to produce ETcal with stable and good accuracy from clear sky to overcast sky (bias < 22 Wm(-2) or 18%, RMSE < 77 Wm(-2) or 59%). The daily ET and its components (ETveg, ETsoil and ETint) derived from our algorithm are further compared with those from Global Land Evaporation Amsterdam Model (GLEAM) ET products. EDVI-based ET (EDVI-ET) generally shows equal performances with GLEAM-ET when using in-situ ET as reference. EDVI-ET veg shows a fairly good correlation (R-2 = 0.21) and an underestimation of -0.32 mm/day compared with GLEAM-ETveg. EDVI-ETint shows a significant correlation (R-2 = 0.30) with GLEAM-ETveg after excluding three outlier tropical forest sites. Meanwhile, EDVI-ETsoil shows a fairly good positive correlation (R-2 = 0.15) and an overestimation of 0.23 mm/day compared with GLEAMET, ETsoil] . The results indicate that our method has great potential for regional ET estimation under various cloud conditions when combined with satellite optical and microwave remote sensing.

DOI:
10.1016/j.rse.2019.111463

ISSN:
0034-4257