Mapping evapotranspiration using MODIS and MM5 Four-Dimensional Data Assimilation

Abstract

Evapotranspiration (ET), the sum of evaporation from soil and transpiration from vegetation, is of vital importance in the hydrologic cycle and must be taken into consideration in assessments of the water resources of any region. The MODerate resolution Imaging Spectroradiometer (MODIS) sensor offers a promising opportunity for estimating daily ET with a 1 km spatial resolution, but is hampered by frequent cloud contamination or data gaps from other factors. In this study, 1) a stand-alone ET model was applied and tested during clear or partial cloudy sky conditions using MODIS-based inputs of land surface and atmospheric data and 2) meteorological simulations by using Four-Dimensional Data Assimilation (FDDA) system between MODIS and the 5th Generation Meso-scale Meteorological Model (MM5) was used in cloudy conditions to facilitate continuous daily ET estimates. The MODIS ET algorithm modified from Mu et al. (2007) is based on the Penman–Monteith equation and was applied to predict ET at flux measurement sites. This algorithm considers both the effects of surface energy partitioning processes and environmental constraints on ET. We devised gap-filling approaches for MODIS aerosol and albedo data that were identified as bottlenecks to determine retrieval rates of insolation and ET. MODIS-derived input variables (i.e., meteorological variables and radiation components) for estimating ET showed a good agreement with flux tower observations at each site. The retrieval rate of MODIS ET doubled at four flux measurement sites after gap-filling with negligible compensation was undertaken for accuracy. In spite of the high accuracy of MODIS-derived input variables, MODIS ET showed meaningful errors at the four flux measurement sites. These errors were mainly associated with errors in the estimated canopy conductance. During clear sky conditions, MODIS was used to calculate ET, while the MODIS-MM5 FDDA system provided input variables for the calculation of ET under cloudy sky conditions. The performance of the MODIS-MM5 FDDA system was evaluated by comparing ET based on MODIS, which showed a good agreement with the MODIS ET for various land cover types. Our results indicate that MODIS can be applied to monitor the land surface energy budget and ET with reasonable accuracy and that MODIS-MM5 FDDA has the potential to provide reasonable input data of ET estimation under cloudy conditions.