Study On Estimation Of Land Surface Evapotranspiration Driven By Microwave Soil Moisture

Soil water is the core and link of groundwater-soil water-atmospheric water circulation system,evapotranspiration,as an important driving force of the system,is of great significance for energy balance and water balance to study the distribution characteristics of soil moisture and evapotranspiration on a regional scale.However,a large amount of ground observation data is needed in evapotranspiration estimation.Therefore,how to carry out evapotranspiration simulation estimation in areas without measuring sites or lack of observation data has always been a difficulty in hydrology research.With the development of remote sensing technology,a large amount of remote sensing data can play an increasingly important role in the study of evapotranspiration.With remote sensing as the main technical means in this study,the Southern Great Plains of the United States was selected as the study area,and SMAP passive microwave remote sensing data and MODIS remote sensing data were used as data sources to carry out researches on soil moisture downscaling,evapotranspiration estimation,factors and correlation analysis affecting evapotranspiration.Soil moisture parameters were optimized for each SMAP pixel,using the solar zenitic Angle and surface temperature parameters provided by MODIS data in a small area one by one,the cosine function relationship was established through the empirical relationship between them.Moreover,the value obtained by fitting was optimized as the theoretical dry and wet edges of the feature space,a 1km high-resolution MTVDI was obtained from the optimized dry and wet edges.A 1km soil moisture product was obtained after nonlinear fitting between the high-resolution MTVDI and the 36 km coarse resolution SMAP product.The method avoids the accumulated error caused by multiple parameters and reduces the dependence of temperature vegetation index on dry edge.An actual evapotranspiration simulation framework based on remote sensing data was proposed.The evaporation fraction was estimated by using soil moisture downscaling factor(1-MTVDI)as the driving force,the daily net radiation flux was expanded by the instantaneous surface net radiation,and the daily evapotranspiration was obtained by combining the evaporation ratio and the daily net radiation flux.The estimated and measured values of the flux in various tables were verified and analyzed.The results show that the actual evapotranspiration of this method is completely estimated by remote sensing data,which completely gets rid of the dependence on the measured data.The variation trend of daily evapotranspiration and each influencing factor based on the evapotranspiration model was analyzed.The results showed that among the influencing factors,sunshine duration had the greatest correlation with daily evapotranspiration,followed by NDVI and air temperature,while relative humidity,wind speed and air pressure had little correlation with evapotranspiration.Soil moisture downscaling,evapotranspiration estimation,and the influence factors and correlation analysis of evapotranspiration are studied in this paper,which can provide certain guidance for the spatio-temporal monitoring research of soil moisture and evapotranspiration process at regional scale by remote sensing.