Study On Evapotranspiration Upscaling Methods And Their Application

Accurate and timely determination of evapotranspiration is essential to a lot of research areas,such as hydrology,agronomy,forestry.The state of the art tools can monitor various temporal scale evapotranspiration data,including hourly,daily,and monthly evapotranspiration data,which is valuable for related research.However,those tools can only measure evapotranspiration data within limited spatial scale,which is already out of the demand of recent research.With the development of remote sense technique,many regional evapotranspiration models were proposed to derive large spatial scale evapotranspiration from remote sense data.Those models are used to estimate regional evapotranspiration which can not be easily measured by the state of the art equipment.However,those models can only be used to derive instantaneous evapotranspiration which is useless for research and practical application.Hence,more work need to be done to convert instantaneous evapotranspiration into daily evapotranspiration or monthly evapotranspiration.Based on the measured data for winter wheat from Daxing district in China and for canola crop from Coleambally Irrigation Area(CIA)in Australia,several methods are evaluated to convert daytime evapotranspiration into daily evapotranspiration and to convert daily evapotranspiration into monthly evapotranspiration.After that,a regional evapotranspiration model is used to derive monthly evapotranspiration for Daxing district and CIA with aforementioned temporal upscaling methods.Moreover,three methods are evaluated to simulate regional dryness index for Daxing district and CIA.After that,soil water content is simulated by crop water stress index method.Results showed that:Three methods,including evaporation fraction(EF)method,crop coefficient(Kc)method and modified crop coefficient(Kcm)method,were evaluated to convert daytime evapotranspiration into daily evapotranspiration based on the measured evapotranspiration for the canola crop and winter wheat crop.All three parameters were nearly constant during daytime.However,only the daytime value of Kc and Kcm were closed to the corresponding daily value.Hence,Kc method and Kcm method performed better than EF method both for the canola crop and winter wheat crop.Moreover,the performance of temporal scaling method was different when different spatial scale daytime data were used.In those methods,the performance of Kc method was less affected when different spatial scale daytime data were used.Three methods,including crop coeffient method,AA method and KP method,were evaluated to convert daily evapotranspiration into monthly evapotranspiration.The linear relation of parameters in AA method and KP method were sometimes not significant due to the fewer calibration data.However,all three methods can get reliable estimated evapotranspiration in a certain situation.Moreover,the performance of crop coefficient method is best than AA method and KP method.Based on the remote sense data,SEBS model was used to derive instantaneous evapotranspiration for Daxing district and CIA.Compared with measured evapotranspiration,the estimated evapotranspiration was reliable when aforementioned temporal scaling methods were applied to convert instantaneous evapotranspiration into daily evapotranspiration and convert daily evapotranspiration into monthly evapotranspiration.Finally,based on the surface temperature,NDVI,latent flux,net radiation and soil heat flux derived from remote sense data,three dryness index methods,including vegetation supply water index,crop water stress index(CWSI)and surface resistance(Rd),were evaluated in this paper.The CWSI method was found suitable to similate regional drought condition for Daxing district and CIA.Moreover,the CWSI method was used to estimate daily soil water content for winter wheat crop.