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,*,Click to edit Master title style,Click to edit Master text styles,Second level,Third level,Fourth level,Fifth level,A Sensitivity Analysis on Remote Sensing ET AlgorithmRemote Evapotranspiration Calculation(RET),Junming Wang,Ted.Sammis,Luke Simmons,David Miller,and Craig Meier,Agronomy and Horticulture Dept.,New Mexico State University,Objective,Find the key variables and equations in the ET estimate that are most sensitive to change in input or change in functions within the calculations.,Procedure,Build the model,Validate it,Sensitivity analysis,Build the ModelASTER Satellite from NASA,15 by 15 m visible and near-infrared radiance.Bands 1-3,30 by 30 m shortwave infrared radiance.Bands 4-9,90 by 90 m infrared radiance.Bands 10-14,Reflectance(Bands1-9)and temperature data can be requested as secondary processed data,Availability:potentially 16 days upon request,Reflectance(resolution 15 by 15 m),Build the Model,Temperature(resolution 90 by 90 m),Build the Model,Build the modelTheory,ETins=Rn -G -H,R,n,G,H,ETins,Graph from Allen,et.al.,(2002),Build the Model,NDVI=f(reflectance,),H=,f,(NDVI,temperature,reflectance,solar radiation,wind speed),G=,f,(NDVI,solar radiation,reflectance),End,Start,ETins=Rn-H-G,Output daily ET,General flowchart,Rn=,f,(Rs,reflectance),Build the Model,Satellite inputs:surface temperature and reflectance.,Local weather inputs:solar radiation,humidity and wind speed,Rn,Rn=Rns-Rnl=net radiation,Rns=(1-,)Rs=net solar radiation is surface albedo,=0.484,1,+0.335,3,-0.324,5,+0.551,6,+0.305,8,-0.376,9,-0.0015,i,is the reflectance for ASTER data band I,averaged to 90m,2,resolution.,Rnl=f(RH,Ts)=net long wave radiation,Build the Model,Empirical function G=Rn*C,NDVI from,ASTER,reflectance data of bands 3 and 2,Build the Model,Sensible Heat Flux(H),H=(,r,c,p,dT)/r,ah,H,r,ah,dT,r,ah,=the aerodynamic resistance to heat transport(s/m).,z,1,z,2,dT,=the near surface temperature difference(K).,Graph from Allen,et.al.,(2002),Build the Model,r,ah,=ln(z2/z1)/(u*k),u*=friction velocity,Selection of“Anchor Pixels for dT calculation,“wet pixel:Ts Tair,“dry pixel:ET 0,Ts=303 K,Ts=323 K,Build the Model,At the“wet pixel:,dTwet=Ts-Tair=0,Should be an alfalfa field,not cut and not stressed for water,At the“dry pixel:Hdry=Rn G-ETdry,where ETdry=0,dTdry=Hdry rah/(cp),Should be a bare soil field where evaporation is zero.,Build the Model,dT regression,Build the Model,Sensible Heat Flux(H),dT for each pixel is computed using the regression.,H is calculated for each pixel after calculating rah for each pixel,H=(,cp dT)/rah,Build the Model,Start,Calculate friction velocity(u*)at weather station and use to get wind speed at 200m,Calculate roughness length(z,o,m),for each pixel from NDVI,Calculate dT for each pixel from Ts,Calculate friction velocity(u*)for each pixel,Calculate r,ah,for each pixel,Calculate H for each pixel,Calculate stability parameter for each pixel,Update H for each pixel based on stability parameter and iterate till change in H less than 10%,End,Build the Model,Calculate Et from energy balance,Et Calculation,Obtain instant latent heat for each pixel,ETins=Rn -G -H,Obtain instant reference latent heat for irrigated,alfalfa field(,ETrins),Obtain Daily reference ET calculated by FAO Penman-Monteith from weather station for alfalfa field(,ETrdaily),Calculated ET daily for each pixel,ETdaily=,ETins/ETrinsETrdaily,Build the Model,Validate the modelMeasurement sites,Pecan orchard,Alfalfa field,Build the Model,ET measurement,Li Cor,system,Validate the Model,ET map,mm/day,Validate the Model,The pecan ET of simulation vs.observation.,Validate the Model,The data represent no cover,partial leaf cover and closed canopy.,Average of relative error all days 11%with the greatest%error when Et was small in the winter and early spring.,Average error,Validate the Model,Sensitivity analysis,ET=Rn-G-H,Sensitivity Analysis areas,Full vegetation area(6 points,NDVI=0.57),Half vegetation area(6 points,NDVI=0.31),Little vegetation area(6 points,NDVI=0.19),Sensitivity analysis,Sensitivity analysis,Sensitivity Analysis,Variables related to Rn,Rs(500-1100 w/m,2,),(0.1-0.4),Variables related to G,C(G/Rn,0.1-0.5),Variables related to H,rah(0-100 s/m,),Variables were c,hanged over a typical rang for the selected six pixels,dT regression,Build the Model,ET vs.dT,dT is linearly related to Ts,H=f(dT,rah,u*,L,Zom),Sensitivity analysis,ET vs.dT,ET is sensitive to dT which is calculated from Ts.,An error in your hot or cold spot dT calculation results in error in H and ET for intermediate points.,Ts from satellite is not sensitive as an absolute number only as a relative number which may represent a 2%error in dT and ET,If the algorithms in the model are to be changed,the dT calculation equation will be the key equation.It may not be linear,Sensitivity analysis,ET vs.Rs,Rns=(1-,)Rs,Rn=Rns-Rnl,Sensitivity analysis,ET vs.Rs,ET is sensitive to Rs which determines Rn.,Rs is from local weather stations and errors in this value can be as high
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