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Note: Dry taken 23 Feb after air-drying in the lab for 3 days, then baking in the toaster oven for an hour.  (The oven got rid of about another 1.5g in each sample.)

The results show all EC5s about 2% low (which could be due to coupling to the soil, just after installation). 

Note2: 9 Mar sample processed as 2 aliquots (since scale range was limited).  The sum of both aliquots is shown in the above table.

Note3: 20 Apr sample also processed as 2 aliquots.  Both are shown above.

Note4: Tried to get a better depth match with 20 Apr samples, moving the 1cm ring to the top.

Note5: 20 Apr EC5 readings taken using minicom – see teardown comment.

Note6: assume that 9 Mar had a math error: 142.333, rather than 152.333???

tare = c(5.58, 2.15, 2.50, 16.477, 8.237+8.260, 8.232+8.214, 8.265+2.139, 2.126+2.379, 2.111+2.094, 2.079+2.107)

wet = c(100.74, 99.59, 89.51, 142.333, 81.960+60.946, 71.380+74.505, 96.082+29.133, 56.184+61.353, 70.604+60.122, 60.887+70.702)-tare

dry = c(83.54, 87.36, 78.51, 127.741, 70.854+52.124, 62.335+65.162, 84.192+25.476, 46.364+50.476, 58.938+49.878, 50.456+58.281)-tare

vol = 3*pi*(5.31/2)^2

rho = dry/vol

moist = (100*(wet-dry)/volrho = dry/vol) # density numerically equal to volume mixing ratio since rho_water = 1.

ec5 = c(23.98, 16.38, 13.17, 28.4, 29.47, 28.20, 26.00, 30.1, 32.0, 29.4)

ch = as.character(c(1,2,3,1,1,2,3,1,2,3))

col = c(1,1,1,2,2,2,2,1,1,1)

par(las=1,tck=0.02,xaxs="i",yaxs="i")

plot(moist,ec5,xlim=c(0,40),ylim=c(0,40),col=col,pch=ch); abline(0,1,lty=2)

bias = c(1.5,1.5,4.0,0.5,0.5,-0.5,-2.5,1.5,1.5,4.0)

matplotplot(moist,ec5+bias,xlim=c(0,6040),ylim=c(0,60),40),col=col,pch=ch,xlab="Gravimetric (%Vol)",ylab="EC5, bias adjusted (%Vol)"); abline(0,1,lty=2)

legend(2,38,c("bao.20cm","bao.10cm","bao.5cm","ehs.20cm","ehs.10cm","ehs.5cm"),col=c(1,1,1,2,2,2),pch=c("3","2","1","3","2","1"))

title("CABL Gravimetric Sampling")

As of 5/26/15, I would set biases (add to ec5 to make correct) to be:

bao.5cm: 1.5%

bao.10cm: 1.5%

bao.20cm: 4%

ehs.5cm: 0.5%

ehs.10cm: -0.5%

ehs.20cm: -2.5%

5/29/15: 

I've also tried to remove the diurnal cycle, assuming that it is a temperature affect (since vegetation shouldn't have been very active, especially at the beginning of this experiment).  I use the correction:

Q_correct(z) = Q_meas(z) - xm*Tsoil(z),

where:

xm = c(0.11,0.18,0.17,0.12,0.20,0.18) for bao 5,10,20 and ehs 5,10,20 cm, respectively.

With this temperature correction, the bias correction changes a bit:

Q_correct(z) = Q_meas(z) + xb - xm*Tsoil(z)

xb = c(2.3,2.7,5.0,0.5,-0.5,-2.5) (same order as xm, above)

After these corrections, I get the attached plot: Qgrav.pdf, where the left panels are from bao, the right panels from ehs, the top panels are just a bias correction and the bottom panels are with the combined correction.  Also on these plots are the gravimetric samples as circles.  For ehs, Qsoil was read manually (independent of the data system) at the time of the second soil cores, and these values are plotted as "+" (though I don't have the corresponding Tsoil to apply the combined correction).