UNDERSTANDING VARIATION IN PARTITION COEFFICIENT, Kd ...

KD
PH
CEC
EC
G.12
DCARB
Figure G.1. Scatter plot matrix of soil properties and the distribution coefficient (K d) of
plutonium.
The variable selection with and without an intercept indicated that the 2 most significant variables
for reliably forecasting the K d values were the concentrations of dissolved carbonate (DCARB)
and the clay content (CLAY) of soils (Table G.2). Using these 2 independent variables, several
forms of polynomial regression models and a piecewise regression model with a breakpoint were
generated. The results showed that the best regression model among all the models tested was
the piecewise regression model. The relationship between the K d values and the 2 independent
variables (CLAY and DCARB) is shown as a 3-dimensional surface (Figure G.2). This graph
illustrates that the highest K d values are encountered under conditions of high clay content and
dissolved carbonate concentrations. In contrast, the low K d values are encountered in soils
containing low clay content and low dissolved carbonate concentrations.
Using the piecewise regression model, a look-up table (Table G.3) was created for ranges of clay
content and soluble carbonate values which are typically encountered in soils.
IC
OC
CLAY