Figure S1. The prediction of HCC of the FXW-M3 model on
different values of ha for different soil types
(a) R2 . (b) RMSE .
Figure S1 shows the impact of different values ofha on the performance of the HCC estimation with
the FXW-M3 model. Including the impact of soil structure (with non-zeroha ) does improve the estimation of HCC,
represented by a higher value of R2 and a lower
value of RMSElog10 (K ).
Compared to the original FXW-M2 model, the FXW-M3 model substantially
increases the value of R2 and reduces the value
of RMSElog10 (K ) for
especially sand, sandy loam, loam and silt loam soils. When it comes to
silty clay and clay soils, only slightly improvement is achieved.
The optimized value of ha varies for the
different soil types of the validated 152 soil samples. For sand, sandy
loam and loam soils, the optimized value of ha is
in the range from about −50 cm to −30 cm. Silt loam has a slightly
higher optimized value of about −17cm. When it comes to silty clay and
clay soils, ha has a much higher optimized value
close to −5 cm. However, it should keep in mind that both the silty clay
and clay soil types have a small number of soil samples. For all the 152
soil samples, the optimized ha is about −28 cm.
This value is further applied in predicting the HCC for all soil samples
as shown in section 4 in the main text.
Table S1 . The optimized and fixed parameters of different model
settings. The number in the bracket demonstrates the lower and upper
boundary of the optimized parameters.