Mean slope, precipitation seasonality, and mean elevation were also
significantly correlated with the deviation between the topographic and
effective areas of the Brazilian catchments (Figure 5, the other
influencing factors based on RFA are available in Supplement S3). Our
ECI results were positively correlated with mean slope and did not vary
with decreasing slope contrasting the results of Liu et al.(2020), who observed positive and negative ECI in lower slope degrees.
On the contrary, a clear pattern shows a tendency of flat areas to lose
water (Aeff < Atopo) and hilly
areas to gain water (Aeff >
Atopo). The ECI variability decreased with increasing
elevation, showing that elevated areas tend to gain water
(Aeff > Atopo).
Furthermore, the catchments with summer precipitation (P seasonality
close to +1, Figure 5c) are prone to have effective areas larger than
their corresponding topographic areas. We found positive ECI in areas
with a well-defined precipitation seasonality, mainly in the Cerrado and
Atlantic Forest biomes, while the northeast region — Caatinga biome
— endures long drought spells leading to an unbalanced timing between
temperature seasonal dynamics, seasonality close to 0 (negative ECI). We
provide further detail about the relationship between those most
influencing attributes and ECI in section 4.1 (i.e., aridity index, mean
slope, mean elevation, and precipitation seasonality).
It is important to mention that, besides the four most relevant
attributes, WTD and HAND also explain the variance in the attribute’s
dataset according to PCA (variance-based test). A significant non-linear
correlation (Spearman’s p-value < 0.05) corroborates the
results from PCA (Figure 5e and f). Nevertheless, they showed less
influence on the ECI than the previously mentioned attributes after the
RFA (Supplement S3). The fact that HAND is closely related to slope and
mean elevation may have contributed to its lower score after the machine
learning process in the RFA.