2.4 Statistical analysis
The geomorphic parameters (HL , A , Pe , andHDC ) and indices (CC , FF , RR , LR , andHI ) of the catchments were grouped according to the Rift margin
and Valley floor derivations. Normality of each geomorphic parameter and
index in each group was tested with the Kolmogorov-Smirnov test (α =
0.05) and the Shapiro-Wilk test (α = 0.05), and homogeneity of variance
was tested with the Levene test (α = 0.05). For the parameters and
indices that were tested for normality and homogeneity of variance, a
t-test was applied to detect differences in the mean values between the
two groups; otherwise, a non-parametric test was applied.
Least square regression analysis was applied for log-transformeds (slope of the gully head) and a (upslope drainage area)
to draw the threshold line that represented the gully topographical
thresholds at each of the 12 main study gullies on a double logarithmic
chart. Based on the appearance of the 12 threshold lines, hypotheses
were made, and the topographical threshold of gully heads were
categorised into different subgroups, e.g., periods of gully head
incision or land use items around gully heads. Analysis of covariance
(ANCOVA) was made to find there were significant differences (α = 0.05)
in the mean values of the dependent variable (s or a )
between the different subgroups (controlled independent variable, or
factor) while taking into account the influence of the uncontrolled
independent variable (a or s as a covariate). ANCOVA
assumes that: (i) the dependent variables are normally distributed, and
those variances are equal overall subpopulations; (ii) the interaction
between the factor and covariate are negligible; (iii) a linear
relationship between the covariate and dependent variable. In the
analysis, these assumptions were tested, and post hoc tests were made
using the Bonferroni correction method to find the subgroups that had
significant differences in the mean values. SPSS ver. 20 (IBM) was used
for the statistical analyses.
RESULTS