  In the analytic hierarchy process (AHP) based flood risk estimation models,
it is widely acknowledged that different weighting criteria can lead to
different results. In this study, we evaluated and discussed the sensitivity of
flood risk estimation brought by judgment matrix definition by investigating
the performance of pixel-based and sub-watershed-based AHP models. Taking a
flood event that occurred in July 2020 in Chaohu basin, Anhui province, China,
as a study case, we used the flood areas extracted from remote sensing images
to construct ground truth for validation purposes. The results suggest that the
performance of the pixel-based AHP model fluctuates intensively given different
definitions of judgment matrixes, while the performance of sub-watershed-based
AHP models fluctuates considerably less than that of the pixel-based AHP model.
Specifically, sub-watershed delimitated via multiple flow direction (MFD)
always achieves increases in the correct ratio and the fit ratio by >35% and
>5% with the pixel-based AHP model, respectively.
