5. CONCLUSION
Based on NCRS-CN, this study investigated the spatial distribution of SY
and risk of sediment disaster in typhoon events by using big data
collected during 1999–2009. The relationship between potential maximum
retention and SY was analyzed and applied to simulate the spatial
distribution of the risk of sediment disasters. The results showed that
different cumulated rainfall levels, land use, soil, and slope could all
be essential factors that affect SY. Based on daily river discharge and
SY data, the rating curve (Q–Qs rating curve) of runoff–SY indicated
that the coefficient of determination of the curve was R² = 0.95; thus,
the SY of typhoon events can be estimated using the rating curve.
The analytical results of potential maximum retention and SY showed that
the relationship between the two parameters could be expressed by a
power function. This function could be divided into three categories
according to different cumulative rainfall conditions. If the cumulative
rainfall was less than 197.2 mm, Type I was applicable, and the SY was
0. If the cumulative rainfall was between 197.2 and 754.4 mm, Type II
was applicable, and the corresponding function was SY =
473.64S–0.866. If the cumulative rainfall was between
754.4 and 1419.7 mm, Type III was applicable, and the corresponding
function was SY = 13764S–1.133. The potential maximum
erosion in the catchment area could be estimated using the analytical
results of potential maximum retention and SY.
The management strategy of this study was to take management
subdivisions as a unit and to use the potential maximum erosion and
slope to establish the spatial distribution of sediment disaster risks.
The risks were ranked, and the landslide rate of each subdivision was
estimated. The results indicated that the cumulative number of
subdivision was positively correlated with the landslide rate. In areas
with limited data, the relational curve between the cumulative number of
subdivisions and landslide rate could be used to determine subdivisions
with management priorities. In addition, in the 70% landslide rate
simulation scenario, the spatial distribution of landslides in selected
subdivisions was mostly consistent with actual landslide locations.