5.1. The effect of rainfall duration
Rainfall characteristics are the driving force for runoff generation,
and different rainfall regimes could result in different runoff
generation capacities for individual plot.
The 148 rainfall events of the six plots in the two watersheds (XDG and
CBG) were divided into three groups using K-means clustering (Hong,
2003) based upon rainfall depth and duration to test the performance of
SCS-CN method for different types of rainfall regimes (Table 4). The
classification met the ANOVA criterion for a significant level (***P
< 0.001) Rainfall regime 1 is the group of rainfall events
with strong intensity, short duration and lower precipitation, which had
the largest occurring frequency, occupying 79.73% of the total events;
Rainfall Regime 3 consists of rainfall events with low intensity, long
duration and infrequent occurrence (3.38%), while Rainfall Regime 2 is
composed of rainfall events, which have moderate rainfall eigenvalues,
i.e., lower precipitation and shorter duration than Rainfall Regime 3,
but higher precipitation and longer duration than Rainfall Regime 1. In
general, The mean P and D decreased in the following order: Rainfall
Regime 3 >Rainfall Regime 2 >Rainfall Regime
1. This classification of rainfall regimes is consistence with Wei et
al. (2007) and Fang et al.(2008), which also classified the rainfall
into three rainfall regimes with 14 and 9 years of field measurements on
the Loess Plateau, respectively.
Figure 6 shows the predicted runoff values plotted against the
corresponding measurement values for the three rainfall regimes. The
original SCS-CN method under-predicted most storm-runoff events of the
Rainfall Regime 1 and over-predicted the events of Rainfall Regime 3,
while the Rainfall Regime 2 seems preformed better than Rainfall Regime
1 and 3, but the points of Rainfall Regime 2 still lie scatter to 1:1
line (Fig. 6a). This is because the SCS-CN method only account for the
rainfall amount but ignore the storm duration. The runoff predicted by
the conventional SCS-CN method were increased as the rainfall amount
increased from Rainfall Regime 1 to 3, while the storm duration from
Rainfall Regime 1 to 3 is also increased thereby the measured runoff did
not increase with rainfall amount monotonously, which finally made the
SCS-CN method perform poorly. However, when incorporating the storm
duration in the proposed method with Eq.8, under-prediction of the
Rainfall Regime 1 and over-prediction of Rainfall Regime 3 were removed
and also improved the performance of predicting Rainfall Regime 2 with
most of the data points lie close to 1:1 as compared with the
traditional SCS-CN method (Fig. 6b). The better performance indicated
the storm duration plays a significant role in rainfall-runoff
production and estimation, and the proposed method can account for
different type of rainfall regime with varying duration. Other also
confirmed that storm duration plays a vital role in both runoff
generation and prediction (Fang et al., 2008; Mishra et al., 2008b;
Reaney et al., 2010)