**4. Discussion**

1.6% of total 1357 cross sections. Most of the river widths show widening adjustment after the typhoon disturbance. Here we focused on the widening adjustment of the 1335 cross sections for the Cishan River in 2009. Also, we characterized the noncumulative frequency-widening relations to clarify whether the river widening has a SOC phenomenon. The noncumulative

where *Rw* is the magnitude of river widening, the *p*(*Rw*) is a PDF (probability density function)

and *Rw* + △*Rw* and the *RwT* is the total number of river cross section widening. The constants *α* and *β* are obtained from fitting medium and large river widening in order to detect the right heavy tailed decay of PDF through a power-law. We increase our bin width △*Rw* with increasing area *Rw*, so that bin widths are approximately equal in logarithmic coordinates. **Figure 19** shows that river widening having *Rw* larger than 64 m could be well interpreted by

Of particular interest, the *β* value for river widening is greater than that for landslides driven by the same external trigger, i.e., Typhoon Morakot, suggesting that the occurrence likelihood of large magnitude of river widening is smaller than that of large landslides in the CRW for the perspective of environmental risks. Also, typhoon-induced river widening could have self-organized criticality. However, the *β* values in (10) are very limited on the basis of worldwide observations and are not like the *β* values in (2) for landslides that can be obtained

**Figure 19.** Noncumulative frequency distribution of river width widening after Typhoon Morakot for the Cishan River.

Above the cutoff of 64 m, the river width widening satisfies a power-law relation with exponent β = 1.93.

, and the △*Nw* is the number of cross sections with widening between *Rw*

<sup>−</sup>*<sup>β</sup>* (10)

frequency distribution of river widening can be mathematically expressed as

*p*(*Rw*) = *αRw*

a power-law statistic with *α* = 25.6 and *β* = 1.93 with *r*<sup>2</sup> = 0.98.

equivalent to \_\_\_1

36 Environmental Risks

*Nw* <sup>Δ</sup> *<sup>N</sup>* \_\_\_\_*<sup>w</sup>* Δ *Rw*

In this chapter, we characterize landslides triggered by Typhoon Morakot in 2009, and its corresponding frequency-area distribution. Results show that the exponent value of a noncumulative relation for these landslides approximates the lowest limitation of worldwide observation. This infers that the hillslopes of the CRW has high potentials on landslide triggering. Meanwhile, ambient sediment materials produced by landslides could deposit on hillslopes and river channels and cause the adjustments of hillslope and fluvial systems, which can be observed from raised river-borne suspended-sediment concentration in the Cishan River (i.e., rich-supply hillslopes) and its decreased stream power (severe sedimentation in river channels). These patterns indicate that landslides not only pose threats to people's life and properties, but also have significant influence on the downstream. Hence, long-term and short-term strategies for landslide countermeasures are both necessary. The long-term strategies are the comprehensive management and regulation of basins and watersheds. The shortterm strategies are the development of real-time warning systems for landslide triggering on hillslopes. In Taiwan, the present real-time warning system developed for landslide hazards are described as follow.

### **4.1. Landslide warning system adopted by the Taiwan's government**

Before hit by this typhoon storms, the Central Geological survey, MOEA (2009) in Taiwan has used logistic equation to estimate landslide ratios via the potential values obtained from the combination of 100-year return period hourly rainfall depth and cumulative daily rainfall to map the landslide susceptibility. On the basis of this susceptibility, Taiwan's hillslopes were categorized in three regions of high risk, medium risk and low risk. Comparing with the location and initiation time in situ of landslides or rock avalanching (total of 909; provided by Soil and Water Conservation Bureau and Central Geologic Survey) show that these geomorphic erosion processes crop out the regions of high risk ~43% of totals. 90% of total can be observed when we consider both of high risk and medium risk regions. However, although the construction of landslide susceptibility can provide some useful information on mapping landslide-prone areas, the effect of real-time rainfall during typhoon storms should be necessary for landslide warning, still. Considering only landslide-prone area could also lead to the over-issued orders of hazard mitigation from landslide warning and also the wasting of governmental administrative resources.

Rainfall brought by typhoon storms plays a majorly important role in triggering landslides on hillslopes. Typically, some topographic and geologic regimes could provide suitable conditions for landslide triggering but landslides are still needed to be initiated by external triggers such as rain infiltration and its consequent saturation. The evolution of soil pore pressure can be mainly influenced by these triggers, leading to the change of normal and shear stresses for a soil profile, further reducing slope failure [36, 37]. Many researchers have investigated landslide and debris flow triggering in response to different rainfall parameters [18, 38–40, 42, 43], showing that different rainfall characteristics can affect the initiation of debris flows and landslides from place to place. The precise relationship between landslides and rainfall parameters remains unclear, leading to the need of studies on the characteristics of rainfalltriggered landslides on hillsides in different regions [18].

mitigation and the above mentioned works, Jan [41] has proposed a rainfall-threshold index

*LRTI* = I¯<sup>3</sup> × Rt (11)

evaluating landslide triggering, the Weibull distribution was used to estimate the values of *LRTI* for the cumulative frequencies at 70% and 90%, respectively, for total rainfall events. During typhoon storms, if its corresponding *LRTI* is greater than the value for the cumulative frequency at 70% (denoted by *LRTI*70), the landslide warning system would issue 'yellow' warning; if the *LRTI* value is greater than the value for the cumulative frequency at 90% (denoted by *LRTI*90), the landslide warning system would issue 'red' warning, as reported by Jan [41]. On the basis of those two LRTI values (at 70 and 90% of cumulative frequency), the operation of landslide warning issuance is suggested follow-

• Level 2 warning would be released when the values of real rainfall data gauging is higher

• Level 1 warning would be released when the values of real rainfall data gauging during a

• Level 1 warning would be reduced to Level 2 when the values of real rainfall data gauging

• Level 2 warning would be left when the values of real rainfall data gauging during a 3-hour

This rainfall-induced, shallow landslide warning system is used to provide information on the decision making of landslide hazard mitigation for Soil and Water Conservation Bureau

Severe typhoon storms and the consequent landslide hazards on hillslopes have frequently posed threats to economic implementation whose impacts on the wealth and property may exhaust the available resources to deal with the aftermath of those disasters. In Taiwan, the countermeasures of debris flow have been well developed in recent 20 years, gradually. However, the development of shallow landslide mitigation measures and warning systems are still limited and should be emergent in the future. Moreover, it must need to strengthen public awareness of landslide hazards, educating people on how to respond to landslide hazards on hillsides, especially during rainy seasons. Meanwhile, more research on landslide mechanics, warning system, and its corresponding rationale prediction and assessment

is the 3-hour average rainfall intensity. To establish rainfall threshold for

is the effective accumulative

39

Landslides Triggered by Typhoon Morakot in Taiwan http://dx.doi.org/10.5772/intechopen.76930

for landslide mitigation as follow:

rainfall, and I¯<sup>3</sup>

ing the criterion as

than *LRTI*70.

of Taiwan.

**5. Conclusions**

methods are necessary.

where *LRTI* is the landslide rainfall triggering index, Rt

3-hour period is simultaneously higher than *LRTI*70.

period is simultaneously lower than *LRTI*70.

during a 3-hour period is simultaneously lower than *LRTI*70.

To analyze the relationships of landslide triggering with respect to rainfall characteristics, Jan [41] collected 15 landslide inventories for different periods, comparing with its corresponding different rainfall parameters that include 3-hour average rainfall intensity *I* 3 , 6-hour average rainfall intensity *I* 6 , 12-hour average rainfall intensity *I* 12 and 24-hour average rainfall intensity *I* 24, obtained from the records of near rainfall stations. Results indicate that the strongest correlation is between landslide occurrence and 3-hour average rainfall intensity based on logistic regression analysis, with determined coefficient *r*<sup>2</sup> equivalent to 0.679. In other words, **Figure 20** shows the relationships between different average rainfall intensities (i.e., *I* 3 , *I* 6 , *I* 12 and *I* 24) and accumulative rainfall amount calculated from hourly rainfall data recorded by the Shinfa gauge. Red dots represent landslides occurred in that rainfall event and triangles represent no landslides occurred in that rainfall event (see **Figure 20**). These patterns suggest that *I 3* can be recognized as a suitable indicator to the warning of rainfall-induced, shallow landslide [41].

In Taiwan, the rainfall-threshold warning system is well constructed for debris flow mitigation. Referring the rainfall parameter considered in the warning system for debris flow

**Figure 20.** Effective accumulative rainfall (R<sup>t</sup> ) against 3-hour average rainfall intensity (I ¯ <sup>3</sup> ) illustrated from hourly rainfall data recorded by Shinfa gauge.

mitigation and the above mentioned works, Jan [41] has proposed a rainfall-threshold index for landslide mitigation as follow:

$$LRTI = \overline{\mathbf{I}}\_{\mathfrak{z}} \times \mathbf{R}\_{\mathfrak{t}} \tag{11}$$

where *LRTI* is the landslide rainfall triggering index, Rt is the effective accumulative rainfall, and I¯<sup>3</sup> is the 3-hour average rainfall intensity. To establish rainfall threshold for evaluating landslide triggering, the Weibull distribution was used to estimate the values of *LRTI* for the cumulative frequencies at 70% and 90%, respectively, for total rainfall events. During typhoon storms, if its corresponding *LRTI* is greater than the value for the cumulative frequency at 70% (denoted by *LRTI*70), the landslide warning system would issue 'yellow' warning; if the *LRTI* value is greater than the value for the cumulative frequency at 90% (denoted by *LRTI*90), the landslide warning system would issue 'red' warning, as reported by Jan [41]. On the basis of those two LRTI values (at 70 and 90% of cumulative frequency), the operation of landslide warning issuance is suggested following the criterion as


This rainfall-induced, shallow landslide warning system is used to provide information on the decision making of landslide hazard mitigation for Soil and Water Conservation Bureau of Taiwan.

## **5. Conclusions**

be mainly influenced by these triggers, leading to the change of normal and shear stresses for a soil profile, further reducing slope failure [36, 37]. Many researchers have investigated landslide and debris flow triggering in response to different rainfall parameters [18, 38–40, 42, 43], showing that different rainfall characteristics can affect the initiation of debris flows and landslides from place to place. The precise relationship between landslides and rainfall parameters remains unclear, leading to the need of studies on the characteristics of rainfall-

To analyze the relationships of landslide triggering with respect to rainfall characteristics, Jan [41] collected 15 landslide inventories for different periods, comparing with its corresponding

24, obtained from the records of near rainfall stations. Results indicate that the strongest correlation is between landslide occurrence and 3-hour average rainfall intensity based on logistic

accumulative rainfall amount calculated from hourly rainfall data recorded by the Shinfa gauge. Red dots represent landslides occurred in that rainfall event and triangles represent no

landslides occurred in that rainfall event (see **Figure 20**). These patterns suggest that *I*

recognized as a suitable indicator to the warning of rainfall-induced, shallow landslide [41].

In Taiwan, the rainfall-threshold warning system is well constructed for debris flow mitigation. Referring the rainfall parameter considered in the warning system for debris flow

) against 3-hour average rainfall intensity (I ¯ <sup>3</sup>

3

12 and 24-hour average rainfall intensity

3 , *I* 6 , *I* 12 and *I*

equivalent to 0.679. In other words, **Figure 20**

, 6-hour average

*3* can be

) illustrated from hourly

24) and

different rainfall parameters that include 3-hour average rainfall intensity *I*

, 12-hour average rainfall intensity *I*

shows the relationships between different average rainfall intensities (i.e., *I*

triggered landslides on hillsides in different regions [18].

rainfall intensity *I*

38 Environmental Risks

*I*

6

**Figure 20.** Effective accumulative rainfall (R<sup>t</sup>

rainfall data recorded by Shinfa gauge.

regression analysis, with determined coefficient *r*<sup>2</sup>

Severe typhoon storms and the consequent landslide hazards on hillslopes have frequently posed threats to economic implementation whose impacts on the wealth and property may exhaust the available resources to deal with the aftermath of those disasters. In Taiwan, the countermeasures of debris flow have been well developed in recent 20 years, gradually. However, the development of shallow landslide mitigation measures and warning systems are still limited and should be emergent in the future. Moreover, it must need to strengthen public awareness of landslide hazards, educating people on how to respond to landslide hazards on hillsides, especially during rainy seasons. Meanwhile, more research on landslide mechanics, warning system, and its corresponding rationale prediction and assessment methods are necessary.

Occurrence of landslides on hillslopes is not only a real challenge of natural hazard mitigation, but also river channel management. As we above mentioned, ambient Typhoon Morakot had led to significant sedimentation in the Cishan River and the dredging of river channels therefore becomes an important issue after the typhoon disturbance on landscapes. Landslide triggering can simultaneously influence the evolution of hillslope and fluvial systems, leading to its regulation should be integrated and consistent. Hence, Compound-disaster perspective and its domino effect on each disaster are necessary to be considered in the development of landslide countermeasures. In addition, for disaster evaluation in the case of emergency, satellite images, aerial photography and field survey immediate after typhoon storms are necessary to construct high resolution digital topography models that can be used in the aftermath analysis and modeling. Also, more fruitful research on the understanding of landslide mechanics, from which we can develop appropriate design codes in building and installing sediment-control structures, are pressingly needed in Taiwan.

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