Heavy downpours on Sunday evening brought flooding and landslides to more than half of Chiayi County, blocking many key roadways. Areas including Jhongpu (中埔), Singang (新港), Minsyong (民雄), Jhuci (竹崎) and Fanlu (番路) townships had more than 200mm of rain on Sunday evening. Firefighters rescued 32 people near the Jhonghe Exchange along Provincial Highway No. 82 in Shueishang Township (水上).
However, damage and several deaths have led the public to accuse the government of failing to issue an advance warning. In the face of the public’s grievances, the government probably feels that its hands were tied, as mudslides are difficult to predict, even with the most modern technology.
This does not mean that landslides are beyond human control. The Landslide Susceptibility Index (LSI) was adopted to map and evaluate landslide susceptibility and to classify areas into five susceptibility zones: “very low,” “low,” “moderate,” “high” and “very high.” As mudslides are caused by a combination of factors, such as soil properties, geology, and soil and water conservation, prediction is a great challenge. The recent unexpected landslide in Jhuci is one such example. On Aug. 4, Nantou County’s Renai Township (仁愛) also experienced a major mudslide.
Nevertheless, prediction is still possible, as precipitation monitoring provides a certain degree of reliability. Hourly, daily and accumulated precipitation data are an important index for landslides. Once precipitation reaches a certain level in mountainous regions, the government should launch evacuation operations as a precaution. To better predict landslides, the following three factors could play a decisive role in the accuracy of predictions:
The first is widespread public awareness and education. Landslide incidents have shown that people’s disaster awareness, sensitivity and preparedness play a huge role in reducing loss of life, personal injury and damage from natural disasters. Precipitation monitoring provides officials and the public with the easiest index for predicting landslides and floods. The Agency of Rural Development and Soil and Water Conservation provides landslide-prone areas with rain gauges so that communities can monitor rainfall and take corresponding action.
Second, education and training are crucial in landslide predictions. While reading weather and precipitation data require professional training, the public should be taught basic knowledge and skills on the subject. This education should be coupled with the government’s disaster-resistant community policy promotion so that the public and community can have systematic learning and a higher awareness of disaster prevention and reduction.
Third, communities should form stronger ties with authorities. As the authorities are responsible for issuing warnings in landslide-prone areas, when the public has close connections with the authorities, they can ask for help to read the data and increase prediction accuracy.
According to my experience, the more proactive the community is, the more help they can get from the authorities in the event of disasters.
Even though landslides are difficult to predict, there are still some clues to follow for preliminary assessments, but these have to be built upon after the implementation of the three aforementioned factors.
Yang Yung-nane is a political science professor at National Cheng Kung University and a member of the board of directors of Transparency International Chinese Taipei.
Translated by Rita Wang
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