Title

坡地降雨致災熱區警戒模式

Translated Titles

Warning Model for Predicting the Risk Zones of Rainfall-Induced Slopeland Disasters

DOI

10.29417/JCSWC.201903_50(1).0001

Authors

陳振宇(Chen-Yu Chen);陳均維(Jyun-Wei Chen);陳國威(Kuo-Wei Chen);林詠喬(Yung-Chiau Lin)

Key Words

災害 ; 脆弱度 ; 危害度 ; 崩塌 ; 預警系統 ; Disaster ; fragility ; hazard ; landslide ; warning system

PublicationName

中華水土保持學報

Volume or Term/Year and Month of Publication

50卷1期(2019 / 03 / 01)

Page #

1 - 10

Content Language

繁體中文

Chinese Abstract

儘管降雨誘發的坡地災害與該地區之地質、地形、植生等條件有關,但多數警戒模式僅針對降雨指標進行量化。例如,現行國內的RTI土石流警戒雨量模式及日本的RBFN土砂災害雨量警戒模式,雖已藉由調整不同警戒雨量以表現各地區之地文地質等條件差異,但仍未有一套明確的量化評估方式可表達各地區之地文脆弱度。本研究採用QPESUMS雷達降雨網格資料之歷史相對雨量值,以及各網格範圍內歷年新增崩塌地之發生頻率及規模,提出降雨危害度指標(H_R)與地文脆弱度指標(F_P),並以此二指標建立颱風豪雨期間各QPE網格內之坡地降雨致災風險等級(R_h)。以高雄市六龜區2005-2017年之降雨事件為例,本研究建立之警戒模式可有效預測新生崩塌發生之時間及區域,並以視覺化方式展示可能的坡地降雨致災熱區。

English Abstract

Slopeland disasters triggered by rainfall are related to geology, topography, and vegetation conditions; however, most warning models are only quantified for rainfall indicators. For example, although the current debris flow warning model in Taiwan and the sediment-related disaster warning model in Japan employ different critical lines, indicating the differences in the geology and terrain of the two regions, these models do not comprise a defined set of quantitative assessment methods for expressing the physiographic fragility of each region. In this study, we used historical relative rainfall data from QPESUMS to define a rainfall hazard index (H_R) and adopted the frequency and scale of new collapses in each QPESUMS mesh to determine a physiographic fragility index (F_P). Then, we integrated these two indicators to obtain the risk level of rainfall-induced hazard (R_h) for each QPESUMS mesh during a typhoon or heavy rainfall. Finally, we considered rainfall events from 2005 through 2017 in Liougui District of Kaohsiung City as an example. The results indicate that the warning model can predict the occurrence and location of new collapses and also display the risk zones of rainfall-induced slopeland disasters through a visualization platform.

Topic Category 生物農學 > 農業
生物農學 > 森林
生物農學 > 畜牧
生物農學 > 漁業
生物農學 > 生物環境與多樣性
工程學 > 土木與建築工程
工程學 > 市政與環境工程