雷達資料同化技術之極短期定量降雨預報於淺層崩塌預警應用研究

Application of Very Short-term Quantitative Precipitation Forecast with Radar Data Assimilation Method for Shallow Landslide Prediction

10.6937/TWC.201906_67(2).0002

何瑞益(JUI-YI HO)；林郁峰(YU-FENG LIN)；林忠義(CHUNG-YI LIN)；黃琇蔓(XIU-MAN HUANG)；蕭玲鳳(LING-FENG HSIAO)；李光敦(KWAN TUN LEE)

雷達資料同化技術 ； 極短期降雨預報 ； 崩塌預警 ； 飽和水位變化 ； Radar data assimilation method ； Very short-term rainfall forecast ； Landslide warning system ； Changes in saturated water levels

台灣水利

67卷2期（2019 / 06 / 01）

9 - 20

繁體中文

台灣地區因特殊地形、地質與水文條件易於誘發山坡地坍塌，於颱風豪雨侵襲期間，往往造成崩塌等坡地災害的發生。欲有效降低颱風與豪雨所帶來的坡地災害損失，除必要的工程方法外，亦須配合適當的災害預警和應變措施，於災前掌握颱風與豪雨動態，因此準確的降雨預報和淺層崩塌模式，乃是坡地崩塌預警減災的重要環節。本研究分別採用雷達資料同化技術與系集平均降雨預報資料，以提供未來6小時極短期降雨預報；且以地形性水文模式與無限邊坡穩定分析理論為基礎，建置SIMTOP模式（Shallow Landslide Prediction Based on Infinite Slope Model and TOPMODEL），此模式不僅可考量集水區地文特性，並能分析降雨強度對於飽和水位之變化，藉此計算集水區中邊坡安全係數，以判斷未來6小時淺層崩塌災害可能發生的時間。本研究選用新北市烏來區台9甲線10.2K上邊坡集水區與6場重大颱洪事件進行模式測試，逐時進行1至6小時之淺層崩塌預警分析，同時採用可偵測率、誤報率、預兆得分以及正確率，以評估兩種降雨預報分別結合SIMTOP模式之淺層崩塌預警能力。研究結果顯示，雷達資料同化技術之未來6小時降雨預報結合SIMTOP模式較系集降雨預報表現較佳，相關研究成果可提供相關單位作為災害應變之參考依據，以保障民眾生命財產的安全。

Taiwan is prone to hillslope disasters in mountain areas because of its special topographical, geological, and hydrological conditions. During typhoons and rainstorms, severe shallow landslides frequently occur. To mitigate the impact of shallow landslides, not only the structural measures are necessary, but also adequate warning systems and contingency measures must be executed. Hence, precise precipitation forecasts and landslide prediction are the most important measures in practice. To account for inherent weather uncertainties precipitation forecasts based on quantitative precipitation forecast model with radar data assimilation method and ensemble mean prediction were adopted in this project instead of using a single model output. The SIMTOP model based on infinite-slope model and TOPMODEL was developed. In considering detail topographic characteristics of the subcatchments, the proposed model can estimate the variation of saturated water level during rainstorms, and then link with the slope instability analysis to clarify whether shallow landslides would occur in the subcatchment. The subcatchment on 10.2 K of No. 9A Highway was selected as the test site for landslide predictions with lead time of 6 hours. Hydrological data and landslide observed records from 6 typhoons events were used to verify the applicability of the proposed model. Four indexes including the probability of detection (POD), false alarm ratio (FAR), threat score (TS), and accuracy (ACC) were adopted to assess the performance of two kinds of very short-term rainfall forecasts with SIMTOP model. The results indicate that quantitative precipitation forecast model with radar data assimilation with SIMTOP model was better than ensemble rainfall forecasts with SIMTOP model. It is promising to apply the proposed model for landslide early warnings to reduce the magnitude of the loss of lives and properties.

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