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Typhoons are recurring meteorological phenomena in the southeastern coastal area of China, frequently triggering debris flows and other forms of slope failures that result in significant economic damage and loss of life in densely populated and economically active regions. Accurate prediction of typhoon-triggered debris flows and identification of high-risk zones are imperative for effective risk management. Surprisingly, little attention has been devoted to the construction of physical vulnerability curves in typhoon-affected areas, as a basis for risk assessment. To address this deficiency, this paper presents a quantitative method for developing physical vulnerability curves for buildings by modeling debris flow intensity and building damage characteristics. In this study, we selected the Wangzhuangwu watershed, in Zhejiang Province of China, which was impacted by a debris flow induced by Typhoon Lekima on August 10, 2019. We conducted detailed field surveys after interpreting remote sensing imagery to analyze the geological features and the mechanism of the debris flow and constructed a comprehensive database of building damage characteristics. To model the 2019 debris flow initiation, entrainment, and deposition processes, we applied the Soil Conservation Service-Curve Number (SCS-CN) approach and a two-dimensional debris flow model (FLO-2D). The reconstructed debris flow depth and extent were validated using observed debris flow data. We generated physical vulnerability curves for different types of building structures, taking into account both the degree of building damage and the modeled debris flow intensity, including flow depth and impact pressure. Based on calibrated rheological parameters, we modeled the potential intensity of future debris flows while considering various recurrence frequencies of triggering rainfall events. Subsequently, we calculated the vulnerability index and economic risk associated with buildings for different frequencies of debris flow events, employing diverse vulnerability functions that factored in uncertainty in both intensity indicators and building structures. We observed that the vulnerability function utilizing impact pressure as the intensity indicator tends to be more conservative than the one employing flow depth as a parameter. This comprehensive approach efficiently generated physical vulnerability curves and a debris flow risk map, providing valuable insights for effective disaster prevention in areas prone to debris flows. [ABSTRACT FROM AUTHOR]

Mitigation works are very essential for mitigation of debris-flow hazards in mountainous areas. Usually, it is difficult to assess the effectiveness of existing mitigation works in a catchment. This paper presented a method for quantitative assessment of debris flow mitigation measures by using Kanako system, a user-friendly GUI-equipped debris flow simulator that allows good visualization and easy interpretation. Kanako 2D (Ver. 2.04) was applied to a case study at Caijia Gully, Sichuan Province, China. Mitigation works including check dams, drainage channel, and deposition basin were constructed in the gully in 2001 and 2006. Kanako 2D can simulate debris flow from steep area to alluvial fan. 1D simulation was applied for assessing the effect of the check dams at the lower part of the gully, and 2D simulation was applied for the effect of the drainage channel and deposition basin on the alluvial fan. The simulation results indicate that debris flow will cause great damage to residential area on the alluvial fan if mitigation measures were not implemented in the gully. For old dams which have been filled up with deposits of previous debris flows, the results show that they still have the function for controlling debris flow due to the gradient reduction of the channel bed in front of the dams by the trapped debris flow deposition. After the comprehensive control of debris flow including trapping, drainage, and deposition in the gully, the simulation results indicate that the risk on the alluvial fan can be reduced to an acceptable level. [ABSTRACT FROM AUTHOR]