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Debris flows are a common natural trigger of disasters in mountainous areas, and check dams are standard structural measures for controlling debris flows. Despite their prevalence in debris flow-prone areas worldwide, the capacity of check dams is still calculated using empirical formulas, which lead to large calculation errors. This paper proposes a new method that uses GIS to calculating the design storage capacity of a check dam in the debris flow-prone Cutou Gully in Wenchuan County, China. Large-scale digital surface models derived from unmanned aerial vehicle imagery and ground surveys identify local topographic changes in the debris flow path and develop appropriate maintenance plans for check dams. The measured storage capacity of the check dam is determined by analyzing the DEM differences. This study uses the newly proposed method to calculate the design storage capacity of the check dam. The accuracy of the calculation results was evaluated using the checkpoint method, and the results showed that the design and measured siltation surface errors ranged from -1.16-2.96 m, with a root mean square error of 0.93 m. The design capacity of the check dam is 33.6× 104 m3, and the actual capacity is 36.7× 104 m3, with an absolute error of 3.1× 104 m3 and relative error of 8.6%. The results prove the validity of the proposed calculation method; moreover, this study shows that the new method is accurate, easy to operate, and highly efficient for visualizing the spatial distribution of the siltation depth behind the check dam. This work will help improve future engineering decisions, design strategies, and find optimal design solutions to minimize the risk of debris flow hazards.

The upper reaches of Min River (The upper Min River) is located in Southwest China with significant mountain settlements, which are vulnerable to frequent geological hazards. Based on a field investigation, collation of yearbook data, and analysis through the use of SPSS statistical software, a vulnerability evaluation index system of geological hazards was devised. According to the actual field situation and the acquired data of the study area in 2006, 2009, and 2015, 16 indicators were selected as settlement vulnerability evaluation indexes of geological hazards. The indexes included population density, building coverage, and economic density. Based on the comprehensive evaluation model of entropy value, the dynamic change in the settlement vulnerability of geological hazards was analyzed. The results showed that population density, building coverage, economic density, and road density were the factors that affected the settlement vulnerability of geological hazards the most—Wenchuan earthquake caused considerable damage to the upper Min River, making the area the most vulnerable in 2009. However, its vulnerability decreased in 2015, which indicated that postearthquake reconstruction achieved significant results. Thus, the vulnerability has emerged as an important indicator reflecting the safety and healthy development of mountain settlements.