Debris Flow Assessment in the Gaizi-Bulunkou Section of Karakoram Highway

Abstract

Highways frequently run through the flow and accumulation areas of debris flow gullies and thus are susceptible to debris flow hazards. Assessing debris flows along highways can provide references for highway planners and debris flow control, emergency management. However, the existing assessment methods mostly neglect the essential information of the flow paths and spreading areas of debris flows at the regional scale. Taking the Gaizi Village-Bulunkou Township Section (hereinafter referred to as “the Gaizi-Bulunkou Section”) of the Karakoram highway as the study area, this research introduces a simple empirical model (the Flow-R model) and establishes a method for assessing the debris flow hazard level. The main processes include data collection, inventory of former events, calculating source areas and spreading probability, verification of the model, extraction of hazard assessment factors, and calculation of debris flow hazard levels. The results show that: 1) the accuracy, sensitivity, and positive predictive power of the Flow-R model in simulating the debris flow spreading probability of the study area were 81.87, 70.80 and 72.70%, respectively. The errors mainly occurred in the debris flow fans. 2) The calculation results make it possible to divide debris flow hazard levels into four levels. N5, N19, and N28 gullies had the highest hazard level during the study period. 3) In the Gaizi-Bulunkou Section of the Karakoram highway, during the study period, the highways with very high, high, medium, and low hazards were 4.33, 0.62, 1.41, and 1.68 km in length, respectively.

Modeling Shallow Landslide Runout Distance in Eocene Flysch Facies Using Empirical–Statistical Models (Western Black Sea Region of Türkiye)

“…Flow-R, a distributed empirical model, was implemented with great success not only in this study but also in many studies in the literature. Giano et al [2], Polat and Erik [60], Charbel and El Hage Hassan [50], and Jiang et al [51] discussed whether Flow-R and observed landslide runout results are compatible. The researchers concluded that Flow-R results are well matched with the observed results.…”

“…Back-calculated debris flow velocities were observed in the range of 5 to 15 m/s in a study by Prochaska et al [106]. Similarly, different researchers considered different velocity values in the literature, e.g., 5 m/s [49], 10 m/s [37], 15 m/s [42,47,54], 16 m/s [107], 20 m/s [46], and 25 m/s [51]. By considering both back analyses and the local information obtained by residents having memorials related to the shallow landslides that occurred in May 1998 in this region, it was concluded that the velocity parameter could be set as 15 m/s for shallow landslides in the Eocene flysch facies.…”

“…The value of x is equal to 4 for debris flows, while it can be set as 22 to 26 for shallow landslides [105]. The value of x has also been set as 4 for debris flows in recent studies [37,47,51,61]. In this study, comparative analyses were performed depending on whether failures occurred as debris flows or shallow landslides.…”

“…The multiple flow direction [40], Holmgren [41], modified Holmgren [42], cellular automata [43], and random walk [44,45] models provide opportunities to simulate possible runout paths. A combination of the empirical-statistical simplified friction-limited model (SFLM), which considers the reach angle, and flow direction algorithms, enables us to observe details such as feasible runout distances and paths using Flow-R software [42], as shown in recent studies [39,[46][47][48][49][50][51][52][53][54]. Owing to the development of computer technology, recent studies on landslide runout distance prepared with software go well beyond the conventional techniques.…”

“…Flow-R software, which was developed at the University of Lausanne [42], was used to empirically examine shallow landslide runout scenarios in this study. This software offers researchers the opportunity to try a variety of landslide runout simulations [39,[46][47][48][49][50][51][52][53][54][60][61][62][63] to obtain runout distances by considering different parameter configurations. Table 1 provides a summary of previous Flow-R studies.…”