The initial of debris flow can be classified into two types based on their triggering positions, that is, debris flow from slope and debris flow from gully or channel. For the former, great progress has been achieved on the mechanisms of soil failure and liquefaction. The framework established by a series of theories or laws, such as the Mohr–Coulomb criteria, the unsaturated soil mechanics, and the critical state of soil mass, has been used widely in industry and research. However, the details and discrimination basis for the transformation process from landslide into debris flow still need to be further clarified. Relatively, debris flow from gully or channel is more complex due to its various mass sources and the diversity of processes. Nevertheless, through a great number of case studies and experimental statistics, people have gradually recognized the influential rule and critical condition of factors from landform, hydrology, and other aspects on debris flow initiation. Furthermore, based on the theories of granular flow, continuum mechanics, and rheological law, some typical event-based scenarios can also be reproduced by different single-/two-phase depth integral/average numerical models. However, some key knowledge on mechanism and application level is still insufficient, such as the erosion and entrainment mechanism of materials from different sources, the boundary tractions and materials exchange, as well as the selection of prediction indicators. Three current discriminated methodologies for debris flow initiation, that is, the safety factor method, the rainfall indicator method, and the comprehensive assessment method, were summarized in this article. Considering the technical limitation of each methodology, it is believed that the establishment or improvement of a unified, stable, and open-access database system for event registration and query, as well as the development of large-scale and high-precision rainfall monitoring, is still regarded as the important aspect of debris flow prevention in the future. In addition, as an economic and efficiency means for obtaining information on potential threats and real-time hazard messages, the multielement method for debris flow is recommended as a long-term reference.

Using data sourced from 15 periglacial debris flow gullies in the Parlung Zangbo Basin of southeast Tibet, the importance of 26 potential indicators to the development of debris flows was analyzed quantitatively. Three machine learning approaches combined with the borderline resampling technique were introduced for predicting debris flow occurrences, and several scenarios were tested and compared. The results indicated that temperature and precipitation, as well as vegetation coverage, were closely related to the development of periglacial debris flow in the study area. Based on seven selected indicators, the Random Forest-based model, with its weighted recall rate and Area Under the ROC Curve (AUC) greater than 0.76 and 0.77, respectively, performed the best in predicting debris flow events. Scenario tests indicated that the resampling was necessary to the improvement of model performance in the context of data scarcity. The new understandings obtained may enrich existing knowledge of the effects of main factors on periglacial debris flow development, and the modeling method could be promoted as a prediction scheme of regional precipitation-related debris flow for further research.

Based on the large-scale field conceptual solid model experiments of artificial torrents and water-rock flows, this paper studied the changes of flooding areas and cross-sections morphology of river channel in different bedload transport rates, and the results showed that:1) there is a critical point in bedload transport rate between the bedload transport levels and flooding areas, before the rate reaches the critical point, the more the bedload transport rates, the larger the flooding area; but when the rate reaches the point, the more the bedload transport rates, the smaller the flooding area. 2) The great amount of bedload of flash floods would promote the deposition in river channel and raise the river bed significantly, and this is the reason why flooding area extends with the increase of bedload transport rate in low-level bedload transport of flash floods. However, with the rise of bedload transport rate, the collisions of big particles greatly consumed the flood power, which obviously slows down the flood flow velocity and eventually leads to the reduction of flooding area.