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Leakage through the permeable coarse soils of dam foundations in Tibet, China, lessened over time without any additional antiseepage measures. In fact, clogging generated during the infiltration process is recognized as the major factor in reducing leakage. A laboratory study was conducted to understand clogging in highly permeable coarse soil of a dam foundation with the primary aim of determining the clogging patterns and optimum clogging particle size (PS). Seven replicate experiments were constructed using soil media with PS ranges of 32–64 mm, 16–32 mm, 8–16 mm, 4–8 mm, 2–4 mm, 1-2 mm, and 0.5–1 mm to observe clogging after feeding the soil media with sediments of different PSs. The experimental results showed that four clogging patterns were formed in different PSs of the coarse foundation soil. The ratio of the effective aperture of the soil Dea and the equivalent clogging particle size dede/Dea had a dominant effect on the four clogging patterns (surface clogging, de/Dea>1; surface-internal clogging, 0.5<de/Dea≤1; internal partial pore blockage, 0.25<de/Dea≤0.5; and unclogging, de/Dea≤0.25). The assessment criterion of the optimum clogging pattern was determined by 0.5<de/Dea≤1, and from that, the optimum clogging PS do was calculated.

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Abstract. The present study is to explore the potential relationship between debris flow and landslides by establishing susceptibility zoning maps (SZMs) separately with the use of random forest (RF). Lhünzê county, located in southeastern Tibet, was selected as the study area. The work was carried out with the following steps: (1) an inventory map consisting of 399 landslides and 49 debris flows was determined; (2) slope units and 11 conditioning factors were prepared for the susceptibility modeling of landslide while watershed units and 12 factors were prepared for debris flow; (3) SZMs were constructed for landslide and debris flow, respectively, with the use of RF; (4) the performance of two models was evaluated by 5-fold cross-validation using receiver operating characteristic (ROC), area under the curve (AUC) and statistical measures; (5) the potential relationship between landslide and debris flow was explored by the superimposition of two zoning maps; (6) the Gini index was applied to determine the major factors and analyze the difference between debris flow and landslides; (7) a combined susceptibility map with two considered hazardous phenomena was obtained. Two used models had demonstrated great predictive capabilities, with an accuracy of 87.33 % and 85.17 % and AUC of 0.902 and 0.892, respectively. Comparing the overlap of different susceptibility classes for two obtained maps, it was concluded that there is no straightforward relationship between the occurrence of debris flow and landslides. Although most landslides can be converted into debris flow, the area prone to debris flow did not promote the occurrence of a landslide. A susceptibility zoning map composed of two or more hazardous phenomena is comprehensive and significant in this regard, which provides a valuable reference for research studies of disaster-chain and engineering applications.