Takahisa Mizuyama

Development of new sensor systems for continuous bedload monitoring using a submerged load-cell system (SLS): Development of new sensor systems for continuous bedload monitoring

It is important to evaluate bedload discharge and temporal changes of the bed surface, and bed deformation can be estimated during floods if the bedload discharge is properly evaluated in an arbitrary cross-section. With the exception of grain size and its distribution within the bedload, bedload discharge has been measured using both direct and indirect methods. Bedload slot is a direct method but cannot be used to measure bedload during a flood because of volume limitations. Indirect methods require correlation between the signals and sediment volume measured using another method. In the present study, a small, automatically recording bedload sensor with an iron plate and a pair of load cells is developed in order to evaluate not only large particles but also sand particles as bedload. Bedload mass is calculated by integrating with respect to both the velocity of sediment particles and the averaged particle weight as measured by a pair of load cells, and, as an example, the velocity is estimated by the cross-correlation function of weights measured by load cells. The applicability of the proposed sensor is discussed based on the results of flume tests in the laboratory (2014) and the observation flume of the Hodaka Sedimentation Observatory of Kyoto University in Japan (2015). The system was installed in the observation flume in November of 2012, and flume data were obtained using natural sediment particles. In particular, it was difficult to estimate the velocity of averaged bedload particles, and it was better to apply a cross-correlation function in the laboratory tests. However, it appears that the previous estimation can estimate these velocities in the observation flume using a connecting tube and submerged load-cell systems. Copyright

Case study of debris flow disaster scenario caused by torrential rain on Kiyomizu-dera, Kyoto, Japan - using Hyper KANAKO system

This paper presents debris-flow numerical simulations using the Hyper KANAKO system, developed by the authors. The system uses the debris flow simulator KANAKO 2D equipped with a graphical user interface (GUI); hence, a user can easily produce appropriate landform data for simulations using standard laser profiler data, and visualize the results using a GIS. Hyper KANAKO was applied to the streams around Kiyomizu-dera in Kyoto, Japan. Kiyomizu-dera is a famous temple in Japan which is visited by numerous tourists throughout the year. We simulated a disaster scenario of debris flow caused by torrential rain. We set the hydrograph using rainfall intensity data, and set the landform data using information from the Geospatial Information Authority of Japan (GSI) and a digital elevation model (DEM). We evaluated different mesh sizes and also used a digital surface model (DSM) to consider the building heights. The simulation results showed that with small mesh size, the debris flow moved through the roads, which seems realistic for a disaster situation. When buildings were considered, the flow direction changed, and a 1-m flow depth, which was deeper than in other cases, appeared in the flow path. This may pose a dangerous situation for evacuations.

A Basic Study on Protective Steel Structures Against Woody Debris Hazards

This paper presents a basic study for protective structures (slit dams) against woody debris hazards. First, a model experiment was carried out to examine the trap efficiency of a slit dam against woody debris with or without roots. Herein, the effects of length of woody debris, flow discharge and opening width of a slit dam on the trap efficiency were investigated. Second, a new three dimensional distinct element method (3D-DEM) was developed to simulate the trap efficiency of woody debris with or without roots by introducing cylindrical elements. Finally, the new 3D-DEM was applied to simulate an actual woody debris disaster site in Hiroshima, Japan.

A STUDY ON THE REAL-TIME JUDGEMENT MODEL OF SEDIMENT STABILITY OF NEURAL NETWORK FOR COLLAPSE AND DEBRIS-FLOW IN HAZARD TORRENT

豪雨による土砂崩壊の発生に対して, パターン認識に優れるニューラルネットワークを用いて, 素因である地形要因に誘因となる降雨要因を考慮することにより土砂崩壊の「発生」「非発生」を判断するモデルを構築した. また, このモデルを用いてリアルタイムでの発生予測を行い, ニューラルネットワークの適用可能性について検討した. さらに, ニューラルネットワークの汎化能力を向上させるための検討と降雨要因による感度解析を行い, 本手法の有効性を示した.

A STUDY ON THE CHANGE OF DESTRUCTION FORM AND SCALE TO DEBRIS-FLOW AND COLLAPSE OF DEBRIS-FLOW IN HAZARDOUS TORRENT

昭和49年7月と昭和51年9月の2度に渡り土石流に見舞われた小豆島東海岸部を対象として, 渓流の崩壊形態や崩壊規模の変化を崩壊現象の拡大性や免疫性の観点から考察した. また, 地形要因や降雨要因を用いて崩壊現象の変化を定量的に扱い, 渓流の崩壊規模評価モデルを構築した. この評価モデルは, 一旦土石流の発生した渓流に対しても土石流の発生状況をモデル内に取り込むことにより, 再度土石流の発生を評価することができるため, 崩壊現象の変化を追跡することによりモデルの適用範囲を示した.

A STUDY ON THE METHOD FOR DETERMINING CRITICAL RAINFALL IN A SEDIMENT COLLAPSE DUE TO NATURAL FACTORS

土石流危険渓流における豪雨による土砂崩壊を対象として, 素因である地形要因と誘因となる降雨要因を組み合わせることにより, 土砂崩壊の「発生」「非発生」を判別するシステムを構築した. 判別システムでは, 土砂崩壊の発生に影響を与える要因について検討するとともにその発生を予測する上での課題について検討した. また, 本手法を土砂崩壊の発生限界線の設定に用いることにより, 渓流毎の個別防災管理を提案し, 土砂災害のソフト対策への適用可能性について検討した.

STUDY ON THE EVALUATION METHOD OF DEBRIS FLOW AND THE HILLSIDE LANDSLIDE SCALE OF DEBRIS FLOW IN HAZARDOUS TORRENT

土石流危険渓流における渓流調査は, 全国的に実施され渓流の危険度が評価されている. しかし, この調査の後に多くの渓流で土石流が発生したが, その妥当性の検証は十分であるとは言い難い. 本研究では, 昭和57年7月に長崎地方で発生した土石流災害のうち, 最も被害の大きかった長崎市東部地方を対象とし, 現行の渓流危険度評価の検証を行うと共に素因である地形要因を用いて谷頭崩壊や土石流の発生状況に基づいた渓流の崩壊規模を評価する方法を提案した.