Application of back-propagation networks in debris flow prediction

Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.     

Rainfall induced debris flows in pyroclastic deposits, Campania (southern Italy)

A combination of empirical and physically based hydrological models has been used to analyze historical data on rainfall and debris-flow occurrence in western Campania, to examine the correlation between rainfall and debris-flow events.

Rainfall data from major storms recorded in recent decades in western Campania were compiled, including daily series from several rain gauges located inside landslide areas, supplemented by hourly rainfall data from some of the principal storms.

A two-phase approach is proposed. During phase 1, soil moisture levels have been modelled as the hydrological balance between precipitation and evapotranspiration, on a daily scale, using the method of Thornthwaite [Geograph. Rev. 38 (1948) 55].

Phase 2 is related to the accumulation of surplus moisture from intense rainfall, leading to the development of positive pore pressures. These interactions take place on an hourly time scale by the “leaky barrel” (LB) model described by Wilson and Wiezoreck [Env. Eng. Geoscience, 1 (1995) 11]. In combination with hourly rainfall records, the LB model has been used to compare hydrological effects of different storms. The critical level of retained rain water has been fixed by the timing of debris-flow activity, related to recorded storm events.

New rainfall intensity–duration thresholds for debris-flow initiation in western Campania are proposed. These thresholds are related to individual rain gauge and assume a previously satisfied field capacity condition. The new thresholds are somewhat higher than those plotted by previous authors, but are thought to be more accurate and thus need less conservatism.     

A size classification for debris flows

A 10-fold classification for debris flow size is proposed based on total volume, peak discharge and area inundated by debris. Size classes can be used for regional overview studies where detailed site investigations are either unnecessary, too costly or where the highest hazard and risk creeks need to be identified for further study. They are also useful to compare the regional impact between affected areas and the effects of rainstorms, and they allow lay-people to obtain an understanding of debris flow magnitude and consequences. Finally, different size classes allow the estimation of travel times to points of interest based on empirically derived equations. It is proposed that agencies concerned with debris flows should establish a documentation of debris flow size according to this classification, which serves as a data base for hazard and risk planning.     

Possible effect of ENSO on annual sediment discharge of debris flows in the Jiangjia Ravine based on Morlet wavelet transforms

The multi-time-scale structures of an annual sediment discharge series of debris flow in the Jiangjia Ravine and the Southern Oscillation index are analysed using the method of Morlet wavelet transformations. The possible effects of E1 Nirio episodes on the annual sediment discharge are discussed by comparing the period variations of ENSO and the discharge. The results show that the annual sediment discharge series of debris flow is related to E1 Nifio episodes. Generally, the annual sediment discharge of debris flow is less than usual during an E1 Nifio episode and debris flow is less active. On the contrary, the annual sediment discharge of debris flows is greater than usual during a La Nifia episode and debris flows are more frequent. There is a relationship between the annual sediment discharges of debris flow in the Jiangjia Ravine and the summer Southern Oscillation index, with both having quasi-periodic variations of 2 and 5-6 years.     

A 2D finite volume model for bebris flow and its application to events occurred in the Eastern Pyrenees

FLATModel is a 2D finite volume code that contains several original approaches to improve debris-flow simulation. Firstly, FLATModel incorporates a ＂stop-and-go＂ technique in each cell to allow continuous collapses and remobilizations of the debris-flow mass. Secondly, flow velocity and consequently yield stress is directly associated with the type of rheology to improve boundary accuracy. Thirdly, a simple approach for entrainment is also included in the model to analyse the effect of basal erosion of debris flows. FLATMODEL was tested at several events that occurred in the Eastern Pyrenees and simulation results indicated that the model can represent rather well the different characteristics observed in the field.     

Soil evolution features of debris flow waste-shoal land

The reclamation and utilization of debris flow waste-shoal land plays an important role in the mitigation and control of debris flow hazards, which thus contributes a lot to the exploitation of insufficient land resources in mountainous areas and the reduction of losses caused by debris flow. The aim of this paper is to discuss the features and mechanism of soil evolution of debris flow waste-shoal land so as to search for the available modes of its reclamation and utilization. The Jiangjiagou Ravine, a typical debris flow ravine, was selected to study soil evolution features of debris flow waste-shoal land based on the analysis of soil physieochemical properties and soil microstructure. It was found that the soil evolution rates of debris flow waste-shoal land varied with different modes of reclamation. For the land which had been reclaimed for less than lO years, soil evolved most rapidly in paddy fields, and more rapidly in dry farmland than in naturally restored waste-shoal land. For the land which had been used for more than lo years, the soil evolution rates of dry farmland, naturally restored waste-shoal land and paddy farmland decreased in the file. For the same utilization period of time, significant differences were recognized in soil evolution features under different modes of reclamation. Analysis data showed that soil clay content, soil thickness, the psephicity of skeleton particles and contents of microaggregates （〈0.02 mm） in paddy farmland were all highest. Soil nutrients and porosity of dry farmland were better than those of paddy farmland and naturally restored waste-shoal land, and those of paddy farmland were superior to those of naturally restored waste-shoal land. Paddy farmland characterized by rapid pedogenesis, stable evolution and high utilizability was the priority candidate for the reclamation and utilization of debris flow waste -shoal land.     

Curvature derived from LiDAR digital elevation models as simple indicators of debris-flow susceptibility

To mitigate the damage caused by debris flows resulting from heavy precipitation and to aid in evacuation plan preparation, areas at risk should be mapped on a scale appropriate for affected individuals and communities. We tested the effectiveness of simply identifying debris-flow hazards through automated derivation of surface curvatures using LiDAR digital elevation models. We achieved useful correspondence between plan curvatures and areas of existing debris-flow damage in two localities in Japan using the analysis of digital elevation models(DEMs). We found that plan curvatures derived from 10 m DEMs may be useful to indicate areas that are susceptible to debris flow in mountainous areas. In residential areas located on gentle sloping debris flow fans, the greatest damage to houses was found to be located in the elongated depressions that are connected to mountain stream valleys. Plan curvaturederived from 5 m DEM was the most sensitive indicators for susceptibility to debris flows.     

彭州市干溪沟流域地震诱发地质灾害成因分析

干溪沟属于湔江的支流,在大地构造部位上位于龙门山断褶带中段前缘,地貌上属于侵蚀构造地貌和河流地貌,切割深,降雨量丰富,河谷、河流较发育.由于人工开采矿石普遍,地质灾害较发育,典型的地质灾害主要有大白岩崩塌体、大团包滑坡体、干溪沟潜在泥石流.大白岩逆冲崩塌体是在汶川大地震发生时,映秀一北川断层发生逆冲,上盘灰岩错出山坡,...     

Debris-flow event in the Frangerello Stream-Susa Valley (Italy)—calibration of numerical models for the back analysis of the 16 October, 2000 rainstorm

Three debris-flow simulation model software have been applied to the back analysis of a typical alpine debris flow that caused significant deposition on an urbanized alluvial fan. Parameters used in the models were at first retrieved from the literature and then adjusted to fit field evidence. In the case where different codes adopted the same parameters, the same input values were used, and comparable outputs were obtained. Results of the constitutive laws used (Bingham rheology, Voellmy fluid rheology and a quadratic rheology formulation which adds collisional and turbulent stresses to the Bingham law) indicate that no single rheological model appears to be valid for all debris flows. The three applied models appear to be capable of reasonable reproduction of debris-flow events, although with different levels of detail. The study shows how different software can be used to predict the debris-flow motion for various purposes from a first screening, to predict the runout distance and deposition of the solid material and to the different behaviour of the mixtures of flows with variation of maximum solid concentration.     

四川省都江堰市龙池地区泥石流危险性评价研究

汶川地震灾区震后泥石流灾害较震前活跃,对灾区泥石流危险性进行评价是灾后重建过程中合理防灾减灾的基础工作。通过研究泥石流灾害事件中的泥石流规模、泥石流沟堆积扇面积及相应的灾害损失等基础资料,提出以泥石流在泥石流沟堆积扇上的平均堆积厚度替代泥石流规模作为主要危险因子的单沟泥石流危险性评价方法。用该方法对汶川震区都江堰市龙池镇龙溪河流域2010年"8.13"泥石流事件中的29条沟谷型泥石流进行危险性评价,评价结果中9条为高度危险,12条为中度危险,8条为低度危险。用以泥石流规模为主要危险因子的单沟泥石流危险性评价方法进行对比评价,2种评价方法中有65.5%的泥石流的危险性评价结果一致。以泥石流沟堆积扇平均堆积厚度为主要危险因子的单沟泥石流危险性评价方法更能突出规模对泥石流综合危险度的贡献,能更好地反映小泥石流流域和小泥石流堆积扇的泥石流在中小规模的泥石流总量下的危险程度。