SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.     

昆仑山口大地震与地形变异常的讨论

针对昆仑山口大地震，总结了多种地形变（大地测量）手段所显示的异常变化及其时空分布，结果显示：8．1级大震前存在空间尺度大，时间尺度的地形变前兆异常，简要介绍了相关的异常图像，给出了初步解释，并对未来震情的发展进行了探讨，认为近期内强震活动向华北迁移的可能性不大。     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

形变大地测量学的进展、问题与地震预报

简要概括了形变大地测量学的革命性进展，研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”，但也存在不少急待解决的问题。着重研讨了在21世纪前10年，形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术，开展创新性研究和试验以推进地震预报。为此，对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。     

Late Holocene great earthquakes and relative sea‐level change at Kenai,southern Alaska

Kenai, located on the west coast of the Kenai Peninsula, Alaska, subsided during the great earthquake of AD 1964. Regional land subsidence is recorded within the estuarine stratigraphy as peat overlain by tidal silt and clay. Reconstructions using quantitative diatom transfer functions estimate co‐seismic subsidence (relative sea‐level rise) between 0.28±0.28 m and 0.70±0.28 m followed by rapid post‐seismic recovery. Stratigraphy records an earlier co‐seismic event as a second peat‐silt couplet, dated to ～1500–1400 cal. yr BP with 1.14±0.28 m subsidence. Two decimetre‐scale relative sea‐level rises are more likely the result of glacio‐isostatic responses to late Holocene and Little Ice Age glacier expansions rather than to co‐seismic subsidence during great earthquakes. Comparison with other sites around Cook Inlet, at Girdwood and Ocean View, helps in constructing regional patterns of land‐level change associated with three great earthquakes, AD 1964, ～950–850 cal. yr BP and ～1500–1400 cal. yr BP. Each earthquake has a different spatial pattern of co‐seismic subsidence which indicates that assessment of seismic hazard in southern Alaska requires an understanding of multiple great earthquakes, not only the most recent. All three earthquakes show a pre‐seismic phase of gradual land subsidence that marked the end of relative land uplift caused by inter‐seismic strain accumulation. Copyright © 2005 John Wiley & Sons, Ltd.     

Strong Tides in 1964 and 1982

1StrongtideandastronomicalconditionsPartial solar eclipse occurred 4 times in 1964, 1982 and 2000 respectively. Time interval is about 3 Saros periods (one Saros period is 18 years and 10.33～11.33 days). Total lunar eclipse occurred 2 times in 1964 and 2000 respectively and 3 times in 1982. However, there was no lunar eclipse in 1966, 1984 and 2002. It seems that they had similar astro-nomical conditions and the best was in 1982. The studies about the effect of tide on the global climate…     

临猗5.0级地震前后品质因子值变化特征研究

利用西安数字地震遥测台网记录的数字地震资料，采用P波初动半周期残差法求得1998年7月临猗5．0级地震前后不同路径的Q(品质因子)值变化，发现在地震发生前Q值为87～203，震后Q值为67～164，震前震中区附近出现明显的高Q值异常。结果表明，地震前的高Q值异常可以作为地震预测的一种手段。