The state of land subsidence and prediction approaches due to groundwater withdrawal in China

This article gives a general introduction to land subsidence with the prediction approaches due to withdrawal of groundwater in three subsided/subsiding regions in China: the deltaic plain of Yangtse River (YRDP), North China Plain (NCP), and Fenwei Plain (FP). On YRDP, Shanghai is the typical subsided/subsiding city; on NCP Tianjin is the typical subsided/subsiding city, and on FP Taiyuan is the typical subsided/subsiding city. The subsided area with subsidence over 200 mm on YRDP is about 10,000 km² and the maximum subsided value reached 2.9 m at Shanghai; on NCP the subsided area reached 60,000 km² with the maximum subsidence of 3.9 m at Tianjing; on FP the subsided area is relatively smaller than that on the other two plains and is about 1,135 km² with maximum subsidence of 3.7 m at Taiyuan city. In order to protect the civil and industrial facilities, it is necessary to predict the future development of land subsidence based on present state. Many researchers proposed several approaches to predict the land subsidence due to groundwater withdrawal according to different geological conditions and groundwater withdrawal practice. This article classifies these approaches into five categories: (i) statistical methods; (ii) 1D numerical method; (iii) quasi-3D seepage model; (iv) 3D seepage model; (v) fully coupled 3D model. In China, the former four categories are presently employed in the prediction practice and their merits and demerits are discussed. According to the prediction practice, 3D seepage model is the best method presently.     

Triple diagram method for the prediction of wave height and period

Many formulations have been developed so far to predict the wave height and period from fetch length and wind blowing duration for a constant wind speed. This study aimed to predict wave parameters from fetch length and meteorological factors by using triple diagram methodology based on Kriging principles. Proposed model results were compared with Joint North Sea Wave Project (JONSWAP) model which is used so commonly in the ocean and coastal engineering studies. For the implementation of the methodology hourly wave and wind data were obtained from a buoy located in Lake Ontario. Numerical and graphical comparisons demonstrated that the proposed method outperforms the classical formulation.     

Filters for linear sea-wave prediction

Deterministic sea-wave prediction (DSWP) models are appearing in the literature designed for quiescent interval prediction in marine applications dominated by large swell seas. The approach has focused upon spectral methods which are straightforward and intuitively attractive. However, such methods have the disadvantage that while the sea is aperiodic in nature, the standard discrete spectral processing techniques force an absolutely periodic structure onto the resulting sea surface prediction models. As it is the shape of the sea surface that is important in such applications, particularly near the end of the domain which is important, the standard windowing techniques used in signal processing work to reduce leakage artifacts cannot be employed. This has necessitated the use of end matching methods that can be both inconvenient and may reduce the fraction of the time for which legitimate predictions are available. As a result, an investigation has been undertaken of the use of finite impulse response prediction filters to provide the necessary dispersive phase shifting required in DSWP systems. The present work examines the theoretical basis for such filters and explores their properties together with their application to both long and short crested swell seas. It is shown that wide band forms of such filters are only convergent in the sense of distributions having both infinite duration impulse responses and asymptotically divergent first derivatives. However, appropriate band limitation can produce useful finite impulse responses allowing implementation via standard discrete convolution methods. It is demonstrated that despite the prediction filters having a non-causal impulse response such filters can be used in practice due to a combination of the asymmetric nature of the impulse response and the fundamental nature of the prediction process. The findings are confirmed against actual sea-wave data.     

长江中下游6月份降水的一个预报指标

根据１９６３－１９９２年嵊山海洋站２月海气感热输送和２２ａ太阳磁周期与降水的关系，提出了一个长江中下游６月降水的综合预报指标，用此指标，对１９９３年６月长江中下游降水进行回报，结果与实况一致。     

Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.     

中国公路泥石流研究

公路泥石流是指发育于公路沿线并对公路桥涵、路基路面及相应防护结构具有冲击毁损和淤埋破坏的病害类型。丰富的物源、具有焚风效应的气象条件以及泥石流沟轴线与区域新构造应力场主压应力方向一致等是形成大型泥石流的宏观背景。将泥石流概化为固、液两相流体,运用两相流理论、泥沙运动力学、Bingham流变方程和Bagnold颗粒相互作用试验结果等,初步建立了泥石流固-液分相流速计算方法、基于泥石流在防治结构表面及泥石流沟岸产生的冲击形迹建立的反求泥石流冲击力计算方法以及泥石流磨蚀力计算方法。开发了速流结构、泥石流隧道及翼型墩汇流结构等10余种防治技术,集成了拦-汇-排等多种综合治理模式。据此撰写了《公路泥石流防治工程设计、施工指南》。实施了60余个防治工程。效果显著。研究成果初步构建了公路泥石流理论及技术体系。     

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.     

Testing earthquake prediction methods: «The West Pacific short-term forecast of earthquakes with magnitude MwHRV ≥ 5.8»

Analyzing the tables and probability maps posted by Yan Y. Kagan and David D. Jackson in April 2002–September 2004 at http://scec.ess.ucla.edu/~ykagan/predictions_index.html and the catalog of earthquakes for the same period, the conclusion is drawn that the underlying method could be used for prediction of aftershocks, while it does not outscore random guessing when main shocks are considered.     

重力斜导数方法在时间域中的理论模型与研究

Miller和Singh在1994年首次提出了斜导数(Tilt梯度)的定义,J.Derek Fairhead和Chris M.Green又于2004年在斜导数的基础上提出了Tilt梯度水平导数的概念。国内学者已对斜导数及斜导数水平导数展开研究,设定了多体模型、无限延伸倾斜脉模型、有限延伸倾斜台阶模型及埋深相同无限延伸垂直厚板及薄板模型,得出一些结论。针对一些地质体产状的判断,提出非绝对值斜导数水平导数的新概念,并应用于理论模型中验证,得出正确的结论。在上述理论模型基础上补充了断层模型和无限延伸倾斜台阶模型,应用非绝对值水平导数的理论解释地质体的产状,并对上述模型提出新的观点和看法。