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.     

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.     

分形在储层参数井间预测中的应用

现有地震资料难以实现储层薄层的预测，分形理论的引入，可弥补这一不足．以具有连续性和等间距采样点的测井资料为基础，以分形分析理论为手段，结合生产实际进行了研究．根据分形地质统计学中对储层参数的研究，得出其分形理论模型，并通过VisualBasic语言编程，在计算机上实现了某地区4口井储层参数（包括孔隙度、渗透率和泥质含量）的井间预测，其结果达到了预期的效果，说明将分形理论用于储层参数井间预测具有可行性．     

地震储层描述技术的应用效果

随着勘探程度的不断提高和油气勘探技术的不断发展,岩性油气藏勘探已成为主要的勘探目标,对三维地震储层描述新技术、新方法的要求越来越迫切.精细三维地震属性分析技术和储层识别标定技术以及测井约束反演技术的综合应用,形成了一套完善可行的技术系列,相继发现了辛154、王541、牛871等区块.地震储层描述技术的应用效果十分明鲜.     

陕西省地下水水质监测发展探析

本文针对陕西省地下水水质监测控制范围局限于农灌区，监测项目单一的现状，通过分析研究，提出水质监测的发展思路，剖析实现新思路的相关条件。