基于GIS的山区年均温分布模拟与制图

针对某些下垫面复杂而气象站(哨)有限的山区,用地理信息系统(GIS)和气温推算数学模型相结合,来获取全域的年均温分布栅格图和等值线矢量图。以龙游县为例,说明了该方法从数学模型、因素图输入、图层格式转换、图幅叠置分析等一系列技术步骤。     

Foliation fields and 3D cartography in geology: Principles of a method based on potential interpolation

A modeling method that takes into account known points on a geological interface and plane orientation data such as stratification or foliation planes is described and tested. The orientations data do not necessarily belong to one of the interfaces but are assumed to sample the main anisotropy of a geological formation as in current geological situations. The problem is to determine the surfaces which pass through the known points on interfaces and which are compatible with the orientation data. The method is based on the interpolation of a scalar field defined in the space the gradient in which is orthogonal to the orientations, given that some points have the same but unknown scalar value (points of the same interface), and that scalar gradient is known on the other points (foliations). The modeled interfaces are represented as isovalues of the interpolated field. Preliminary two-dimensional tests carried-out with different covariance models demonstrate the validity of the method, which is easily transposable in three dimensions.     

Measurement of the spatial distribution of fluvial bedload transport velocity in both sand and gravel

Maps are presented of the spatial distribution of two‐dimensional bedload transport velocity vectors. Bedload velocity data were collected using the bottom tracking feature of an acoustic Doppler current pro?ler (aDcp) in both a gravel‐bed reach and a sand‐bed reach of Fraser River, British Columbia. Block‐averaged bedload velocity vectors, and bedload velocity vectors interpolated onto a uniform grid, revealed coherent patterns in the bedload velocity distribution. Concurrent Helley‐Smith bedload sampling in the sand‐bed reach corroborated the trends observed in the bedload velocity map. Contemporaneous 2D vector maps of near‐bed water velocity (velocity in bins centered between 25 cm and 50 cm from the bottom) and depth‐averaged water velocity were also generated from the aDcp data. Using a vector correlation coef?cient, which is independent of the choice of coordinate system, the bedload velocity distribution was signi?cantly correlated to the near‐bed and depth‐averaged water velocity distributions. The bedload velocity distribution also compared favorably with variations in depth and estimates of the spatial distribution of shear stress. Published in 2004 by John Wiley & Sons, Ltd.     

疏降地下水引起地面塌陷浅析--以淮南煤矿区为例

以淮南西部矿区为例，介绍了该地区自20世纪60年代开采煤矿以来，由于疏降地下水，引起的地面塌陷。为了研究灰岩水动力场规律，先后在该区进行多时段、多水平放水试验。研究表明，覆盖粘土层、岩溶及人工疏降地下水，是该地区岩溶塌陷形成的基本条件。通过对粘土盖层性质、疏降地下水岩溶塌陷演化过程及塌陷机理与对应阶段过程综合分析，结合区域地质条件，掌握了塌陷点的分布规律。对目前西部地区塌陷“复活”、整治及未来城市规划，提出了建设性建议。     

GIS中矢量与栅格数据模型比较

由于GIS软件的多样性，每种软件都有自己特定的数据模型，从数据结构上来说，矢量和栅格是地理信息系统中两种主要的空间数据结构。本文通过对栅格数据与矢量数据模型的应用比较．对于空间数据从需求分析，以满足对数据信息进行更改、更新、增加或者为了某种特定的需要。     

基于GIS的地下水水源地补给潜力探讨

本文提出了一种基于GIS的补给潜力分析方法。在实例研究中,通过对地形、地表物质组成、包气带岩性、植被覆盖等因子建立的专题图层的叠加分析,确定了地下水的补给潜力分区,结合研究区含水层分布特征,综合确定了水源地的靶区和开采潜力区。研究表明,利用GIS确定研究区降雨入渗补给量是一种高效、直观、可行的方法。     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.