新疆及邻区地震构造图简介

This paper briefly introduces the Seismotectonic Map of Xinjiang and its neighborhood in the scale of 1∶2500000.The map is amended,supplemented and expanded based of the newly compiled Seismotectonic Map of Xinjiang in scale 1∶1000000.The base map of this seismotectonic map is the geologic map of western China and its neighborhood compiled by Li Tingdong.The abundant new materials from related research,referential literatures and the analyses on remote sensing data were used in the compiling work.A database and relevant documents are built for nearly 300 active faults and 150 active folds.The basic information of the major active faults,especially those near the border areas in this map are introduced in this paper.     

Estimation of the Budyko model parameter for small basins in China

At the mean annual scale, water availability of a basin is substantially determined by how much precipitation will be partitioned into evapotranspiration and run-off. The Budyko framework provides a simple but efficient tool to estimate precipitation partitioning at the basin scale. As one form of the Budyko framework, Fu's equation has been widely used to model long-term basin-scale water balance. The major difficulty in applications of Fu's equation is determining how to estimate the curve shape parameter ω efficiently. Previous studies have suggested that the parameter ω is closely related to the long-term vegetation coverage on large river basins globally. However, on small basins, the parameter ω is difficult to estimate due to the diversity of controlling factors. Here, we focused on the estimation of ω for small basins in China. We identified the major factors controlling the basin-specific (calibrated) ω from nine catchment attributes based on a dataset from 206 small basins (≤50,000 km²) across China. Next, we related the calibrated ω to the major factors controlling ω using two statistical models, that is, the multiple linear regression (MLR) model and artificial neural network (ANN) model. We compared and validated the two statistical models using an independent dataset of 80 small basins. The results indicated that in addition to vegetation, other landscape factors (e.g., topography and human activity) need to be considered to capture the variability of ω on small basins better. Contrary to previous findings reached on large basins worldwide, the basin-specific ω and remote sensing-based vegetation greenness index exhibit a significant negative correlation. Compared with the default ω value of 2.6 used in the Budyko curve method, the two statistical models significantly improved the mean annual ET simulations on validation basins by reducing the root mean square error from 114 mm/year to 74.5 mm/year for the MLR model and 70 mm/year for the ANN model. In comparison, the ANN model can provide a better ω estimation than the MLR model.     

Incorporating spatial association into statistical classifiers: local pattern-based prior tuning

ABSTRACT

This paper proposes a new classification method for spatial data by adjusting prior class probabilities according to local spatial patterns. First, the proposed method uses a classical statistical classifier to model training data. Second, the prior class probabilities are estimated according to the local spatial pattern and the classifier for each unseen object is adapted using the estimated prior probability. Finally, each unseen object is classified using its adapted classifier. Because the new method can be coupled with both generative and discriminant statistical classifiers, it performs generally more accurately than other methods for a variety of different spatial datasets. Experimental results show that this method has a lower prediction error than statistical classifiers that take no spatial information into account. Moreover, in the experiments, the new method also outperforms spatial auto-logistic regression and Markov random field-based methods when an appropriate estimate of local prior class distribution is used.     

Improved finite element–based limit equilibrium method for slope stability analysis by considering nonlinear strength criteria and its application in assessing the anchoring effect

The shear strength envelope of most geotechnical materials is nonlinear. In this study, the finite element–based limit equilibrium method (FELE) is improved to assess the stability of a prescribed slip surface that obeys a nonlinear failure criterion. Two nonlinear failure criteria, namely, the Barton criterion and the generalized Hoek-Brown (GHB) criterion, are implemented. A power curve model that can perfectly fit the envelope of the GHB criterion is proposed to explicitly express the shear strength from the normal stress. The algorithm of the improved FELE, which includes a nonlinear criterion, is explained in detail, and the fast convergence of the method is checked by evaluating examples. The numerical examples show that, for a smooth slip surface, FELE can calculate a greater factor of safety (FOS) than that calculated using the Morgenstern-Price (MP) method when the strength criterion of slip surface is nonlinear. In addition, FELE can determine the bell-shaped distribution of the increase in normal stress caused by anchoring measures, which cannot be considered in the MP method.     

Application of multivariate model based on three simulated sensors for water quality variables estimation in Shitoukoumen Reservoir,Jilin Province,China

This study applied a multivariate model based on three simulated sensors to estimating water quality variables in Shitoukoumen Reservoir, Changchun City, Jilin Province, China, including concentration of total suspended matter, concentration of chlorophyll-a and non-pigment matter absorption. Two field campaigns for spectra measurements with a total of 40 samples were carried out on June 13 and September 23, 2008. The in-situ spectra were recalculated to the spectral bands and sensitivities of the instruments applied in this paper, i.e. Landsat TM, Alos and P6, by using the average method. And the recalculated spectra were used for estimating water quality variables by the single model and multivariate model. The results show that the multivariate model is superior to the single model as the multivariate model takes the combined effects of water components into consideration and can estimate water quality variables simultaneously. According to R ² and RMSE, Alos is superior to other sensors for water quality variables estimation although the precision of non-pigment matter absorption inversion performed the second.     

三江平原挠力河上游流域水文过程及其驱动力模型研究

以三江平原挠力河上游流域为研究对象,选择年均流量和洪峰流量两个水文参变量,对流域降水、耕地面积和各水文参变量的统计回归分析,分别建立水文过程的单因素模型,用于分析气候变化、土地利用变化对水文过程的影响。在定量区分土地利用变化和气候变化的水文效应基础上,利用最小二乘法建立基于降雨量和耕地面积两种因素的流域水文过程驱动力模型。研究结果表明:(1)1956-1975年间降雨量对水文过程的影响非常显著,之后影响逐渐降低,总体上为气候模型对年均流量的模拟能力高于洪峰流量;(2)流域耕地面积,自1954年以来不断扩张,但未对水文过程产生显著影响,对洪峰流量的影响高于对年均径流的影响;(3)研究区的水文过程驱动力模型的模拟效果较好,相比单因素模型,年均流量和洪峰流量的模拟精度均得到较大提高,RMSE分别为0.5和1.04;对年均流量的模拟精度更高一些,决定性系数为0.933;(4)总体上,研究区水文过程受气候变化的影响程度高于土地利用变化,但土地利用变化对水文过程的影响不容忽视,尤其是对洪峰流量的影响呈增大趋势。     

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郑州城市游憩地意象空间分析

城市游憩地意象空间分析对城市旅游的规划与开发具有重要的指导意义。以城市居民和外来游客为研究对象,采用意象草图调查和问卷调查相结合的方法对郑州市游憩地意象空间进行研究。研究表明,居民和游客构图特点存在一定差异,并且草图中有一些城市意象5种要素无法涵盖的成分。通过对草图和问卷调查结果的分析,对郑州市的游憩地开发提出了一些建议。