Groundwater recharge of carbonate aquifers of the Silesian-Cracow Triassic (southern Poland) under human impact

A Triassic carbonate unit has been intensively drained by zinc and lead ore mines and numerous borehole fields since the nineteenth century. Its groundwater recharge has increased due to: pumping of water from boreholes, mining activity, and urbanization. An approach to determine the amounts of the recharge at a variety of spatial scales is presented in the paper. Different methods were used to identify and quantify recharge components on a regional and local scale: mathematical modelling was performed for four aquifers included in an aquifer system, an analytical estimation based on the assumption that an average recharge is equal to the average discharge of the hydrogeological system—for six man-made drainage centres, and the method of water level fluctuation (WLF) was applied in one observation borehole. Results of modelling have been supplemented by observation of environmental tracers (δ¹⁸O, δ²H, ³H), noble gases temperatures, and ⁴He_exc in groundwater. The regional aquifer’s current recharge according to estimations performed by means of modelling varies from 39 to 101 mm/year on average. Depending on the aquifer site the average precipitation ranges from 779 to 864 mm/year. In the confined part of the aquifer average recharge ranges from 26 to 61 mm/year. Within outcrops average recharge varies from 96 to 370 mm/year. Current recharge estimated by the analytical method for man-made drainage centres varies from 158 up to 440 mm/year. High values are caused by different recharge sources like precipitation, induced leakage from shallow aquifers, and water losses from streams, water mains and sewer systems. Pumping of water, mining and municipal activities constitute additional factors accounting for the intensified recharge.     

An earthquake scenario for the microzonation of Sofia and the vulnerability of structures designed by use of the Eurocodes

The study of the site effects and the microzonation of a part of the metropolitan Sofia, based on the modelling of seismic ground motion along three cross-sections are performed. Realistic synthetic strong motion waveforms are computed for scenario earthquakes (M=7) applying a hybrid modelling method, based on the modal summation technique and finite differences scheme. The synthesized ground motion time histories are source and site specific. The site amplification is determined in terms of response spectra ratio (RSR). A suite of time histories and quantities of earthquake engineering interest are provided. The results of this study constitute a “database” that describes the ground shaking of the urban area. A case study of experiment-based assessment of vulnerability of a cast-in-situ single storey, industrial, reinforced concrete frame, designed according to Eurocodes 2 and 8 is presented. The main characteristics of damage index and storey drift are discussed for the purposes of microzonation.     

斜坡变形综合评价系统研究

应用系统科学的基本思想,结合研究斜坡变形的各种方法,建立了针对斜坡变形和破坏的工程地质评价系统。该系统由基于人工神经网络法的稳定性计算子系统、可靠性评价子系统和以灰色系统理论为基础的预测子系统3部分组成,可完成对斜坡的稳定性计算、可靠性评价和变形及破坏的预测等功能,通过实例计算表明,该系统具有较好的适用性,可为斜坡灾害的防治提供重要的依据。      

一元P-范分布参数估计的改进方法

当观测误差服从P范分布时,本文从P范分布的概率密度函数和统计性质出发,利用绝对矩得到了参数p和方差的合理选择公式,给出了一种P范分布的参数的估计方法,可以使误差分布更加接近真实分布.将得到的参数估值作为应用极大似然估计法进行迭代时的初值,从而减少了运算时间,提高了运算效率.同时,将模型展开为泰勒级数,取至二次项,从而使...     

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基于地理神经网络加权回归的中国PM2.5浓度空间分布估算方法

中国空气污染问题日益严重,为获得连续的PM_2.5浓度空间分布,现有研究建立了多种基于统计回归的PM_2.5估算模型。然而,由于PM_2.5回归关系显著的空间非平稳性和复杂的非线性特征,如何实现高精度、高合理性的PM_2.5浓度空间大面估计仍然面临挑战,尤其在地形变化复杂、覆盖范围广阔的中国地区更为突出。本文引入了一种将普通线性回归（OLR）和神经网络结合的地理神经网络加权回归（GNNWR）模型,通过集成遥感数据、气象数据和地理信息数据建立了基于GNNWR的PM_2.5浓度空间估算方法。文章以中国2017年PM_2.5年平均浓度估算为例,开展了该模型与OLR、地理加权回归（GWR）的比较实验。实验结果表明,基于GNNWR的PM_2.浓度估算性能指标均明显优于OLR和GWR,且预测精度显著高于GWR。此外,GNNWR获得的PM_2.5浓度空间分布也更为合理,较为细致地刻画了中国地区PM_2.5浓度的局部空间变化和细节层次。     

Biomass estimation using Landsat-TM and -ETM+. Towards a regional model for Southern Africa?

Grazing and fire are major factors influencing the savanna ecosystems of Southern Africa. In both grazing and conservation areas overgrazing is an important reason for degradation of vegetation and soil. Insufficient fire management can cause a change in the species composition and may influence the soil negatively. For adequate planning purposes the knowledge of available biomass is indispensable. High-resolution satellite systems can provide such knowledge on a large scale. Three study areas in Southern Africa contributed to a first survey. Gutu District is situated in Zimbabwe. In its Communal Lands a high population density leads to severe degradation of vegetation and soil. The South African test sites are located in Kruger National Park and Madikwe Game Reserve. Therefore a wide ecological range from highly degraded to slightly disturbed savanna ecosystems is included. Satellite images of both Landsat-5 (TM) and Landsat-7 (ETM+) were applied. After cross-calibration of the two different satellite systems, indices applied to radiance and reflectance showed significant correlations with ground truth data of grass and other foliage biomass. Including new data from Hluhluwe National Park (South Africa) into the regression models improved the results, indicating that a regional model for savanna ecosystems in Southern Africa could be found. This revised version was published online in August 2006 with corrections to the Cover Date.     

一元有界p范分布的参数自适应估计

根据实际观测误差的有界性，得到了有界误差分布的一般模式，讨论了此分布的数学期望、方差和特征函数等数字特征，得到了极大似然估计方程。模拟算例的结果表明，有界p范分布参数估计的结果优于无界p范分布极大似然估计的结果。     

一元p范分布的参数快速估计方法

首先得到了一元p范分布在不同情况下的估计效率公式,给出了选择不同尺度参数时Lp估计的效率,说明了选择合适尺度参数的重要性;然后根据误差分布的实际情况,从一元p范分布的概率密度函数和统计性质出发,利用绝对矩得到了尺度参数和方差的合理选择公式。通过曲线拟合的公式,给出了一种一元p范分布的参数p的估计方法,并用两个模拟算例对本文方法进行了验证。