Bathymetric inversion of South China Sea from satellite altimetry data

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Gamma Emitters on Micro-Becquerel Activity Level in Air at Kraków (Poland)

The Petryanov air filters combined into half-year sets were analyzed for the presence of ⁴⁰K, ¹³⁷Cs and ²²Na by means of low-background gamma rays spectrometry. Each sample contains aerosols from more than 1 Mm³ of air. Samples were collected in ground level air at Kraków (Southern Poland) from 1996 to 2002. Activity concentrations of ⁴⁰K are almost constant with the mean of 14.7± 4.5 Bq m^–3. Activity concentrations of ¹³⁷Cs, which are on the level of single Bq m^{– 3} show exponential decrease with effective half-life time of 7.07± 0.77 years. The cosmogenic ²²Na shows a strong seasonal variation with significant different mean values activity concentration between 0.333± 0.095 Bq m^–3 and 0.137± 0.045 Bq m^–3, for summer and winter, respectively. Moreover, the activity ratio for two cosmogenic radionuclides: ²²Na and measured previously ⁷Be show also changes with statistically significant seasonal differences. The lower values were found during winters. The mechanisms which might govern this ratio are discussed. The conclusion is that transport of ²²Na during summer seems to be so much effective, that results in kind of relative depletion of stratosphere of this nuclide.     

中强震前形变固体潮汐资料短期信息的提取

分析了各种潮汐观测资料处理方法,针对短期异常提取的要求,提出了适合提取短期异常信息的潮汐资料处理方法,对其计算公式进一步推导和展开。应用这些方法对华北地区和西南地区的重力、倾斜、应变等形变观测量进行了计算。对地震前潮汐因子、时间滞后、响应比等潮汐参数的异常信息进行了提取与分析;突出了震源区附近的短期异常信息,并分析总结其变化特征。     

云南水汞在打破M≥5级地震平静后强震前的异常分析

通过普洱6．3、宁蒗6．2级和姚安6．5级3个在省内M≥5级地震平静了10余个月,打破5级平静后发生的M≥6级强震前水汞的异常分析,并着重短临异常研究,结果表明这3次地震前水汞均有中期和短、临异常,中、短、临异常台站数为两头少,中间多。中期异常表现为11％。22％的水汞观测台站震前出现2—10个月的中期异常;短期异常表现为震前2—3个月,平均44％的台站观测到短期异常,最大异常幅度与异常判定线比值在1．3—3．2倍之间：强震前都只有1个台站出现临震异常。短期异常有差异,宁蒗6．2级主震前,短期异常在2次前震前出现,普洱6．3、姚安6．5级地震前,水汞短期异常在打破5级平静的地震前出现,水汞短期异常有活跃、平静的现象。最早出现中期异常的台站相对靠近震中。     

Sea surface height and transport stream function of the South China Sea from a variable-grid global ocean circulation model

The study on the South China Sea (SCS) circulation has a history of more than 40 years. Nevertheless, the SCS circulation is not fully understood compared with the Bohai Sea, Yellow Sea and East China Sea (ECS). Many numerical studies on the SCS circulati…     

Conditioning mean steady state flow on hydraulic head and conductivity through geostatistical inversion

Nonlocal moment equations allow one to render deterministically optimum predictions of flow in randomly heterogeneous media and to assess predictive uncertainty conditional on measured values of medium properties. We present a geostatistical inverse algorithm for steady-state flow that makes it possible to further condition such predictions and assessments on measured values of hydraulic head (and/or flux). Our algorithm is based on recursive finite-element approximations of exact first and second conditional moment equations. Hydraulic conductivity is parameterized via universal kriging based on unknown values at pilot points and (optionally) measured values at other discrete locations. Optimum unbiased inverse estimates of natural log hydraulic conductivity, head and flux are obtained by minimizing a residual criterion using the Levenberg-Marquardt algorithm. We illustrate the method for superimposed mean uniform and convergent flows in a bounded two-dimensional domain. Our examples illustrate how conductivity and head data act separately or jointly to reduce parameter estimation errors and model predictive uncertainty.This work is supported in part by NSF/ITR Grant EAR-0110289. The first author was additionally supported by scholarships from CONACYT and Instituto de Investigaciones Electricas of Mexico. Additional support was provided by the European Commission under Contract EVK1-CT-1999-00041 (W-SAHaRA-Stochastic Analysis of Well Head Protection and Risk Assessment).     

Stochastic estimation of facies using ground penetrating radar data

Explicitly defining large-scale heterogeneity is a necessary step of groundwater model calibration if accurate estimates of flow and transport are to be made. In this work, neural networks are used to estimate radar facies probabilities from ground penetrating radar (GPR) images, yielding stochastic facies-based models that honour the large-scale architecture of the subsurface. For synthetic GPR images, a neural network was able to correctly identify radar facies with an accuracy of approximately 90%. Manual interpretation of a set of 450 MHz GPR field data from the Borden aquifer resulted in the identification of four radar facies. Of these, a neural network was able to identify two facies with an accuracy of near 80% and one with an accuracy of 44%. The neural network was not able to identify the fourth facies, likely due to the choice of defining facies characteristics. Sequential indicator simulation was used to generate facies realizations conditioned to the radar facies probabilities. Numerical simulations indicate that significant improvements in the prediction of solute transport are possible when GPR is used to constrain the facies model compared to using well data alone, especially when data are sparse.This work was supported by funding to R. Knight under Grant No. DE-FG07–00ER15118-A000, Environmental Management Science Program, Office of Science and Technology, Office of Environment Management, United States Department of Energy (DOE). However, any opinions, findings, conclusions, or recommendations expressed herein are those of the authors and do not necessarily reflect the views of DOE. Further support was provided by a Stanford Graduate Fellowship to S. Moysey. The authors would also like to thank James Irving for his assistance with processing of the radar data.     

Potential pollution of groundwater in the valley of the Seybouse River,north-eastern Algeria

In north-eastern Algeria, the Seybouse River is an important source of water used mainly for irrigation of large agricultural areas extending from the Guelma region to Annaba city. Industrial activities in this region contribute substantial water pollution to the river and the groundwater. Based on the different sources of pollution, mapping of areas vulnerable to groundwater pollution has been accomplished by combining land use and data on groundwater levels. The resulting maps show that the most vulnerable areas are those with large industrial activities—in Meboudja, Bouchegouf and Guelma. Infiltration and runoff contribute to pollution, and the highest infiltration rate is generally observed in areas of agricultural and industrial activities. Pollution of the aquifers in this area is of concern. Mountains, such as the Edough and Gelaat Bou Sbaa, contribute high runoff that carries pollutants towards the groundwater.     

GIS-based determination of the mean long-term groundwater recharge in Lower Saxony

This paper presents the findings of a collaborative research project of the Geological Survey of Lower Saxony (NLfB) and the Programme Group Systems Analysis and Technology Evaluation (STE) of Research Centre Jülich on the GIS-based determination of the mean long-term groundwater recharge in Lower Saxony using high-resolution digital data (Dörhöfer and others 2001). The model calculations were performed on the basis of the water-balance model GROWA (Kunkel and Wendland 2002) with a spatial resolution of 100x100 m². The accuracy of the calculated groundwater recharge values for the period 1961–1990 was verified on the basis of data from gauging stations and displayed a good agreement between observed runoff values and model results.     

大别山地震波速度剖面的重力拟合及花岗岩带

笔者对穿越大别山造山带的六安—大冶宽角反射地震剖面进行了重力拟合。拟合结果表明严格按宽角反射地震速度换算成的密度剖面所产生的是一个重力高,它反映出大别山是一个穹隆,与实测大别山重力低大相径庭。只有将位于大别山山根上,南北大别之间设置一个从地表直达莫霍界面的巨大低密度体,重力曲线才能得到很好的拟合。这个低密度体应为近北西走向的花岗岩带。它与反射地震剖面上石镇透明反射地震带位置吻合,但宽度远较反射地震透明带为大。重力曲线的拟合进一步说明,在华北陆块与扬子陆块碰撞后的白垩纪时,大别山出现一个伸展期,在这个时期,大别山穹隆形成,并伴随有大规模花岗岩的侵入,超高压变质岩从地壳中下部折返到地表。研究说明,联合应用反射地震、宽角反射地震和重力,进行综合解释是必要的,可以得到更令人信服的地质结论。