Simultaneous Determination of Fluorine,Chlorine, Bromine and Iodine in Six Geochemical Reference Materials Using Pyrohydrolysis,Ion Chromatography and Inductively Coupled Plasma‐Mass Spectrometry

Concentrations of halogens (fluorine, chlorine, bromine and iodine) were determined in six geochemical reference materials (BHVO‐2, GS‐N, JG‐1, JR‐1, JB‐1b, JB‐2). Halogens were first extracted from powdered samples using a pyrohydrolysis technique, then hydrolysis solutions were analysed by ion chromatography for F and Cl and inductively coupled plasma‐mass spectrometry for Br and I. The detection limits in solutions were 100 μg l^?1 for both F and Cl and 10 ng l^?1 for Br and I. Considering the extraction procedure, performed on a maximum of 500 mg of sample and producing 100 ml of pyrohydrolysis solution, detection limits in rock samples were 20 mg kg^?1 for F and Cl and 2 μg kg^?1 for Br and I. The mean analytical errors on the studied composition ranges were estimated at 10 mg kg^?1 for F and Cl, 100 μg kg^?1 for Br and 25 μg kg^?1 for I. The concentration values, based on repeated (generally > 10) sample analysis, were in good agreement generally with published values and narrowed the mean dispersion around mean values. Large dispersions are discussed in terms of samples heterogeneity and contaminations during sample preparation. Basaltic RMs were found to be more suitable for studies of halogen compositions than differentiated rock material, especially granites – the powders of which were heterogeneous in halogens at the 500 mg level.     

Analysis of low-flow characteristics for catchments in Dongjiang Basin, China

Low-flow indices have been determined from long-term daily streamflow data for 13 catchments in Dongjiang Basin in southern China. The Brutsaert-Nieber method was applied to estimate catchment-scale effective groundwater parameters; representative values were 4.5?×?10^?4 m² s^?1 for the hydraulic diffusivity; 3.19?×?10^?5 m² s^?1/2 for the hydraulic desorptivity; 2.27?×?10^?4 m s^?1 for the hydraulic conductivity; and 0.2617 for the drainable porosity. The response constants correlate well with the total stream length and catchment area. Solutions of the linearised Boussinesq equation were used to guide the development of regional multivariate regression models for estimating low-flow indices from the catchment-scale effective parameters. Results showed that these catchments exhibit similar low-flow characteristics. The 7-day lowest average streamflows with return periods of 10 and 2 years (7Q10 and 7Q2) are highly correlated with the catchment-scale response constants. The low-flow ratio Q95/Q50 (ratio of daily streamflow exceeded 95 and 50% of the time, respectively) varied between 0.3 and 0.5, indicating a high proportion of groundwater in the streamflow. The advantage of the regional regression model is its conceptual basis and use of the catchment-scale effective parameters. The method has the potential to be applied to ungauged catchments for estimating low-flow statistics from stream length and catchment area.     

Representing geographical objects with scale‐induced indeterminate boundaries: A neural network‐based data model

The degree of uncertainty of many geographical objects has long been known to be in intimate relation with the scale of its observation and representation. Yet, the explicit consideration of scaling operations when modeling uncertainty is rarely found. In this study, a neural network‐based data model was investigated for representing geographical objects with scale‐induced indeterminate boundaries. Two types of neural units, combined with two types of activation function, comprise the processing core of the model, where the activation function can model either hard or soft transition zones. The construction of complex fuzzy regions, as well as lines and points, is discussed and illustrated with examples. It is shown how the level of detail that is apparent in the boundary at a given scale can be controlled through the degree of smoothness of each activation function. Several issues about the practical implementation of the model are discussed and indications on how to perform complex overlay operations of fuzzy maps provided. The model was illustrated through an example of representing multi‐resolution, sub‐pixel maps that are typically derived from remote sensing techniques.     

A comparative analysis of DEM‐based models to estimate the solar radiation in mountainous terrain

Daily solar radiation estimates of four up‐to‐date solar radiation models (Solar Analyst, r.sun, SRAD and Solei‐32), based on a digital elevation model (DEM), have been evaluated and compared in a Mediterranean environment characterized by a complex topography. The models' estimates were evaluated against 40 days of radiometric data collected in 14 stations. Analyzed sky conditions ranged from completely overcast conditions to clear skies. Additionally, the role of the spatial resolution of the DEM has been evaluated through the use of two different resolutions: 20 and 100 m. Results showed that, under clear‐sky conditions, the daily solar radiation variability in the study area may be reasonably estimated with mean bias errors under 10% and root mean square error values of around 15%. On the other hand, results proved that the reliability of the estimates substantially decreases under overcast conditions for some of the solar radiation models. Regarding the role of the DEM spatial resolution, results suggested that the reliability of the estimates for complex topography areas under clear‐sky conditions improves using a higher spatial resolution.     

A data‐mining approach for assessing consistency between multiple representations in spatial databases

When different spatial databases are combined, an important issue is the identification of inconsistencies between data. Quite often, representations of the same geographical entities in databases are different and reflect different points of view. In order to fully take advantage of these differences when object instances are associated, a key issue is to determine whether the differences are normal, i.e. explained by the database specifications, or if they are due to erroneous or outdated data in one database. In this paper, we propose a knowledge‐based approach to partially automate the consistency assessment between multiple representations of data. The inconsistency detection is viewed as a knowledge‐acquisition problem, the source of knowledge being the data. The consistency assessment is carried out by applying a proposed method called MECO. This method is itself parameterized by some domain knowledge obtained from a second method called MACO. MACO supports two approaches (direct or indirect) to perform the knowledge acquisition using data‐mining techniques. In particular, a supervised learning approach is defined to automate the knowledge acquisition so as to drastically reduce the human‐domain expert's work. Thanks to this approach, the knowledge‐acquisition process is sped up and less expert‐dependent. Training examples are obtained automatically upon completion of the spatial data matching. Knowledge extraction from data following this bottom‐up approach is particularly useful, since the database specifications are generally complex, difficult to analyse, and manually encoded. Such a data‐driven process also sheds some light on the gap between textual specifications and those actually used to produce the data. The methodology is illustrated and experimentally validated by comparing geometrical representations and attribute values of different vector spatial databases. The advantages and limits of such partially automatic approaches are discussed, and some future works are suggested.     

An adaptive approach to selecting a flow‐partition exponent for a multiple‐flow‐direction algorithm

Most multiple‐flow‐direction algorithms (MFDs) use a flow‐partition coefficient (exponent) to determine the fractions draining to all downslope neighbours. The commonly used MFD often employs a fixed exponent over an entire watershed. The fixed coefficient strategy cannot effectively model the impact of local terrain conditions on the dispersion of local flow. This paper addresses this problem based on the idea that dispersion of local flow varies over space due to the spatial variation of local terrain conditions. Thus, the flow‐partition exponent of an MFD should also vary over space. We present an adaptive approach for determining the flow‐partition exponent based on local topographic attribute which controls local flow partitioning. In our approach, the influence of local terrain on flow partition is modelled by a flow‐partition function which is based on local maximum downslope gradient (we refer to this approach as MFD based on maximum downslope gradient, MFD‐md for short). With this new approach, a steep terrain which induces a convergent flow condition can be modelled using a large value for the flow‐partition exponent. Similarly, a gentle terrain can be modelled using a small value for the flow‐partition exponent. MFD‐md is quantitatively evaluated using four types of mathematical surfaces and their theoretical ‘true’ value of Specific Catchment Area (SCA). The Root Mean Square Error (RMSE) shows that the error of SCA computed by MFD‐md is lower than that of SCA computed by the widely used SFD and MFD algorithms. Application of the new approach using a real DEM of a watershed in Northeast China shows that the flow accumulation computed by MFD‐md is better adapted to terrain conditions based on visual judgement.     

A combinatorial data model for representing topological relations among 3D geographical features in micro‐spatial environments

This research is motivated by the need for 3D GIS data models that allow for 3D spatial query, analysis and visualization of the subunits and internal network structure of ‘micro‐spatial environments’ (the 3D spatial structure within buildings). It explores a new way of representing the topological relationships among 3D geographical features such as buildings and their internal partitions or subunits. The 3D topological data model is called the combinatorial data model (CDM). It is a logical data model that simplifies and abstracts the complex topological relationships among 3D features through a hierarchical network structure called the node‐relation structure (NRS). This logical network structure is abstracted by using the property of Poincaré duality. It is modelled and presented in the paper using graph‐theoretic formalisms. The model was implemented with real data for evaluating its effectiveness for performing 3D spatial queries and visualization.     

福建地区人工爆破与天然地震的判定

利用福建地震台网的人工爆破与天然地震的数字记录,采用波形对比法,分析发生在同一地区的爆破与地震波形特征.结果发现,爆破与地震在震相、P波初动符号分布、振幅比As/Ap等方面具有不同特征,据此得出爆破识别的有效判据,并对一次疑爆事件进行有效检验,为今后爆破的识别提供依据.     

Performance of Full‐Scale Enhanced Reductive Dechlorination in Clay Till

At a low permeability clay till site contaminated with chlorinated ethenes (Gl. Kongevej, Denmark), enhanced reductive dechlorination (ERD) was applied by direct push injection of molasses and dechlorinating bacteria. The performance was investigated by long‐term groundwater monitoring, and after 4 years of remediation, the development of degradation in the clay till matrix was investigated by high‐resolution subsampling of intact cores. The formation of degradation products, the presence of specific degraders Dehalococcoides spp. with the vinyl chloride (VC) reductase gene vcrA, and the isotope fractionation of trichloroethene, cis‐dichloroethene (cis‐DCE), and VC showed that degradation of chlorinated ethenes occurred in the clay till matrix as well as in sand lenses, sand stringers, and fractures. Bioactive sections of up to 1.8 m had developed in the clay till matrix, but sections, where degradation was restricted to narrow zones around sand lenses and stringers, were also observed. After 4 years of remediation, an average mass reduction of 24% was estimated. Comparison of the results with model simulation scenarios indicate that a mass reduction of 85% can be obtained within approximately 50 years without further increase in the narrow reaction zones if no donor limitations occur at the site. Long‐term monitoring of the concentration of chlorinated ethenes in the underlying chalk aquifer revealed that the aquifer was affected by the more mobile degradation products cis‐DCE and VC generated during the remediation by ERD.     

A Practical Measurement Strategy to Estimate Nonlinear Chlorinated Solvent Sorption in Low foc Sediments

In this study, we tested a practical strategy useful for accurate chlorinated volatile organic compound (cVOC) sorption prediction. Corresponding to the feature of the superposition of adsorption due to thermally altered carbonaceous matter (TACM) with organic carbon‐water partitioning, a nonlinear Freundlich sorption isotherm covering a wide range of aqueous concentrations was defined by equilibrium sorption measurement at one or a few low concentration points with extrapolation to the empirical organic carbon‐water partition coefficient (K_oc,e) near compound solubility. We applied this approach to obtain perchloroethene equilibrium sorption isotherm parameters for TACM‐containing glacial sand and gravel subsoil samples from a field site in New York. Sorption and associated K_oc,c applicable to low (5–500 µg/L) and high (>100,000 µg/L) aqueous concentrations were determined in batch experiments. (The K_oc,c is the organic carbon‐normalized sorption partition coefficient corresponding to aqueous concentration C_w.) The K_oc,c measurements at low concentration (~5 µg/L) were 6 to 34 times greater than the K_oc,e. The importance of this type of data is illustrated through presentation of its substantial impact on the site remedy. In so doing, we provide an approach that is broadly applicable to cVOC field sites with similar circumstances (low carbon content glacial sand and gravel with TACM).