Isotope hydrological study of mean transit time in the granitic Strengbach catchment (Vosges massif,France): application of the FlowPC model with modified input function

Measurements of ¹⁸O concentrations in precipitation, soil solution, spring and runoff are used to determine water transit time in the small granitic Strengbach catchment (0·8 km²; 883–1146 m above sea level) located in the Vosges Mountains of northeastern France. Water transit times were calculated by applying the exponential, exponential piston and dispersion models of the FlowPC program to isotopic input (rainfall) and output (spring and stream water) data sets during the period 1989–95. The input function of the model was modified compared with the former version of the model and estimated by a deterministic approach based on a simplified hydrological balance. The fit between observed and calculated output data showed marked improvements compared with results obtained using the initial version of the model. An exponential piston version of the model applied to spring water indicates a 38·5 month mean transit time, which suggests that the volume in the aquifer, expressed in water depth, is 2·4 m. A considerable thickness (>45 m) of fractured bedrock may be involved for such a volume of water to be stored in the aquifer. Copyright © 2005 John Wiley & Sons, Ltd.     

Biological and granulometric controls on sedimentary organic matter of an intertidal mudflat

A variety of measures of organic matter concentration and quality were made on samples collected from the top few mm of intertidal mudflat sediment over the course of a year, in order to assess the relative importance of biological and sedimentological influences on sedimentary organic matter. Winter and summer were times of relatively fine-grained sediment accumulation, caused by biological deposition or stabilization processes and resulting in higher organic matter concentrations. Stable carbon isotope and Br:C ratios indicated a planktonic source of bulk organic matter. Ratios of organic carbon to specific surface area of the sediments were consistent with an organic monolayer coverage of sediment grains. Correction for changing grain size during the year showed no change in the organic concentration per unit surface area, in spite of organic matter inputs by in situ primary production, buildup of heterotroph biomass and mucus coatings, and biodeposition of organic-rich seston. There were also no indications of changes in bulk organic quality, measured as hydrolyzable carbohydrates and amino acids, in response to these biological processes. It is concluded that biological processes on a seasonal time scale affect the bulk organic matter of these sediments via a modulation of grain size rather than creation or decay of organic matter.     

Pressures of Crystallization of Icelandic Magmas

Iceland lies astride the Mid-Atlantic Ridge and was createdby seafloor spreading that began about 55 Ma. The crust is anomalouslythick (20–40 km), indicating higher melt productivityin the underlying mantle compared with normal ridge segmentsas a result of the presence of a mantle plume or upwelling centeredbeneath the northwestern edge of the Vatnajökull ice sheet.Seismic and volcanic activity is concentrated in 50 km wideneovolcanic or rift zones, which mark the subaerial Mid-AtlanticRidge, and in three flank zones. Geodetic and geophysical studiesprovide evidence for magma chambers located over a range ofdepths (1·5–21 km) in the crust, with shallow magmachambers beneath some volcanic centers (Katla, Grimsvötn,Eyjafjallajökull), and both shallow and deep chambers beneathothers (e.g. Krafla and Askja). We have compiled analyses ofbasalt glass with geochemical characteristics indicating crystallizationof ol–plag–cpx from 28 volcanic centers in the Western,Northern and Eastern rift zones as well as from the SouthernFlank Zone. Pressures of crystallization were calculated forthese glasses, and confirm that Icelandic magmas crystallizeover a wide range of pressures (0·001 to 1 GPa), equivalentto depths of 0–35 km. This range partly reflects crystallizationof melts en route to the surface, probably in dikes and conduits,after they leave intracrustal chambers. We find no evidencefor a shallow chamber beneath Katla, which probably indicatesthat the shallow chamber identified in other studies containssilica-rich magma rather than basalt. There is reasonably goodcorrelation between the depths of deep chambers (> 17 km)and geophysical estimates of Moho depth, indicating that magmaponds at the crust–mantle boundary. Shallow chambers (<7·1 km) are located in the upper crust, and probablyform at a level of neutral buoyancy. There are also discretechambers at intermediate depths (11 km beneath the rift zones),and there is strong evidence for cooling and crystallizing magmabodies or pockets throughout the middle and lower crust thatmight resemble a crystal mush. The results suggest that themiddle and lower crust is relatively hot and porous. It is suggestedthat crustal accretion occurs over a range of depths similarto those in recent models for accretionary processes at mid-oceanridges. The presence of multiple stacked chambers and hot, porouscrust suggests that magma evolution is complex and involvespolybaric crystallization, magma mixing, and assimilation. KEY WORDS: Iceland rift zones; cotectic crystallization; pressure; depth; magma chamber; volcanic glass     

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.     

On the recovery of surface wave by pressure transfer function

Except the commonly selected pressure transfer function derived from the linear wave theory, a previous study on the pressure transfer function for recovering surface wave from underwater pressure transducer suggested that the pressure transfer function is a function of frequency parameter only. With careful analysis, this study showed that the pressure transfer function should include a transducer submergence parameter as that given by the linear theory. It was found that the previously suggested empirical formula should be restricted to measurements with the pressure transducer close to the surface; otherwise overestimation of wave height would result. Field measurements were carried out with an acoustic wave gauge and a synchronized pressure transducer located at various depths with submergence parameter close to 1 (near the sea floor). It was shown that the previous one-parameter empirical formula might overestimate the significant wave height by more than 30%. This study found that with deep-water wave bursts excluded, the transfer function based on the linear wave theory provided a fairly good estimation on the significant wave heights, with an average deviation of 3.6%.     

受陆岸影响浅水区台风风浪的计算方案

在我国港口工程技术规范的波浪成长理论基础上，考虑到台风波浪的基本特点、等效水深的概念、浅水区波浪的折射、不规则波的能量分布特性、受陆岸和岛屿影响角度范围内的有效能量风区长度等因素，提出了受陆岸、岛屿影响浅水区（包括海湾区）台风风浪的计算方案。本方案只需台风中心位置、中心气压和计算点于各方位的风区长度（受陆岸影响部分）等资料，便可快速地得到计算点的波浪要素。经实测资料验证，效果良好。     

Sediment movement under unidirectional flows: an assessment of empirical threshold curves

A selection of threshold data sets from previous investigations is used to re-examine, selectively, some of the empirical curves that are most commonly used for the prediction of sediment threshold. Simple analytical formulae are derived describing single line curves for mean threshold values and envelopes for the initial movement of discrete particles and the commencement of mass sediment transport phases of the critical condition.The complexity of factors governing the prevailing conditions at threshold, together with the randomness of events, limits deterministic solutions; however, the curves provide an approach that can be used readily in practical applications. In contrast, the envelope presentation is more of a stochastic approach to the definition of threshold. It recognises that there is no definitive threshold condition under which a particular particle size can be displaced, but rather that a range of threshold values exist.The empirical threshold relationships were derived on the basis of a relatively large amount of data. However, the sources utilised have interpreted the ‘critical condition’ in various ways, implying that the formulae must be treated with caution in applications.     

Bowen数和东中国海Bowen数分布

本文讨论Bowen数的意义、功能和计算法。同时,依据多年水文气象实测资料作统计,计算出东中国海的Bo值。其结果绘制成1月至12月的月平均分布图,从而对本海域的Bo分布特点作详细分析介绍。     

Generalized ‘dependencies’ and parameter variance

The autodependence, (a special case of the — now quite obsolete — dependences, which had been introduced for very specialized astrometric purposes) is proportional to the parameter variance which is the expectation of the variance of the systematic error of a function evaluated with estimated parameters.