Impact of the sampling duration on the uncertainty of averaged velocity measurements with acoustic instruments

Average velocity in streams is a key variable for the analysis and modelling of hydrological and hydraulic processes underpinning water resources science and practice. The present study evaluates the impact of the sampling duration on the quality of average velocity measurements acquired with contemporary instruments such as Acoustic Doppler Velocimeters (ADV) an Acoustic Doppler Current Profilers (ADCP). The evaluation combines considerations on turbulent flows and principles and configurations of acoustic instruments with practical experience in conducting customized analysis for uncertainty analysis purposes. The study sheds new insights on the spatial and temporal variability of the uncertainty in the measurement of average velocities due to variable sampling durations acting in isolation from other sources of uncertainties. Sampling durations of 90 and 150 s are found sufficient for ADV and ADCP, respectively, to obtain reliable average velocities in a flow affected only by natural turbulence and instrument noise. Larger sampling durations are needed for measurements in most of the natural streams exposed to additional sources of data variability.     

Subsurface flow measurements using passive flux meters in variably-saturated cold-regions landscapes

To date, passive flux meters have predominantly been applied in temperate environments for tracking the movement of contaminants in groundwater. This study applies these instruments to reduce uncertainty in (typically instantaneous) flux measurements made in a low-gradient, wetland dominated, discontinuous permafrost environment. This method supports improved estimation of unsaturated and over-winter subsurface flows which are very difficult to quantify using hydraulic gradient-based approaches. Improved subsurface flow estimates can play a key role in understanding the water budget of this landscape.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Belemnites from the lower middle Cenomanian of Hoppenstedt, northern Germany: significance and integrated correlation

The belemnite species Praeactinocamax primus (Arkhangelsky, 1912) and Belemnocamax boweri Crick, 1910 are described from the Cenomanian of the abandoned limestone quarry section of Hoppenstedt (Sachsen-Anhalt, northern Germany). They co-occur in the upper part of a prominent tripartite bioclastic limestone bed associated with the ammonite Acanthoceras rhotomagense, indicating the primus Event of the lower middle Cenomanian A. rhotomagense ammonite Zone. An integrated stratigraphical calibration including carbon stable isotope correlation to southern England suggests that the belemnite event horizon at Hoppenstedt occupies exactly the same chronostratigraphical position as elsewhere, highlighting the strictly isochronous character of the primus Event across northwestern Europe. Furthermore, stratigraphical gaps in the Hoppenstedt succession are evaluated.     

甲醛标准储备液浓度的不确定度评定

讨论了影响甲醛标准溶液浓度标定值不确定的各种因素,并评定了甲醛标准溶液浓度标定值的不确定度。当甲醛标准溶液浓度为1058 mg/L时,它的相对标准不确定度为0.70%(K=2)。     

气相色谱法测定地下水中六六六结果的不确定度评定

依照《测量不确定度评定与表示》,对气相色谱法测定地下水中六六六(HCH)四种单体结果进行了不确定度评定。分析了测量过程中引入的不确定度来源,包括提取液体积的量取、样品提取溶液的定容体积、分析仪器的进样量、标准系列溶液的测量以及仪器重复测定等分量引入不确定度及其各参数的采集和计算方法,最后合成标准不确定度,通过乘以95%概率下的扩展因子2,获得测量结果的扩展不确定度。     

火试金法测定铜精矿中金含量结果的不确定度评定

对火试金法测定铜精矿中金含量的结果进行不确定度评定。分析了铜精矿样品称量、铜精矿样品的不均匀性和配料处理,以及金粒称量等因素对金含量测量结果不确定度的影响,并得出火试金法测量铜精矿中金含量的扩展不确定度。     

GPS变形监测平差计算及不确定度分析

全球定位系统（GPS）是一种全天候、高精度的连续定位系统,它以速度快、方法灵活多样、操作简便等优势被广泛应用于工程测量和变形监测中。结合水厂铁矿GPS边坡变形监测实例,对GPS监测网的星历预报、基线向量平差计算、网平差计算、结果及残差不确定度进行了细致分析研究,以验证GPS技术在边坡变形监测中的可靠性和精度。