958 resultados para Time measurements.
Resumo:
The floods that occurred on the Aare and Rhine rivers in May 2015 and the mostly successful handling of this event in terms of flood protection measures are a good reminder of how important it is to comprehend the causes and processes involved in such natural hazards. While the needed data series of gauge measurements and peak discharge calculations reach back to the 19th century, historical records dating further back in time can provide additional and useful information to help understanding extreme flood events and to evaluate prevention measures such as river dams and corrections undertaken prior to instrumental measurements. In my PhD project I will use a wide range of historical sources to assess and quantify past extreme flood events. It is part of the SNF-funded project “Reconstruction of the Genesis, Process and Impact of Major Pre-instrumental Flood Events of Major Swiss Rivers Including a Peak Discharge Quantification” and will cover the research locations Fribourg (Saane R.), Burgdorf (Emme R.), Thun, Bern (both Aare R.), and the Lake of Constance at the locations Lindau, Constance and Rorschach. My main goals are to provide a long time series of quantitative data for extreme flood events, to discuss the occurring changes in these data, and to evaluate the impact of the aforementioned human influences on the drainage system. Extracting information given in account books from the towns of Basel and Solothurn may also enable me to assess the frequency and seasonality of less severe river floods. Finally, historical information will be used for remodeling the historical hydrological regime to homogenize the historical data series to modern day conditions and thus make it comparable to the data provided by instrumental measurements. The method I will apply for processing all information provided by historical sources such as chronicles, newspapers, institutional records, as well as flood marks, paintings and archeological evidence has been developed and successfully applied to the site of Basel by Wetter et al. (2011). They have also shown that data homogenization is possible by reconstructing previous stream flow conditions using historical river profiles and by carefully observing and re-constructing human changes of the river bed and its surroundings. Taken all information into account, peak discharges for past extreme flood events will be calculated with a one-dimensional hydrological model.
Resumo:
In situ and simultaneous measurement of the three most abundant isotopologues of methane using mid-infrared laser absorption spectroscopy is demonstrated. A field-deployable, autonomous platform is realized by coupling a compact quantum cascade laser absorption spectrometer (QCLAS) to a preconcentration unit, called trace gas extractor (TREX). This unit enhances CH4 mole fractions by a factor of up to 500 above ambient levels and quantitatively separates interfering trace gases such as N2O and CO2. The analytical precision of the QCLAS isotope measurement on the preconcentrated (750 ppm, parts-per-million, µmole mole−1) methane is 0.1 and 0.5 ‰ for δ13C- and δD-CH4 at 10 min averaging time. Based on repeated measurements of compressed air during a 2-week intercomparison campaign, the repeatability of the TREX–QCLAS was determined to be 0.19 and 1.9 ‰ for δ13C and δD-CH4, respectively. In this intercomparison campaign the new in situ technique is compared to isotope-ratio mass spectrometry (IRMS) based on glass flask and bag sampling and real time CH4 isotope analysis by two commercially available laser spectrometers. Both laser-based analyzers were limited to methane mole fraction and δ13C-CH4 analysis, and only one of them, a cavity ring down spectrometer, was capable to deliver meaningful data for the isotopic composition. After correcting for scale offsets, the average difference between TREX–QCLAS data and bag/flask sampling–IRMS values are within the extended WMO compatibility goals of 0.2 and 5 ‰ for δ13C- and δD-CH4, respectively. This also displays the potential to improve the interlaboratory compatibility based on the analysis of a reference air sample with accurately determined isotopic composition.
Resumo:
In this dissertation, we propose a continuous-time Markov chain model to examine the longitudinal data that have three categories in the outcome variable. The advantage of this model is that it permits a different number of measurements for each subject and the duration between two consecutive time points of measurements can be irregular. Using the maximum likelihood principle, we can estimate the transition probability between two time points. By using the information provided by the independent variables, this model can also estimate the transition probability for each subject. The Monte Carlo simulation method will be used to investigate the goodness of model fitting compared with that obtained from other models. A public health example will be used to demonstrate the application of this method. ^