No description available.

A wide variety of information or 'metadata' is required when undertaking dendrochronological sampling. Traditionally, researchers record observations and measurements on field notebooks and/or paper recording forms, and use digital cameras and hand-held GPS devices to capture images and record locations. In the lab, field notes are often manually entered into spreadsheets or personal databases, which are then sometimes linked to images and GPS waypoints. This process is both time consuming and prone to human and instrument error. Specialised hardware technology exists to marry these data sources, but costs can be prohibitive for small scale operations (>$2000 USD). Such systems often include proprietary software that is tailored to very specific needs and might require a high level of expertise to use. We report on the successful testing and deployment of a dendrochronological field data collection system utilising affordable off-the-shelf devices ($100-300 USD). The method builds upon established open source software that has been widely used in developing countries for public health projects as well as to assist in disaster recovery operations. It includes customisable forms for digital data entry in the field, and a marrying of accurate GPS location with geotagged photographs (with possible extensions to other measuring devices via Bluetooth) into structured data fields that are easy to learn and operate. Digital data collection is less prone to human error and efficiently captures a range of important metadata. In our experience, the hardware proved field worthy in terms of size, ruggedness, and dependability (e.g., battery life). The system integrates directly with the Tellervo software to both create forms and populate the database, providing end users with the ability to tailor the solution to their particular field data collection needs.

Estudos de condições oceanográficas tornam-se imperativos a cada dia, tanto no fornecimento de dados para fins de pesquisa quanto para aplicações de engenharia. Tais usos variam desde a validação de modelos de previsão de ondas até a determinação de forças em estruturas offshore, bem como em condições de navegabilidade e operações logísticas. O uso dos movimentos do navio para determinar qual condição de mar os induziu, adotando a embarcação como um sensor, em analogia às boias oceanográficas, é uma das tecnologias disponíveis para a medição das condições oceanográficas. Esta destaca-se pela simplicidade na implementação, além de atender às necessidades da indústria petrolífera, uma vez que o interesse é voltado para eventos de ondas extremas, os quais são bem representados pela tecnologia considerada, como verificado nesta tese. A facilidade de obtenção de dados através da tecnologia mencionada, sem a necessidade de equipamentos adicionais { especialmente no caso de plataformas de petróleo devido à disponibilidade de bases inerciais em muitas embarcações deste tipo { foi essencial para garantir ao presente trabalho um conjunto de dados de campo composto por registros ininterruptos dos movimentos de uma plataforma FPSO durante dois anos, através do qual foi possível realizar estimativas das ondas em intervalos de trinta minutos. Esta rica base de dados, inédita na literatura especializada, aliada às estimativas fornecidas simultaneamente por um sistema de radar de ondas, permitiu um estudo detalhado das características e padrões dos espectros direcionais de onda e uma importante validação da aplicação da tecnologia em campo. Face às incertezas inerentes ao processo, no entanto, observa-se que, para um mesmo registro de movimentos, muitas soluções diferentes e quase equiprováveis podem ser obtidas, uma característica que favorece a aplicação de um método de inferência Bayesiana, afim de fornecer alguma informação a priori sobre as variáveis de estimação. Na presente abordagem, esta informação corresponde a uma suposição de suavidade dos espectros direcionais de onda a serem estimados, cujo grau é controlado pelos chamados hiperparâmetros do processo de inferência - parâmetros dentro do método que controlam a influência da informação a priori sobre a solução. Estudos prévios realizados na EPUSP demonstraram que o uso de hiperparâmetros fixos ou pré-calibrados é vantajoso para tornar o método de estimação operacionalmente aplicável, proporcionando um tempo de execução compatível com aplicações em tempo real. Dada a importância do papel desempenhado pela informação a priori na determinação de soluções viáveis no intervalo de incertezas do método, torna-se patente a necessidade de se definir valores apropriados para estes hiperparâmetros. Assim, neste trabalho, é apresentada uma metodologia de calibração para os hiperparâmetros baseada na dependência destes no período médio de onda e no parâmetro espectral de largura de banda. Esta nova abordagem traz dois aspectos inovadores para a pesquisa: O primeiro é o desenvolvimento de um método iterativo e autossuficiente capaz de identificar erros de estimação causados por incertezas no modelo de previsão de movimentos do navio. O segundo ponto é a capacidade do método de mitigar os erros encontrados, forçando a suavidade espectral ao longo do intervalo de frequências de onda. / Studies of oceanographic conditions become imperative every day, both in the provision of data for research purposes and for engineering applications. Such uses range from the validation of wave prediction models to the determination of forces in offshore structures, as well as navigability and logistical operations. The use of vessel movements to determine which is the condition induced by them, adopting the vessel as a sensor, in analogy to oceanographic buoys, is one of the available technologies for the measurement of oceanographic conditions. It stands out for the simplicity of the implementation, in addition it meets the needs of the oil industry, since the interest is focused on extreme wave events, which are well represented by the technology considered, as verified in this thesis. Ease of data attainment through the mentioned technology, without the need for additional equipment - especially in the case of oil platforms due to the availability of inertial bases in many vessels of this type - was essential to guarantee the present work the data set of field the FPSO platform for two years, through which it was possible to make estimates of the waves in intervals of thirty minutes. This rich database, unprecedented in the specialized literature, together with the estimates provided by a wave radar system, allowed a detailed study of the characteristics and patterns of the directional wave spectra and an important validation of the application of the technology in the field. Given the uncertainties inherent in the process, however, it can be observed that, for the same record of movements, many different and almost equiprobable solutions can be obtained, a feature that favors the application of a Bayesian inference method, in order to provide some information on the variables of estimation. In the present approach, this information corresponds to an assumption of smoothness of the directional wave spectra to be estimated, the degree of which is controlled by so-called hyperparameters of the inference process - parameters within the method that control the influence of a priori information on the solution. Previous studies conducted at EPUSP have demonstrated that the use of fixed or precalibrated hyperparameters is advantageous to make the estimation method operationally applicable, providing a runtime compatible with real-time applications. Given the importance of the role played by a priori information in determining viable solutions in the uncertainty range of the method, it becomes clear that it is necessary to define appropriate values for these hyperparameters. Thus, in this work, the calibration methodology for the hyperparameters is presented, based on the dependency of these on wave mean period and on bandwidth spectral parameter. The _rst is the development of an iterative, self-sufficient method, capable of identifying estimations errors caused by uncertainties on the ship\'s motions prediction model. The second is the ability of the method to mitigate the errors found, forcing spectral smoothness throughout the range of wave frequencies.

The Continuous Helical Displacement (CHD) pile is an auger displacement pile developed by Roger Bullivant Ltd in the UK. The CHD pile is installed in-situ through the use of a drilling auger, in a similar fashion to European screw piles and as such, it has performance characteristics of both displacement and non-displacement piles Based on field experience, it is known that the load capacity performance of the CHD pile significantly exceeds the current design predictions, particularly when installed in sand. Model CHD piles were created in pluviated test beds at a range of different densities and compared to model displacement and non-displacement piles. The load tests show that the CHD piles have a similar ultimate capacity to displacement piles. Instrumentation of the model piles allowed load distribution throughout the pile length to be determined. The tests allowed design parameters to be established, with it being shown that the CHD has lower bearing capacity factors and higher earth pressure coefficients than current suggestions .The disturbance to the in-situ soil conditions caused by the installation of the CHD piles was measured using a model CPT probe. The CHD pile was found to cause significant changes in soil relative density laterally around the pile shaft while displacement piles show changes predominantly below the pile base. The CHD pile is found to cause a densification of the in situ soil for all relative densities with the greatest increase occurring in loose sand. The ultimate capacity of the CHD pile is determined from load tests carried out on field CHD piles with the aid of capacity prediction methods for piles which have not been loaded to their ultimate capacity. The results from model testing have been applied to field pile tests to allow the development of design parameters including appropriate pile diameter, bearing capacity factor Nq and the earth pressure coefficient k which are suitable for CHD piles.

<p>For random waves the free surface elevation can be described by a number of individual wave parameters. The main objective of this work has been to study the statistical properties of individual parameters in successive waves; the wave crest height, the wave height and the wave period.</p><p>In severe sea states the wave crest heights exhibit a nonlinear behavior, which must be reflected in the models. An existing marginal distribution that uses second order Stokes-type nonlinearity is transformed to a two-dimensional distribution by use of the two–dimensional Rayleigh distribution. This model only includes sum frequency effects. A two-dimensional distribution is also established by transforming a second order model including both sum and different frequency effects. Both models are based on the narrow-band assumption, and the effect of finite water depth is included. A parametric wave crest height distribution proposed by Forristall (2000) has been extended to two dimensions by transformation of the two-dimensional Weibull distribution. </p><p>Two successive wave heights are modeled by a Gaussian copula, which is referred to as the Nataf model. Results with two initial distributions for the transformation are presented, the Næss (1985) model and a two-parameter Weibull distribution, where the latter is in best agreement with data. The results are compared with existing models. The Nataf model has also been used for modeling three successive wave heights. Results show that the Nataf transformation of three successive wave heights can be approximated by a first order autoregression model. This means that the distribution of the wave height given the previous wave height is independent of the wave heights prior to the previous wave height. The simulation of successive wave heights can be done directly without simulating the time series of the complete surface elevation. </p><p>Successive wave periods are modeled with the Nataf transformation by using a two-parameter Weibull distribution and a generalized Gamma distribution as the initial distribution, where the latter is in best agreement with data. Results for the marginal and two-dimensional distributions are compared with existing models. In practical applications, it is often of interest to consider successive wave periods with corresponding wave heights exceeding a certain threshold. Results show that the distribution for successive wave periods when the corresponding wave heights exceed the root-mean-square value of the wave heights can be approximated by a multivariate Gaussian distribution. When comparing the results with data, a long time series is needed in order to obtain enough data cases. Results for three successive wave periods are also presented. </p><p>The models are compared with field data from the Draupner field and the Japan Sea, and with laboratory data from experiments at HR Wallingford. In addition, data from numerical simulations based on second order wave theory, including both sum and frequency effects, are included.</p>

For random waves the free surface elevation can be described by a number of individual wave parameters. The main objective of this work has been to study the statistical properties of individual parameters in successive waves; the wave crest height, the wave height and the wave period. In severe sea states the wave crest heights exhibit a nonlinear behavior, which must be reflected in the models. An existing marginal distribution that uses second order Stokes-type nonlinearity is transformed to a two-dimensional distribution by use of the two–dimensional Rayleigh distribution. This model only includes sum frequency effects. A two-dimensional distribution is also established by transforming a second order model including both sum and different frequency effects. Both models are based on the narrow-band assumption, and the effect of finite water depth is included. A parametric wave crest height distribution proposed by Forristall (2000) has been extended to two dimensions by transformation of the two-dimensional Weibull distribution. Two successive wave heights are modeled by a Gaussian copula, which is referred to as the Nataf model. Results with two initial distributions for the transformation are presented, the Næss (1985) model and a two-parameter Weibull distribution, where the latter is in best agreement with data. The results are compared with existing models. The Nataf model has also been used for modeling three successive wave heights. Results show that the Nataf transformation of three successive wave heights can be approximated by a first order autoregression model. This means that the distribution of the wave height given the previous wave height is independent of the wave heights prior to the previous wave height. The simulation of successive wave heights can be done directly without simulating the time series of the complete surface elevation. Successive wave periods are modeled with the Nataf transformation by using a two-parameter Weibull distribution and a generalized Gamma distribution as the initial distribution, where the latter is in best agreement with data. Results for the marginal and two-dimensional distributions are compared with existing models. In practical applications, it is often of interest to consider successive wave periods with corresponding wave heights exceeding a certain threshold. Results show that the distribution for successive wave periods when the corresponding wave heights exceed the root-mean-square value of the wave heights can be approximated by a multivariate Gaussian distribution. When comparing the results with data, a long time series is needed in order to obtain enough data cases. Results for three successive wave periods are also presented. The models are compared with field data from the Draupner field and the Japan Sea, and with laboratory data from experiments at HR Wallingford. In addition, data from numerical simulations based on second order wave theory, including both sum and frequency effects, are included.

Extensive research has been undertaken to improve the robustness of runoff quantity predictions for urban catchments. However, equally robust predictions for runoff quality have yet to be attained. Past studies addressing this issue have typically been confined to the use of simple conceptual or empirical models which forgo the tedious steps of providing a physical representation of the actual system to be modelled. Consequently, even if the modelling results for the test catchments are satisfactory, the reliability and applicability of these models for other catchments remain uncertain. It is deemed that by employing process-based, deterministic models, many of these uncertainties can be eliminated. A lack of understanding of the hydrological processes occurring during storm events and the absence of good calibration data, however, hamper the advancement of such models and limit their use in the field. This research proposes that the development of a hydrologic model based on the kinematic wave equations linked to an advection-dispersion model that simulates pollutant detachment and transport will improve both runoff quantity and quality simulations and enhance the robustness of the predictions. At the very worst, a model of this type could still highlight the underlying issues that inhibit models from reproducing the recorded historical hydrographs and pollutographs. In actual fact, this approach has already been applied by various modellers to simulate the entrainment of pollutants from urban catchments. Also, the paradigm shift to using the Water Sensitive Urban Design (WSUD) approach in designing urban stormwater systems has prompted the need to differentiate the various sources of pollutants in urban catchments such as roads, roofs and other impervious surfaces. The primary objective of the study reported herein is to model runoff quantity and quality from small urban catchments, facilitated by the procurement of the necessary field data to calibrate and validate the model via implementation of a comprehensive field exercise based in Sydney. From a water quality perspective, trace metals were selected as the foci. The study outcomes include the formulation of a linkage of models capable of providing accurate and reliable runoff quantity and quality predictions for the study catchments by taking into consideration: - The different availability of pollutants from urban catchments, i.e. roads vs. roofs; - The build-up characteristics of pollutants on the distinct urban surfaces and their spatial distribution; - The contribution of rainwater to urban runoff pollution; - The partitioning of pollutants according to particulate bound and dissolved phases; - The respective role of rainfall and runoff in the detachment and entrainment of pollutants; - The influence of particle properties such as particle size distribution and density on pollutant transport; and - The relationship associating particulate bound metals to suspended solids. The simulation results obtained using the proposed model were found to be suitable for modelling the detachment and transport of pollutants for small urban catchments. Interpretation of these results reveals several key findings which could help to rectify shortcomings of existing modelling approaches. Even though the robustness of the model presented here may not translate into a significant improvement in the overall robustness of model predictions, the physical basis on which this process-based model was developed nevertheless provides the flexibility necessary for implementation at alternative sites. It is also shown that the availability of reliable runoff data is essential for implementation of the model for other similar urban catchments. In conclusion, the proposed model in this study will serve as a worthy tool in future urban catchment management studies.

Estudos de condições oceanográficas tornam-se imperativos a cada dia, tanto no fornecimento de dados para fins de pesquisa quanto para aplicações de engenharia. Tais usos variam desde a validação de modelos de previsão de ondas até a determinação de forças em estruturas offshore, bem como em condições de navegabilidade e operações logísticas. O uso dos movimentos do navio para determinar qual condição de mar os induziu, adotando a embarcação como um sensor, em analogia às boias oceanográficas, é uma das tecnologias disponíveis para a medição das condições oceanográficas. Esta destaca-se pela simplicidade na implementação, além de atender às necessidades da indústria petrolífera, uma vez que o interesse é voltado para eventos de ondas extremas, os quais são bem representados pela tecnologia considerada, como verificado nesta tese. A facilidade de obtenção de dados através da tecnologia mencionada, sem a necessidade de equipamentos adicionais { especialmente no caso de plataformas de petróleo devido à disponibilidade de bases inerciais em muitas embarcações deste tipo { foi essencial para garantir ao presente trabalho um conjunto de dados de campo composto por registros ininterruptos dos movimentos de uma plataforma FPSO durante dois anos, através do qual foi possível realizar estimativas das ondas em intervalos de trinta minutos. Esta rica base de dados, inédita na literatura especializada, aliada às estimativas fornecidas simultaneamente por um sistema de radar de ondas, permitiu um estudo detalhado das características e padrões dos espectros direcionais de onda e uma importante validação da aplicação da tecnologia em campo. Face às incertezas inerentes ao processo, no entanto, observa-se que, para um mesmo registro de movimentos, muitas soluções diferentes e quase equiprováveis podem ser obtidas, uma característica que favorece a aplicação de um método de inferência Bayesiana, afim de fornecer alguma informação a priori sobre as variáveis de estimação. Na presente abordagem, esta informação corresponde a uma suposição de suavidade dos espectros direcionais de onda a serem estimados, cujo grau é controlado pelos chamados hiperparâmetros do processo de inferência - parâmetros dentro do método que controlam a influência da informação a priori sobre a solução. Estudos prévios realizados na EPUSP demonstraram que o uso de hiperparâmetros fixos ou pré-calibrados é vantajoso para tornar o método de estimação operacionalmente aplicável, proporcionando um tempo de execução compatível com aplicações em tempo real. Dada a importância do papel desempenhado pela informação a priori na determinação de soluções viáveis no intervalo de incertezas do método, torna-se patente a necessidade de se definir valores apropriados para estes hiperparâmetros. Assim, neste trabalho, é apresentada uma metodologia de calibração para os hiperparâmetros baseada na dependência destes no período médio de onda e no parâmetro espectral de largura de banda. Esta nova abordagem traz dois aspectos inovadores para a pesquisa: O primeiro é o desenvolvimento de um método iterativo e autossuficiente capaz de identificar erros de estimação causados por incertezas no modelo de previsão de movimentos do navio. O segundo ponto é a capacidade do método de mitigar os erros encontrados, forçando a suavidade espectral ao longo do intervalo de frequências de onda. / Studies of oceanographic conditions become imperative every day, both in the provision of data for research purposes and for engineering applications. Such uses range from the validation of wave prediction models to the determination of forces in offshore structures, as well as navigability and logistical operations. The use of vessel movements to determine which is the condition induced by them, adopting the vessel as a sensor, in analogy to oceanographic buoys, is one of the available technologies for the measurement of oceanographic conditions. It stands out for the simplicity of the implementation, in addition it meets the needs of the oil industry, since the interest is focused on extreme wave events, which are well represented by the technology considered, as verified in this thesis. Ease of data attainment through the mentioned technology, without the need for additional equipment - especially in the case of oil platforms due to the availability of inertial bases in many vessels of this type - was essential to guarantee the present work the data set of field the FPSO platform for two years, through which it was possible to make estimates of the waves in intervals of thirty minutes. This rich database, unprecedented in the specialized literature, together with the estimates provided by a wave radar system, allowed a detailed study of the characteristics and patterns of the directional wave spectra and an important validation of the application of the technology in the field. Given the uncertainties inherent in the process, however, it can be observed that, for the same record of movements, many different and almost equiprobable solutions can be obtained, a feature that favors the application of a Bayesian inference method, in order to provide some information on the variables of estimation. In the present approach, this information corresponds to an assumption of smoothness of the directional wave spectra to be estimated, the degree of which is controlled by so-called hyperparameters of the inference process - parameters within the method that control the influence of a priori information on the solution. Previous studies conducted at EPUSP have demonstrated that the use of fixed or precalibrated hyperparameters is advantageous to make the estimation method operationally applicable, providing a runtime compatible with real-time applications. Given the importance of the role played by a priori information in determining viable solutions in the uncertainty range of the method, it becomes clear that it is necessary to define appropriate values for these hyperparameters. Thus, in this work, the calibration methodology for the hyperparameters is presented, based on the dependency of these on wave mean period and on bandwidth spectral parameter. The _rst is the development of an iterative, self-sufficient method, capable of identifying estimations errors caused by uncertainties on the ship\'s motions prediction model. The second is the ability of the method to mitigate the errors found, forcing spectral smoothness throughout the range of wave frequencies.

Two important relationships in parasitoid evolutionary ecology are those between adult size and fitness and between host quality and sex ratio. Sexually differential size-fitness relationships underlie predicted sex-ratio relationships. Despite each relationship receiving considerable attention, they have seldom been studied simultaneously or using field data. Here we report the biology of Anoplius viaticus paganus Dahlbom, a little known parasitoid of spiders, using field and laboratory data. We found that larger foraging females were able to select larger host spiders from the field, thus identifying a relatively novel component of the size-fitness relationship. Larger offspring developed from larger hosts and, in agreement with the prediction of the host quality model of sex allocation, were generally female. Data on the size-fitness relationship for males are lacking and, in common with many prior studies, we could not evaluate sexually differential size-fitness relationships as an explanation for the observed sex-ratio patterns. Nonetheless, A. v. paganus exhibited one of the strongest relationships between host size and offspring sex ratio yet reported.

No description available.