Alpine permafrost index map

The objective of this study is the production of an Alpine Permafrost Index Map (APIM) covering the entire European Alps. A unified statistical model that is based on Alpine-wide permafrost observations is used for debris and bedrock surfaces across the entire Alps. The explanatory variables of the model are mean annual air temperatures, potential incoming solar radiation and precipitation. Offset terms were applied to make model predictions for topographic and geomorphic conditions that differ from the terrain features used for model fitting. These offsets are based on literature review and involve some degree of subjective choice during model building. The assessment of the APIM is challenging because limited independent test data are available for comparison and these observations represent point information in a spatially highly variable topography. The APIM provides an index that describes the spatial distribution of permafrost and comes together with an interpretation key that helps to assess map uncertainties and to relate map contents to their actual expression in terrain. The map can be used as a first resource to estimate permafrost conditions at any given location in the European Alps in a variety of contexts such as research and spatial planning. Results show that Switzerland likely is the country with the largest permafrost area in the Alps, followed by Italy, Austria, France and Germany. Slovenia and Liechtenstein may have marginal permafrost areas. In all countries the permafrost area is expected to be larger than the glacier-covered area.

Phycoerythrin concentration during POLARSTERN cruises ANT-XXIV/4, ANT-XXV/1, and ANT-XXVI/4

Phycobiliproteins are a family of water-soluble pigment proteins that play an important role as accessory or antenna pigments and absorb in the green part of the light spectrum poorly used by chlorophyll a. The phycoerythrins (PEs) are one of four types of phycobiliproteins that are generally distinguished based on their absorption properties. As PEs are water soluble, they are generally not captured with conventional pigment analysis. Here we present a statistical model based on in situ measurements of three transatlantic cruises which allows us to derive relative PE concentration from standardized hyperspectral underwater radiance measurements (Lu). The model relies on Empirical Orthogonal Function (EOF) analysis of Lu spectra and, subsequently, a Generalized Linear Model with measured PE concentrations as the response variable and EOF loadings as predictor variables. The method is used to predict relative PE concentrations throughout the water column and to calculate integrated PE estimates based on those profiles.

An Intercomparison of Modelling Approaches for Simulating the Atmospheric Dispersion of Ammonia Emitted by Agricultural Sources

RESUMEN La dispersión del amoniaco (NH3) emitido por fuentes agrícolas en medias distancias, y su posterior deposición en el suelo y la vegetación, pueden llevar a la degradación de ecosistemas vulnerables y a la acidificación de los suelos. La deposición de NH3 suele ser mayor junto a la fuente emisora, por lo que los impactos negativos de dichas emisiones son generalmente mayores en esas zonas. Bajo la legislación comunitaria, varios estados miembros emplean modelos de dispersión inversa para estimar los impactos de las emisiones en las proximidades de las zonas naturales de especial conservación. Una revisión reciente de métodos para evaluar impactos de NH3 en distancias medias recomendaba la comparación de diferentes modelos para identificar diferencias importantes entre los métodos empleados por los distintos países de la UE. En base a esta recomendación, esta tesis doctoral compara y evalúa las predicciones de las concentraciones atmosféricas de NH3 de varios modelos bajo condiciones, tanto reales como hipotéticas, que plantean un potencial impacto sobre ecosistemas (incluidos aquellos bajo condiciones de clima Mediterráneo). En este sentido, se procedió además a la comparación y evaluación de varias técnicas de modelización inversa para inferir emisiones de NH3. Finalmente, se ha desarrollado un modelo matemático simple para calcular las concentraciones de NH3 y la velocidad de deposición de NH3 en ecosistemas vulnerables cercanos a una fuente emisora. La comparativa de modelos supuso la evaluación de cuatro modelos de dispersión (ADMS 4.1; AERMOD v07026; OPS-st v3.0.3 y LADD v2010) en un amplio rango de casos hipotéticos (dispersión de NH3 procedente de distintos tipos de fuentes agrícolas de emisión). La menor diferencia entre las concentraciones medias estimadas por los distintos modelos se obtuvo para escenarios simples. La convergencia entre las predicciones de los modelos fue mínima para el escenario relativo a la dispersión de NH3 procedente de un establo ventilado mecánicamente. En este caso, el modelo ADMS predijo concentraciones significativamente menores que los otros modelos. Una explicación de estas diferencias podríamos encontrarla en la interacción de diferentes “penachos” y “capas límite” durante el proceso de parametrización. Los cuatro modelos de dispersión fueron empleados para dos casos reales de dispersión de NH3: una granja de cerdos en Falster (Dinamarca) y otra en Carolina del Norte (EEUU). Las concentraciones medias anuales estimadas por los modelos fueron similares para el caso americano (emisión de granjas ventiladas de forma natural y balsa de purines). La comparación de las predicciones de los modelos con concentraciones medias anuales medidas in situ, así como la aplicación de los criterios establecidos para la aceptación estadística de los modelos, permitió concluir que los cuatro modelos se comportaron aceptablemente para este escenario. No ocurrió lo mismo en el caso danés (nave ventilada mecánicamente), en donde el modelo LADD no dio buenos resultados debido a la ausencia de procesos de “sobreelevacion de penacho” (plume-rise). Los modelos de dispersión dan a menudo pobres resultados en condiciones de baja velocidad de viento debido a que la teoría de dispersión en la que se basan no es aplicable en estas condiciones. En situaciones de frecuente descenso en la velocidad del viento, la actual guía de modelización propone usar un modelo que sea eficaz bajo dichas condiciones, máxime cuando se realice una valoración que tenga como objeto establecer una política de regularización. Esto puede no ser siempre posible debido a datos meteorológicos insuficientes, en cuyo caso la única opción sería utilizar un modelo más común, como la versión avanzada de los modelos Gausianos ADMS o AERMOD. Con el objetivo de evaluar la idoneidad de estos modelos para condiciones de bajas velocidades de viento, ambos modelos fueron utilizados en un caso con condiciones Mediterráneas. Lo que supone sucesivos periodos de baja velocidad del viento. El estudio se centró en la dispersión de NH3 procedente de una granja de cerdos en Segovia (España central). Para ello la concentración de NH3 media mensual fue medida en 21 localizaciones en torno a la granja. Se realizaron también medidas de concentración de alta resolución en una única localización durante una campaña de una semana. En este caso, se evaluaron dos estrategias para mejorar la respuesta del modelo ante bajas velocidades del viento. La primera se basó en “no zero wind” (NZW), que sustituyó periodos de calma con el mínimo límite de velocidad del viento y “accumulated calm emissions” (ACE), que forzaban al modelo a calcular las emisiones totales en un periodo de calma y la siguiente hora de no-calma. Debido a las importantes incertidumbres en los datos de entrada del modelo (inputs) (tasa de emisión de NH3, velocidad de salida de la fuente, parámetros de la capa límite, etc.), se utilizó el mismo caso para evaluar la incertidumbre en la predicción del modelo y valorar como dicha incertidumbre puede ser considerada en evaluaciones del modelo. Un modelo dinámico de emisión, modificado para el caso de clima Mediterráneo, fue empleado para estimar la variabilidad temporal en las emisiones de NH3. Así mismo, se realizó una comparativa utilizando las emisiones dinámicas y la tasa constante de emisión. La incertidumbre predicha asociada a la incertidumbre de los inputs fue de 67-98% del valor medio para el modelo ADMS y entre 53-83% del valor medio para AERMOD. La mayoría de esta incertidumbre se debió a la incertidumbre del ratio de emisión en la fuente (50%), seguida por la de las condiciones meteorológicas (10-20%) y aquella asociada a las velocidades de salida (5-10%). El modelo AERMOD predijo mayores concentraciones que ADMS y existieron más simulaciones que alcanzaron los criterios de aceptabilidad cuando se compararon las predicciones con las concentraciones medias anuales medidas. Sin embargo, las predicciones del modelo ADMS se correlacionaron espacialmente mejor con las mediciones. El uso de valores dinámicos de emisión estimados mejoró el comportamiento de ADMS, haciendo empeorar el de AERMOD. La aplicación de estrategias destinadas a mejorar el comportamiento de este último tuvo efectos contradictorios similares. Con el objeto de comparar distintas técnicas de modelización inversa, varios modelos (ADMS, LADD y WindTrax) fueron empleados para un caso no agrícola, una colonia de pingüinos en la Antártida. Este caso fue empleado para el estudio debido a que suponía la oportunidad de obtener el primer factor de emisión experimental para una colonia de pingüinos antárticos. Además las condiciones eran propicias desde el punto de vista de la casi total ausencia de concentraciones ambiente (background). Tras el trabajo de modelización existió una concordancia suficiente entre las estimaciones obtenidas por los tres modelos. De este modo se pudo definir un factor de emisión de para la colonia de 1.23 g NH3 por pareja criadora por día (con un rango de incertidumbre de 0.8-2.54 g NH3 por pareja criadora por día). Posteriores aplicaciones de técnicas de modelización inversa para casos agrícolas mostraron también un buen compromiso estadístico entre las emisiones estimadas por los distintos modelos. Con todo ello, es posible concluir que la modelización inversa es una técnica robusta para estimar tasas de emisión de NH3. Modelos de selección (screening) permiten obtener una rápida y aproximada estimación de los impactos medioambientales, siendo una herramienta útil para evaluaciones de impactos en tanto que permite eliminar casos que presentan un riesgo potencial de daño bajo. De esta forma, lo recursos del modelo pueden Resumen (Castellano) destinarse a casos en donde la posibilidad de daño es mayor. El modelo de Cálculo Simple de los Límites de Impacto de Amoniaco (SCAIL) se desarrolló para obtener una estimación de la concentración media de NH3 y de la tasa de deposición seca asociadas a una fuente agrícola. Está técnica de selección, basada en el modelo LADD, fue evaluada y calibrada con diferentes bases de datos y, finalmente, validada utilizando medidas independientes de concentraciones realizadas cerca de las fuentes. En general SCAIL dio buenos resultados de acuerdo a los criterios estadísticos establecidos. Este trabajo ha permitido definir situaciones en las que las concentraciones predichas por modelos de dispersión son similares, frente a otras en las que las predicciones difieren notablemente entre modelos. Algunos modelos nos están diseñados para simular determinados escenarios en tanto que no incluyen procesos relevantes o están más allá de los límites de su aplicabilidad. Un ejemplo es el modelo LADD que no es aplicable en fuentes con velocidad de salida significativa debido a que no incluye una parametrización de sobreelevacion del penacho. La evaluación de un esquema simple combinando la sobreelevacion del penacho y una turbulencia aumentada en la fuente mejoró el comportamiento del modelo. Sin embargo más pruebas son necesarias para avanzar en este sentido. Incluso modelos que son aplicables y que incluyen los procesos relevantes no siempre dan similares predicciones. Siendo las razones de esto aún desconocidas. Por ejemplo, AERMOD predice mayores concentraciones que ADMS para dispersión de NH3 procedente de naves de ganado ventiladas mecánicamente. Existe evidencia que sugiere que el modelo ADMS infraestima concentraciones en estas situaciones debido a un elevado límite de velocidad de viento. Por el contrario, existen evidencias de que AERMOD sobreestima concentraciones debido a sobreestimaciones a bajas Resumen (Castellano) velocidades de viento. Sin embrago, una modificación simple del pre-procesador meteorológico parece mejorar notablemente el comportamiento del modelo. Es de gran importancia que estas diferencias entre las predicciones de los modelos sean consideradas en los procesos de evaluación regulada por los organismos competentes. Esto puede ser realizado mediante la aplicación del modelo más útil para cada caso o, mejor aún, mediante modelos múltiples o híbridos. ABSTRACT Short-range atmospheric dispersion of ammonia (NH3) emitted by agricultural sources and its subsequent deposition to soil and vegetation can lead to the degradation of sensitive ecosystems and acidification of the soil. Atmospheric concentrations and dry deposition rates of NH3 are generally highest near the emission source and so environmental impacts to sensitive ecosystems are often largest at these locations. Under European legislation, several member states use short-range atmospheric dispersion models to estimate the impact of ammonia emissions on nearby designated nature conservation sites. A recent review of assessment methods for short-range impacts of NH3 recommended an intercomparison of the different models to identify whether there are notable differences to the assessment approaches used in different European countries. Based on this recommendation, this thesis compares and evaluates the atmospheric concentration predictions of several models used in these impact assessments for various real and hypothetical scenarios, including Mediterranean meteorological conditions. In addition, various inverse dispersion modelling techniques for the estimation of NH3 emissions rates are also compared and evaluated and a simple screening model to calculate the NH3 concentration and dry deposition rate at a sensitive ecosystem located close to an NH3 source was developed. The model intercomparison evaluated four atmospheric dispersion models (ADMS 4.1; AERMOD v07026; OPS-st v3.0.3 and LADD v2010) for a range of hypothetical case studies representing the atmospheric dispersion from several agricultural NH3 source types. The best agreement between the mean annual concentration predictions of the models was found for simple scenarios with area and volume sources. The agreement between the predictions of the models was worst for the scenario representing the dispersion from a mechanically ventilated livestock house, for which ADMS predicted significantly smaller concentrations than the other models. The reason for these differences appears to be due to the interaction of different plume-rise and boundary layer parameterisations. All four dispersion models were applied to two real case studies of dispersion of NH3 from pig farms in Falster (Denmark) and North Carolina (USA). The mean annual concentration predictions of the models were similar for the USA case study (emissions from naturally ventilated pig houses and a slurry lagoon). The comparison of model predictions with mean annual measured concentrations and the application of established statistical model acceptability criteria concluded that all four models performed acceptably for this case study. This was not the case for the Danish case study (mechanically ventilated pig house) for which the LADD model did not perform acceptably due to the lack of plume-rise processes in the model. Regulatory dispersion models often perform poorly in low wind speed conditions due to the model dispersion theory being inapplicable at low wind speeds. For situations with frequent low wind speed periods, current modelling guidance for regulatory assessments is to use a model that can handle these conditions in an acceptable way. This may not always be possible due to insufficient meteorological data and so the only option may be to carry out the assessment using a more common regulatory model, such as the advanced Gaussian models ADMS or AERMOD. In order to assess the suitability of these models for low wind conditions, they were applied to a Mediterranean case study that included many periods of low wind speed. The case study was the dispersion of NH3 emitted by a pig farm in Segovia, Central Spain, for which mean monthly atmospheric NH3 concentration measurements were made at 21 locations surrounding the farm as well as high-temporal-resolution concentration measurements at one location during a one-week campaign. Two strategies to improve the model performance for low wind speed conditions were tested. These were ‘no zero wind’ (NZW), which replaced calm periods with the minimum threshold wind speed of the model and ‘accumulated calm emissions’ (ACE), which forced the model to emit the total emissions during a calm period during the first subsequent non-calm hour. Due to large uncertainties in the model input data (NH3 emission rates, source exit velocities, boundary layer parameters), the case study was also used to assess model prediction uncertainty and assess how this uncertainty can be taken into account in model evaluations. A dynamic emission model modified for the Mediterranean climate was used to estimate the temporal variability in NH3 emission rates and a comparison was made between the simulations using the dynamic emissions and a constant emission rate. Prediction uncertainty due to model input uncertainty was 67-98% of the mean value for ADMS and between 53-83% of the mean value for AERMOD. Most of this uncertainty was due to source emission rate uncertainty (~50%), followed by uncertainty in the meteorological conditions (~10-20%) and uncertainty in exit velocities (~5-10%). AERMOD predicted higher concentrations than ADMS and more of the simulations met the model acceptability criteria when compared with the annual mean measured concentrations. However, the ADMS predictions were better correlated spatially with the measurements. The use of dynamic emission estimates improved the performance of ADMS but worsened the performance of AERMOD and the application of strategies to improved model performance had similar contradictory effects. In order to compare different inverse modelling techniques, several models (ADMS, LADD and WindTrax) were applied to a non-agricultural case study of a penguin colony in Antarctica. This case study was used since it gave the opportunity to provide the first experimentally-derived emission factor for an Antarctic penguin colony and also had the advantage of negligible background concentrations. There was sufficient agreement between the emission estimates obtained from the three models to define an emission factor for the penguin colony (1.23 g NH3 per breeding pair per day with an uncertainty range of 0.8-2.54 g NH3 per breeding pair per day). This emission estimate compared favourably to the value obtained using a simple micrometeorological technique (aerodynamic gradient) of 0.98 g ammonia per breeding pair per day (95% confidence interval: 0.2-2.4 g ammonia per breeding pair per day). Further application of the inverse modelling techniques for a range of agricultural case studies also demonstrated good agreement between the emission estimates. It is concluded, therefore, that inverse dispersion modelling is a robust technique for estimating NH3 emission rates. Screening models that can provide a quick and approximate estimate of environmental impacts are a useful tool for impact assessments because they can be used to filter out cases that potentially have a minimal environmental impact allowing resources to be focussed on more potentially damaging cases. The Simple Calculation of Ammonia Impact Limits (SCAIL) model was developed as a screening model to provide an estimate of the mean NH3 concentration and dry deposition rate downwind of an agricultural source. This screening tool, based on the LADD model, was evaluated and calibrated with several experimental datasets and then validated using independent concentration measurements made near sources. Overall SCAIL performed acceptably according to established statistical criteria. This work has identified situations where the concentration predictions of dispersion models are similar and other situations where the predictions are significantly different. Some models are simply not designed to simulate certain scenarios since they do not include the relevant processes or are beyond the limits of their applicability. An example is the LADD model that is not applicable to sources with significant exit velocity since the model does not include a plume-rise parameterisation. The testing of a simple scheme combining a momentum-driven plume rise and increased turbulence at the source improved model performance, but more testing is required. Even models that are applicable and include the relevant process do not always give similar predictions and the reasons for this need to be investigated. AERMOD for example predicts higher concentrations than ADMS for dispersion from mechanically ventilated livestock housing. There is evidence to suggest that ADMS underestimates concentrations in these situations due to a high wind speed threshold. Conversely, there is also evidence that AERMOD overestimates concentrations in these situations due to overestimation at low wind speeds. However, a simple modification to the meteorological pre-processor appears to improve the performance of the model. It is important that these differences between the predictions of these models are taken into account in regulatory assessments. This can be done by applying the most suitable model for the assessment in question or, better still, using multiple or hybrid models.

Reliability analysis based on non-dimensional parameters

A reliability analysis method is proposed that starts with the identification of all variables involved. These are divided in three groups: (a) variables fixed by codes, as loads and strength project values, and their corresponding partial safety coefficients, (b) geometric variables defining the dimension of the main elements involved, (c) the cost variables, including the possible damages caused by failure, (d) the random variables as loads, strength, etc., and (e)the variables defining the statistical model, as the family of distribution and its corresponding parameters. Once the variables are known, the II-theorem is used to obtain a minimum equivalent set of non-dimensional variables, which is used to define the limit states. This allows a reduction in the number of variables involved and a better understanding of their coupling effects. Two minimum cost criteria are used for selecting the project dimensions. One is based on a bounded-probability of failure, and the other on a total cost, including the damages of the possible failure. Finally, the method is illustrated by means of an application.

Predicción del remonte extremo en playas : aplicación a los sectores litorales de la costa española

El remonte extremo o remonte del 2% es un parámetro clave en la ingeniería costera dado que permite acometer actuaciones en las playas bajo criterios de sostenibilidad económico y socioambiental. Estas actuaciones van desde el diseño de estructuras en el trasdós de la playa a planes de actuación urbanística en la costa tal que se determine adecuadamente los límites de dominio público. El adecuado diseño de estas actuaciones adquiere más relevancia hoy en día debido a las nuevas amenazas que se ponen de relieve debido al cambio climático, y que en el caso concreto de la costa se materializa en inundaciones que provocan pérdidas económicas. Estudios precedentes han realizado ensayos in situ o en modelo físico para la determinación del remonte extremo en playas. Al comparar estas formulaciones la dispersión es alta lo que implica que la precisión en la obtención del remonte no sea suficiente. Esta dispersión se justifica debido al amplio espectro de playas existentes y la alta variabilidad del clima marítimo. Este problema cobra más relevancia debido a las actuaciones preventivas o correctivas a acometer frente al cambio climático bajo un criterio de sostenibilidad. Con el fin de realizar actuaciones sostenibles bajo el contexto actual del probable aumento de inundaciones costeras por cambio climático no deben obtenerse ni magnitudes sobredimensionadas con el consecuente consumo de recursos y afección a las actividades económicas, ni magnitudes subestimadas que pongan en riesgo la estabilidad y/o la funcionalidad de las actuaciones para un periodo de diseño. El principal objetivo de esta tesis es proponer una formulación de aplicación en la obtención del remonte extremo tal que se cumplan los criterios de seguridad para el servicio y funcionalidad de la obra y los criterios de sostenibilidad económico y socio-ambiental que se requieren hoy en día. Es decir, una fórmula que no sobredimensione el cálculo de este valor pero que pueda cubrir la casuística que acontece en las distintas tipologías de playas. Complementariamente a este objetivo se ejemplifica la aplicación de estas formulaciones en casos reales tal que se reduzca la incertidumbre y ambigüedad en la obtención de las variables independientes de las formulaciones. Para la consecución de estos objetivos se realiza un estado del arte en el que se estudia tanto los estudios estadísticos en la obtención de este parámetro como los modelos numéricos propuestos para ello, tal que se deduzca la mejor línea de investigación en la consecución del fin de esta tesis. Tras este estudio del arte se concluye que la mejor línea de investigación sigue la vía estadística y se diseña un modelo físico con fondo de arena en contraste con modelos físicos con fondo impermeable fijo. Los resultados de dicho modelo se han comparado con las formulaciones precedentes y se proponen las fórmulas de aplicación más convenientes para la obtención del remonte extremo. Complementariamente a la propuesta de formulaciones se desarrolla una metodología de aplicación de dichas formulaciones a casos de la costa española que ejemplifican convenientemente su uso para una adecuada predicción de este valor en las playas. The extreme runup is a key parameter in coastal management. This parameter allows to develop sustainability actions at the coast that meet economical and environmental criteria. At the coast the actions can be either design of structures at the shore or actions plans delimiting reclamation areas. The climate change has given more relevance to accomplish an appropriate design for the coastal management actions. At the coast the threaten are mainly focused on more frequent floods that cause economic losses. Previous studies have carried out field or physical model experiments to accomplish an equation for the extreme runup prediction. Although dispersion remains high when comparing the different proposals so the accuracy in the prediction might be risky. This scattering comes from the wide sort of beaches and the high variability of the maritime climate. The new actions that are needed to develop to counteract the effects of the climate change need a more efficient criteria. Hence formulations should not overestimate or underestimate the values of the extreme runup. The overestimation implies to consume resources that are not needed and the underestimation means in a structure risk to support safely the loads. The main goal of this thesis is to propose a formulation for the extreme runup prediction so the safety of the structure can be accomplished but at the same time the sustainability of the action is ensured under economical and environmental criteria that are demanded nowadays. So the formulation does not overestimate the extreme value but cover with enough confidence the different sort of beaches. The application of the formulation is also explained in order to reduce uncertainty when the input values are obtained. In order to accomplish the goal of this research firstly a literature review is done. Statistical and numerical models are studied. The statistical model is selected as the most convenient research guideline. In order to obtain runup results a physical model with sand bed is carried out. The bed differs from those that used impermeable slope in previous experiments. Once the results are obtained they are compared with the previous equations and a final formulation is proposed. Finally a methodology to apply the deduced formulation to the Spanish beaches is addressed.

A new label fusion method using graph cuts: application to hippocampus segmentation

The aim of this paper is to develop a probabilistic modeling framework for the segmentation of structures of interest from a collection of atlases. Given a subset of registered atlases into the target image for a particular Region of Interest (ROI), a statistical model of appearance and shape is computed for fusing the labels. Segmentations are obtained by minimizing an energy function associated with the proposed model, using a graph-cut technique. We test different label fusion methods on publicly available MR images of human brains.

Desarrollo de metodologías para mejorar la estimación de los hidrogramas de diseño para el cálculo de los órganos de desagüe de las presas

En la presente Tesis se ha llevado a cabo el contraste y desarrollo de metodologías que permitan mejorar el cálculo de las avenidas de proyecto y extrema empleadas en el cálculo de la seguridad hidrológica de las presas. En primer lugar se ha abordado el tema del cálculo de las leyes de frecuencia de caudales máximos y su extrapolación a altos periodos de retorno. Esta cuestión es de gran relevancia, ya que la adopción de estándares de seguridad hidrológica para las presas cada vez más exigentes, implica la utilización de periodos de retorno de diseño muy elevados cuya estimación conlleva una gran incertidumbre. Es importante, en consecuencia incorporar al cálculo de los caudales de diseño todas la técnicas disponibles para reducir dicha incertidumbre. Asimismo, es importante hacer una buena selección del modelo estadístico (función de distribución y procedimiento de ajuste) de tal forma que se garantice tanto su capacidad para describir el comportamiento de la muestra, como para predecir de manera robusta los cuantiles de alto periodo de retorno. De esta forma, se han realizado estudios a escala nacional con el objetivo de determinar el esquema de regionalización que ofrece mejores resultados para las características hidrológicas de las cuencas españolas, respecto a los caudales máximos anuales, teniendo en cuenta el numero de datos disponibles. La metodología utilizada parte de la identificación de regiones homogéneas, cuyos límites se han determinado teniendo en cuenta las características fisiográficas y climáticas de las cuencas, y la variabilidad de sus estadísticos, comprobando posteriormente su homogeneidad. A continuación, se ha seleccionado el modelo estadístico de caudales máximos anuales con un mejor comportamiento en las distintas zonas de la España peninsular, tanto para describir los datos de la muestra como para extrapolar a los periodos de retorno más altos. El proceso de selección se ha basado, entre otras cosas, en la generación sintética de series de datos mediante simulaciones de Monte Carlo, y el análisis estadístico del conjunto de resultados obtenido a partir del ajuste de funciones de distribución a estas series bajo distintas hipótesis. Posteriormente, se ha abordado el tema de la relación caudal-volumen y la definición de los hidrogramas de diseño en base a la misma, cuestión que puede ser de gran importancia en el caso de presas con grandes volúmenes de embalse. Sin embargo, los procedimientos de cálculo hidrológico aplicados habitualmente no tienen en cuenta la dependencia estadística entre ambas variables. En esta Tesis se ha desarrollado un procedimiento para caracterizar dicha dependencia estadística de una manera sencilla y robusta, representando la función de distribución conjunta del caudal punta y el volumen en base a la función de distribución marginal del caudal punta y la función de distribución condicionada del volumen respecto al caudal. Esta última se determina mediante una función de distribución log-normal, aplicando un procedimiento de ajuste regional. Se propone su aplicación práctica a través de un procedimiento de cálculo probabilístico basado en la generación estocástica de un número elevado de hidrogramas. La aplicación a la seguridad hidrológica de las presas de este procedimiento requiere interpretar correctamente el concepto de periodo de retorno aplicado a variables hidrológicas bivariadas. Para ello, se realiza una propuesta de interpretación de dicho concepto. El periodo de retorno se entiende como el inverso de la probabilidad de superar un determinado nivel de embalse. Al relacionar este periodo de retorno con las variables hidrológicas, el hidrograma de diseño de la presa deja de ser un único hidrograma para convertirse en una familia de hidrogramas que generan un mismo nivel máximo en el embalse, representados mediante una curva en el plano caudal volumen. Esta familia de hidrogramas de diseño depende de la propia presa a diseñar, variando las curvas caudal-volumen en función, por ejemplo, del volumen de embalse o la longitud del aliviadero. El procedimiento propuesto se ilustra mediante su aplicación a dos casos de estudio. Finalmente, se ha abordado el tema del cálculo de las avenidas estacionales, cuestión fundamental a la hora de establecer la explotación de la presa, y que puede serlo también para estudiar la seguridad hidrológica de presas existentes. Sin embargo, el cálculo de estas avenidas es complejo y no está del todo claro hoy en día, y los procedimientos de cálculo habitualmente utilizados pueden presentar ciertos problemas. El cálculo en base al método estadístico de series parciales, o de máximos sobre un umbral, puede ser una alternativa válida que permite resolver esos problemas en aquellos casos en que la generación de las avenidas en las distintas estaciones se deba a un mismo tipo de evento. Se ha realizado un estudio con objeto de verificar si es adecuada en España la hipótesis de homogeneidad estadística de los datos de caudal de avenida correspondientes a distintas estaciones del año. Asimismo, se han analizado los periodos estacionales para los que es más apropiado realizar el estudio, cuestión de gran relevancia para garantizar que los resultados sean correctos, y se ha desarrollado un procedimiento sencillo para determinar el umbral de selección de los datos de tal manera que se garantice su independencia, una de las principales dificultades en la aplicación práctica de la técnica de las series parciales. Por otra parte, la aplicación practica de las leyes de frecuencia estacionales requiere interpretar correctamente el concepto de periodo de retorno para el caso estacional. Se propone un criterio para determinar los periodos de retorno estacionales de forma coherente con el periodo de retorno anual y con una distribución adecuada de la probabilidad entre las distintas estaciones. Por último, se expone un procedimiento para el cálculo de los caudales estacionales, ilustrándolo mediante su aplicación a un caso de estudio. The compare and develop of a methodology in order to improve the extreme flow estimation for dam hydrologic security has been developed. First, the work has been focused on the adjustment of maximum peak flows distribution functions from which to extrapolate values for high return periods. This has become a major issue as the adoption of stricter standards on dam hydrologic security involves estimation of high design return periods which entails great uncertainty. Accordingly, it is important to incorporate all available techniques for the estimation of design peak flows in order to reduce this uncertainty. Selection of the statistical model (distribution function and adjustment method) is also important since its ability to describe the sample and to make solid predictions for high return periods quantiles must be guaranteed. In order to provide practical application of previous methodologies, studies have been developed on a national scale with the aim of determining a regionalization scheme which features best results in terms of annual maximum peak flows for hydrologic characteristics of Spanish basins taking into account the length of available data. Applied methodology starts with the delimitation of regions taking into account basin’s physiographic and climatic characteristics and the variability of their statistical properties, and continues with their homogeneity testing. Then, a statistical model for maximum annual peak flows is selected with the best behaviour for the different regions in peninsular Spain in terms of describing sample data and making solid predictions for high return periods. This selection has been based, among others, on synthetic data series generation using Monte Carlo simulations and statistical analysis of results from distribution functions adjustment following different hypothesis. Secondly, the work has been focused on the analysis of the relationship between peak flow and volume and how to define design flood hydrographs based on this relationship which can be highly important for large volume reservoirs. However, commonly used hydrologic procedures do not take statistical dependence between these variables into account. A simple and sound method for statistical dependence characterization has been developed by the representation of a joint distribution function of maximum peak flow and volume which is based on marginal distribution function of peak flow and conditional distribution function of volume for a given peak flow. The last one is determined by a regional adjustment procedure of a log-normal distribution function. Practical application is proposed by a probabilistic estimation procedure based on stochastic generation of a large number of hydrographs. The use of this procedure for dam hydrologic security requires a proper interpretation of the return period concept applied to bivariate hydrologic data. A standard is proposed in which it is understood as the inverse of the probability of exceeding a determined reservoir level. When relating return period and hydrological variables the only design flood hydrograph changes into a family of hydrographs which generate the same maximum reservoir level and that are represented by a curve in the peak flow-volume two-dimensional space. This family of design flood hydrographs depends on the dam characteristics as for example reservoir volume or spillway length. Two study cases illustrate the application of the developed methodology. Finally, the work has been focused on the calculation of seasonal floods which are essential when determining the reservoir operation and which can be also fundamental in terms of analysing the hydrologic security of existing reservoirs. However, seasonal flood calculation is complex and nowadays it is not totally clear. Calculation procedures commonly used may present certain problems. Statistical partial duration series, or peaks over threshold method, can be an alternative approach for their calculation that allow to solve problems encountered when the same type of event is responsible of floods in different seasons. A study has been developed to verify the hypothesis of statistical homogeneity of peak flows for different seasons in Spain. Appropriate seasonal periods have been analyzed which is highly relevant to guarantee correct results. In addition, a simple procedure has been defined to determine data selection threshold on a way that ensures its independency which is one of the main difficulties in practical application of partial series. Moreover, practical application of seasonal frequency laws requires a correct interpretation of the concept of seasonal return period. A standard is proposed in order to determine seasonal return periods coherently with the annual return period and with an adequate seasonal probability distribution. Finally a methodology is proposed to calculate seasonal peak flows. A study case illustrates the application of the proposed methodology.

Cortisol fecal em ovinos: curva de excreção e estabilidade

O presente estudo foi dividido em dois experimentos, tendo como objetivo determinar a curva de excreção do cortisol fecal e sua estabilidade nas fezes perante exposição à diferentes períodos de tempo e temperatura entre as colheitas e análises, correlacionando os níveis de cortisol fecal com o pico de cortisol sanguíneo. No experimento 1, seis fêmeas mestiças (Dorper x Santa Inês) tiveram suas fezes totais colhidas durante 24 horas após a aplicação do hormônio adrenocorticotrófico (ACTH), além de colheitas de sangue realizadas antes da aplicação do ACTH, 60, 120 e 300 minutos depois; durante as quais foram atribuídos escores de reatividade para cada animal. Logo após as análises foi iniciado o experimento 2, no qual 9 cordeiros mestiços (Dorper x Santa Inês) foram submetidos a uma situação de estresse térmico durante os horários das 11 às 15 horas da tarde, tendo suas fezes colhidas às 23 horas do mesmo dia. Após a colheita, as fezes foram agrupadas e homogeneizadas em três grupos distintos, de onde retiraram-se alíquotas referentes aos tratamentos propostos: três temperaturas (15°, 25° e 35°) e quatro tempos (1, 3, 6 e 12 horas). Os dados da curva de excreção foram analisados por ANOVA, bem como pela correlação entre os valores de cortisol sanguíneo, fecal e reatividade. Para análise da estabilidade foi utilizada ANOVA multifatorial com dois fatores (temperatura e intervalo de tempo). Para avaliação das variáveis comportamentais foi realizada a transformação de escala dos dados para \"arco-seno raiz de porcentagem\", procedendo-se à análise de variância. O modelo estatístico contemplou os efeitos de dia (1, 2 e 3) com análise individual por animal. Os parâmetros de cortisol sanguíneo, frequência respiratória e temperatura retal foram analisados pelo teste t e correlação de Pearson. Todas as comparações de médias foram realizadas por teste F e teste t (PDIFF). A reatividade durante a colheita não exerceu efeito significativo sobre os valores de cortisol sanguíneo, os quais demonstraram médias maiores 60 minutos após a aplicação do ACTH e, após 300 minutos as ovelhas apresentaram níveis de cortisol considerados normais para ovinos sem estresse. Por outro lado, o pico de cortisol nas fezes foi verificado aproximadamente 10 a 12 horas após o pico de cortisol no sangue, não sendo verificadas diminuições significativas nas concentrações que indicassem o retorno aos níveis basais durante o período de 24 horas (P>0,05). Não foram observadas diferenças significativas entre os tempos e temperaturas aos quais as amostras de fezes foram submetidas (P>0,05), verificando-se uma tendência a manutenção da concentração do cortisol fecal em ovinos durante o período de 12 horas após a colheita.

Homogeneous Spatial Units (HSU) - a Pan-European geographical basis for environmental and socio-economic modelling

The spatial data set delineates areas with similar environmental properties regarding soil, terrain morphology, climate and affiliation to the same administrative unit (NUTS3 or comparable units in size) at a minimum pixel size of 1km2. The scope of developing this data set is to provide a link between spatial environmental information (e.g. soil properties) and statistical data (e.g. crop distribution) available at administrative level. Impact assessment of agricultural management on emissions of pollutants or radiative active gases, or analysis regarding the influence of agricultural management on the supply of ecosystem services, require the proper spatial coincidence of the driving factors. The HSU data set provides e.g. the link between the agro-economic model CAPRI and biophysical assessment of environmental impacts (updating previously spatial units, Leip et al. 2008), for the analysis of policy scenarios. Recently, a statistical model to disaggregate crop information available from regional statistics to the HSU has been developed (Lamboni et al. 2016). The HSU data set consists of the spatial layers provided in vector and raster format as well as attribute tables with information on the properties of the HSU. All input data for the delineation the HSU is publicly available. For some parameters the attribute tables provide the link between the HSU data set and e.g. the soil map(s) rather than the data itself. The HSU data set is closely linked the USCIE data set.

The North Sea autumn spawning Herring (Clupea harengus L.) Spawning Component Abundance Index (SCAI)

The North Sea autumn-spawning herring (Clupea harengus) stock consists of a set of different spawning components. The dynamics of the entire stock have been well characterized, but although time-series of larval abundance indices are available for the individual components, study of the dynamics at the component level has historically been hampered by missing observations and high sampling noise. A simple state-space statistical model is developed that is robust to these problems, gives a good fit to the data, and proves capable of both handling and predicting missing observations well. Furthermore, the sum of the fitted abundance indices across all components proves an excellent proxy for the biomass of the total stock, even though the model utilizes information at the individual-component level. The Orkney-Shetland component appears to have recovered faster from historic depletion events than the other components, whereas the Downs component has been the slowest. These differences give rise to changes in stock composition, which are shown to vary widely within a relatively short time. The modelling framework provides a valuable tool for studying and monitoring the dynamics of the individual components of the North Sea herring stock.

Social and behavioural determinants of early childhood caries

Background: To investigate the association between selected social and behavioural (infant feeding and preventive dental practices) variables and the presence of early childhood caries in preschool children within the north Brisbane region. Methods: A cross sectional sample of 2515 children aged four to five years were examined in a preschool setting using prevalence (percentage with caries) and severity (dmft) indices. A self-administered questionnaire obtained information regarding selected social and behavioural variables. The data were modelled using multiple logistic regression analysis at the 5 per cent level of significance. Results: The final explanatory model for caries presence in four to five year old children included the variables breast feeding from three to six months of age (OR=0.7, CI=0.5, 1.0), sleeping with the bottle (OR=1.9, CI=1.5, 2.4), sipping from the bottle (OR=1.6, CI=1.2, 2.0), ethnicity other than Caucasian (OR=1.9, CI=1.4, 2.5), annual family income $20,000-$35,000 (OR = 1.7, CI=1.3, 2.3) and annual family income less than $20,000 (OR=2.1, CI=1.5, 2.8). Conclusion: A statistical model for early childhood caries in preschool children within the north Brisbane region has been constructed using selected social and behavioural determinants. Epidemiological data can be used for improved public oral health service planning and resource allocation within the region.

A vulnerability analysis of the temperate forests of south central Chile A vulnerability analysis of the temperate forests of south central Chile. Biological Conservation, 122 2005: 9-21.

Areas of the landscape that are priorities for conservation should be those that are both vulnerable to threatening processes and that if lost or degraded, will result in conservation targets being compromised. While much attention is directed towards understanding the patterns of biodiversity, much less is given to determining the areas of the landscape most vulnerable to threats. We assessed the relative vulnerability of remaining areas of native forest to conversion to plantations in the ecologically significant temperate rainforest region of south central Chile. The area of the study region is 4.2 million ha and the extent of plantations is approximately 200000 ha. First, the spatial distribution of native forest conversion to plantations was determined. The variables related to the spatial distribution of this threatening process were identified through the development of a classification tree and the generation of a multivariate. spatially explicit, statistical model. The model of native forest conversion explained 43% of the deviance and the discrimination ability of the model was high. Predictions were made of where native forest conversion is likely to occur in the future. Due to patterns of climate, topography, soils and proximity to infrastructure and towns, remaining forest areas differ in their relative risk of being converted to plantations. Another factor that may increase the vulnerability of remaining native forest in a subset of the study region is the proposed construction of a highway. We found that 90% of the area of existing plantations within this region is within 2.5 km of roads. When the predictions of native forest conversion were recalculated accounting for the construction of this highway, it was found that: approximately 27000 ha of native forest had an increased probability of conversion. The areas of native forest identified to be vulnerable to conversion are outside of the existing reserve network. (C) 2004 Elsevier Ltd. All tights reserved.

Multiquantum eigenstates of a linear chain of coupled qubits

We present a technique to identify exact analytic expressions for the multiquantum eigenstates of a linear chain of coupled qubits. A choice of Hilbert subspaces is described that allows an exact solution of the stationary Schrodinger equation without imposing periodic boundary conditions and without neglecting end effects, fully including the dipole-dipole nearest-neighbor interaction between the atoms. The treatment is valid for an arbitrary coherent excitation in the atomic system, any number of atoms, any size of the chain relative to the resonant wavelength and arbitrary initial conditions of the atomic system. The procedure we develop is general enough to be adopted for the study of excitation in an arbitrary array of atoms including spin chains and one-dimensional Bose-Einstein condensates.

Ultra-cold fermions in optical lattices

We summarize recent theoretical results for the signatures of strongly correlated ultra-cold fermions in optical lattices. In particular, we focus on collective mode calculations, where a sharp decrease in collective mode frequency is predicted at the onset of the Mott metal-insulator transition; and correlation functions at finite temperature, where we employ a new exact technique that applies the stochastic gauge technique with a Gaussian operator basis.

Detecting finite bandwidth periodic signals in stationary noise using the signal coherence spectrum

All signals that appear to be periodic have some sort of variability from period to period regardless of how stable they appear to be in a data plot. A true sinusoidal time series is a deterministic function of time that never changes and thus has zero bandwidth around the sinusoid's frequency. A zero bandwidth is impossible in nature since all signals have some intrinsic variability over time. Deterministic sinusoids are used to model cycles as a mathematical convenience. Hinich [IEEE J. Oceanic Eng. 25 (2) (2000) 256-261] introduced a parametric statistical model, called the randomly modulated periodicity (RMP) that allows one to capture the intrinsic variability of a cycle. As with a deterministic periodic signal the RMP can have a number of harmonics. The likelihood ratio test for this model when the amplitudes and phases are known is given in [M.J. Hinich, Signal Processing 83 (2003) 1349-13521. A method for detecting a RMP whose amplitudes and phases are unknown random process plus a stationary noise process is addressed in this paper. The only assumption on the additive noise is that it has finite dependence and finite moments. Using simulations based on a simple RMP model we show a case where the new method can detect the signal when the signal is not detectable in a standard waterfall spectrograrn display. (c) 2005 Elsevier B.V. All rights reserved.