929 resultados para Distributed lag model


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The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

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Se presenta la implementación del modelo hidrológico distribuido de Témez sobre GRASS GIS. Este modelo se utiliza para la evaluación de recursos hídricos en régimen natural con paso mensual y para la totalidad del territorio español, tal como aparece en el Libro Blanco del Agua en España. A partir de las variables de entrada, precipitación y evapotranspiración potencial y los parámetros hidrológicos, el modelo obtiene los mapas de los distintos almacenamientos, humedad en el suelo y volumen de acuífero, y de las variables de salida del ciclo hidrológico, evapotranspiración y escorrentía total, obtenida esta última como suma de la escorrentía superficial y subterránea. El objetivo final del trabajo es la implementación de los componentes superficiales y subterráneos en el modelo hidrológico, desarrollando para ello un programa que hace funcional en GRASS GIS el modelo matemático en que se basa la evaluación de recursos hídricos

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Se presenta el análisis de sensibilidad de un modelo de percepción de marca y ajuste de la inversión en marketing desarrollado en el Laboratorio de Simulación de la Universidad del Rosario. Este trabajo de grado consta de una introducción al tema de análisis de sensibilidad y su complementario el análisis de incertidumbre. Se pasa a mostrar ambos análisis usando un ejemplo simple de aplicación del modelo mediante la aplicación exhaustiva y rigurosa de los pasos descritos en la primera parte. Luego se hace una discusión de la problemática de medición de magnitudes que prueba ser el factor más complejo de la aplicación del modelo en el contexto práctico y finalmente se dan conclusiones sobre los resultados de los análisis.

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We show that any invariant test for spatial autocorrelation in a spatial error or spatial lag model with equal weights matrix has power equal to size. This result holds under the assumption of an elliptical distribution. Under Gaussianity, we also show that any test whose power is larger than its size for at least one point in the parameter space must be biased.

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We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues.

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Now, more than ever, higher education institutions are reflecting on the need for flexible leadership models to help adapt to the fast changing academic environment. Rapid shifts in the sector are contributing to a kaleidoscopic ‘supercomplexity’ of challenges, structures, processes and value frameworks for academics who lead and for those who are led. How are institutions’ leadership structures and roles developing in response to these changes? And how do these responses affect academic staff in relation to their identity, status and career trajectory? This paper reports on a Leadership Foundation funded research project exploring the ways in which one UK institution has implemented a new ‘distributed’ leadership model. Crucially, the project examines the impact of the model on both those who are leaders and those being led.

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The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

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Esta tese é composta por três ensaios sobre testes empíricos de curvas de Phillips, curvas IS e a interação entre as políticas fiscal e monetária. O primeiro ensaio ("Curvas de Phillips: um Teste Abrangente") testa curvas de Phillips usando uma especificação autoregressiva de defasagem distribuída (ADL) que abrange a curva de Phillips Aceleracionista (APC), a curva de Phillips Novo Keynesiana (NKPC), a curva de Phillips Híbrida (HPC) e a curva de Phillips de Informação Rígida (SIPC). Utilizamos dados dos Estados Unidos (1985Q1--2007Q4) e do Brasil (1996Q1--2012Q2), usando o hiato do produto e alternativamente o custo marginal real como medida de pressão inflacionária. A evidência empírica rejeita as restrições decorrentes da NKPC, da HPC e da SIPC, mas não rejeita aquelas da APC. O segundo ensaio ("Curvas IS: um Teste Abrangente") testa curvas IS usando uma especificação ADL que abrange a curva IS Keynesiana tradicional (KISC), a curva IS Novo Keynesiana (NKISC) e a curva IS Híbrida (HISC). Utilizamos dados dos Estados Unidos (1985Q1--2007Q4) e do Brasil (1996Q1--2012Q2). A evidência empírica rejeita as restrições decorrentes da NKISC e da HISC, mas não rejeita aquelas da KISC. O terceiro ensaio ("Os Efeitos da Política Fiscal e suas Interações com a Política Monetária") analisa os efeitos de choques na política fiscal sobre a dinâmica da economia e a interação entre as políticas fiscal e monetária usando modelos SVARs. Testamos a Teoria Fiscal do Nível de Preços para o Brasil analisando a resposta do passivo do setor público a choques no superávit primário. Para a identificação híbrida, encontramos que não é possível distinguir empiricamente entre os regimes Ricardiano (Dominância Monetária) e não-Ricardiano (Dominância Fiscal). Entretanto, utilizando a identificação de restrições de sinais, existe evidência que o governo seguiu um regime Ricardiano (Dominância Monetária) de janeiro de 2000 a junho de 2008.

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A procedure for calculation of refrigerant mass flow rate is implemented in the distributed numerical model to simulate the flow in finned-tube coil dry-expansion evaporators, usually found in refrigeration and air-conditioning systems. Two-phase refrigerant flow inside the tubes is assumed to be one-dimensional, unsteady, and homogeneous. In themodel the effects of refrigerant pressure drop and the moisture condensation from the air flowing over the external surface of the tubes are considered. The results obtained are the distributions of refrigerant velocity, temperature and void fraction, tube-wall temperature, air temperature, and absolute humidity. The finite volume method is used to discretize the governing equations. Additionally, given the operation conditions and the geometric parameters, the model allows the calculation of the refrigerant mass flow rate. The value of mass flow rate is computed using the process of parameter estimation with the minimization method of Levenberg-Marquardt minimization. In order to validate the developed model, the obtained results using HFC-134a as a refrigerant are compared with available data from the literature.

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The constant increase of complexity in computer applications demands the development of more powerful hardware support for them. With processor's operational frequency reaching its limit, the most viable solution is the use of parallelism. Based on parallelism techniques and the progressive growth in the capacity of transistors integration in a single chip is the concept of MPSoCs (Multi-Processor System-on-Chip). MPSoCs will eventually become a cheaper and faster alternative to supercomputers and clusters, and applications developed for these high performance systems will migrate to computers equipped with MP-SoCs containing dozens to hundreds of computation cores. In particular, applications in the area of oil and natural gas exploration are also characterized by the high processing capacity required and would benefit greatly from these high performance systems. This work intends to evaluate a traditional and complex application of the oil and gas industry known as reservoir simulation, developing a solution with integrated computational systems in a single chip, with hundreds of functional unities. For this, as the STORM (MPSoC Directory-Based Platform) platform already has a shared memory model, a new distributed memory model were developed. Also a message passing library has been developed folowing MPI standard

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Objective: To investigate the lag structure effects from exposure to atmospheric pollution in acute outbursts in hospital admissions of paediatric rheumatic diseases (PRDs). Methods: Morbidity data were obtained from the Brazilian Hospital Information System in seven consecutive years, including admissions due to seven PRDs (juvenile idiopathic arthritis, systemic lupus erythematosus, dermatomyositis, Henoch-Schonlein purpura, polyarteritis nodosa, systemic sclerosis and ankylosing spondylitis). Cases with secondary diagnosis of respiratory diseases were excluded. Daily concentrations of inhaled particulate matter (PM10), sulphur dioxide (SO2) nitrogen dioxide (NO2), ozone (O-3) and carbon monoxide (CO) were evaluated. Generalized linear Poisson regression models controlling for short-term trend, seasonality, holidays, temperature and humidity were used. Lag structures and magnitude of air pollutants' effects were adopted to estimate restricted polynomial distributed lag models. Results: The total number of admissions due to acute outbursts PRD was 1,821. The SO2 interquartile range (7.79 mu g/m(3)) was associated with an increase of 1.98% (confidence interval 0.25-3.69) in the number of hospital admissions due to outcome studied after 14 days of exposure. This effect was maintained until day 17. Of note, the other pollutants, with the exception of O-3, showed an increase in the number of hospital admissions from the second week. Conclusion: This study is the first to demonstrate a delayed association between SO2 and PRD outburst, suggesting that oxidative stress reaction could trigger the inflammation of these diseases. Lupus (2012) 21, 526-533.

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Nella Regione Emilia-Romagna, la zona delle conoidi ha una valenza strategica essendo la principale fonte di approvvigionamento idropotabile per le utenze civili, oltre che sostegno per le attività industriali ed agricole. All’interno di questo contesto ci si è soffermati sulla provincia di Piacenza, scegliendo come aree di studio le Conoidi del Trebbia e dell’Arda, per valutare le dinamiche di ricarica naturale attraverso l’identificazione della relazione che intercorre fra (i) l’entità dei deflussi superficiali riferiti ai corsi idrici che alimentano le conoidi, e (ii) il livello piezometrico nei rispettivi acquiferi. L’analisi è stata condotta applicando il modello Auto-Regressive Distributed Lag (ARDL).

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Recent observed hydro-climatic changes in mountainous areas are of concern as they may directly affect capacity to fulfill water needs. The canton of Vaud in Western Switzerland is an example of such a region as it has experienced water shortage episodes during the past decade. Based on an integrated modeling framework, this study explores how hydro-climatic conditions and water needs could evolve in mountain environments and assesses their potential impacts on water stress by the 2060 horizon. Flows were simulated based on a daily semi-distributed hydrological model. Future changes were derived from Swiss climate scenarios based on two regional climate models. Regarding water needs, the authorities of the canton of Vaud provided a population growth scenario while irrigation and livestock trends followed a business-as-usual scenario. Currently, the canton of Vaud experiences moderate water stress from June to August, except in its Alpine area where no stress is noted. In the 2060 horizon, water needs could exceed 80% of the rivers' available resources in low- to mid-altitude environments in mid-summer. This arises from the combination of drier and warmer climate that leads to longer and more severe low flows, and increasing urban (+ 40%) and irrigation (+ 25%) water needs. Highlighting regional differences supports the development of sustainable development pathways to reduce water tensions. Based on a quantitative assessment, this study also calls for broader impact studies including water quality issues.

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What are the conditions under which some austerity programmes rely on substantial cuts to social spending? More specifically, do the partisan complexion and the type of government condition the extent to which austerity policies imply welfare state retrenchment? This article demonstrates that large budget consolidations tend to be associated with welfare state retrenchment. The findings support a partisan and a politico-institutionalist argument: (i) in periods of fiscal consolidation, welfare state retrenchment tends to be more pronounced under left-wing governments; (ii) since welfare state retrenchment is electorally and politically risky, it also tends to be more pronounced when pursued by a broad pro-reform coalition government. Therefore, the article shows that during budget consolidations implemented by left-wing broad coalition governments, welfare state retrenchment is greatest. Using long-run multipliers from autoregressive distributed lag models on 17 OECD countries during the 1982–2009 period, substantial support is found for these expectations.

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This study describes detailed partitioning of phytomass carbon (C) and soil organic carbon (SOC) for four study areas in discontinuous permafrost terrain, Northeast European Russia. The mean aboveground phytomass C storage is 0.7 kg C/m**2. Estimated landscape SOC storage in the four areas varies between 34.5 and 47.0 kg C/m**2 with LCC (land cover classification) upscaling and 32.5-49.0 kg C/m**2 with soil map upscaling. A nested upscaling approach using a Landsat thematic mapper land cover classification for the surrounding region provides estimates within 5 ± 5% of the local high-resolution estimates. Permafrost peat plateaus hold the majority of total and frozen SOC, especially in the more southern study areas. Burying of SOC through cryoturbation of O- or A-horizons contributes between 1% and 16% (mean 5%) of total landscape SOC. The effect of active layer deepening and thermokarst expansion on SOC remobilization is modeled for one of the four areas. The active layer thickness dynamics from 1980 to 2099 is modeled using a transient spatially distributed permafrost model and lateral expansion of peat plateau thermokarst lakes is simulated using geographic information system analyses. Active layer deepening is expected to increase the proportion of SOC affected by seasonal thawing from 29% to 58%. A lateral expansion of 30 m would increase the amount of SOC stored in thermokarst lakes/fens from 2% to 22% of all SOC. By the end of this century, active layer deepening will likely affect more SOC than thermokarst expansion, but the SOC stores vulnerable to thermokarst are less decomposed.