Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study was applied to the Bacchiglione catchment, located in Italy. The first methodological step was to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model were implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge were generated, as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location were assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that, overall, the assimilation of uncertain observations can improve the hydrologic model performance. In particular, it was found that the model structure is an important factor, of difficult characterization, since can induce different forecasts in terms of outflow discharge. This study is partly supported by the FP7 EU Project WeSenseIt.

Parameterization Of Turbulence Models Using 3DVAR Data Assimilation

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.

CO2 assimilation, photosynthetic light response curves, and water relations of 'Pêra' sweet orange plants infected with Xylella fastidiosa

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Nitrogen assimilation in Citrus based on CitEST data mining

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Influence of diet on assimilation and turnover of C-13 in the tissues of broiler chickens

1. The C-13 turnover rates of the liver and thoracic pectoral muscle of growing broilers were determined by feeding diets with varying C-13 content.2. Male chicks ( 1- d- old) were subjected to treatments based on free choice of 5 different mixes of energy and protein sources from plants with C-3 and C-4 photosynthetic pathways that had differing C-13 content. Rice bran ( R) and soybean meal ( S) were the C-3 sources, while maize ( C) and maize gluten meal ( G) were the C-4 sources. Choices were R + S, C + G, R + G, C + S or R + C +G + S. The 6th treatment was a complete feed ( CF) that was similar to a commercial broiler feed.3. The isotopic composition of the birds' tissues was representative of the isotopic composition of the diets. The assimilation was faster for C-3, in both liver and muscle, than for C-4 diets, and give the delta per mil difference between the diet and tissues.4. The liver is the most active metabolic tissue and gave more rapid isotope turnover than in muscle.

Condiciones para asimilar la inmigración en el Brasil urbano = Conditions of immigrant assimilation in urban Brazil

Los documentos del Seminario fueron publicados por UNESCO en 1961 con el título: La urbanización en América Latina/Urbanization in Latin America

Comparison of snow data assimilation system with GPS reflectometry snow depth in the Western United States

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Description of atmospheric conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown. (C) 2012 Elsevier B.V. All rights reserved.

Photosynthetic efficiency and rate of CO2 assimilation by Arthrospira (Spirulina) platensis continuously cultivated in a tubular photobioreactor

Similar to other photosynthetic microorganisms, the cyanobacterium Arthrospira platensis can be used to produce pigments, single cell proteins, fatty acids (which can be used for bioenergy), food and feed supplements, and biofixation of CO2. Cultivation in a specifically designed tubular photobioreactor is suitable for photosynthetic biomass production, because the cultivation area can be reduced by distributing the microbial cells vertically, thus avoiding loss of ammonia and CO2. The aim of this study was to investigate the influence of light intensity and dilution rate on the photosynthetic efficiency and CO2 assimilation efficiency of A. platensis cultured in a tubular photobioreactor in a continuous process. Urea was used as a nitrogen source and CO2 as carbon source and for pH control. Steady-state conditions were achieved in most of the runs, indicating that continuous cultivation of this cyanobacterium in a tubular photobioreactor could be an interesting alternative for the large-scale fixation of CO2 to mitigate the greenhouse effect while producing high protein content biomass.

Analysis of the impact of rainfall assimilation during LBA atmospheric mesoscale missions in Southwest Amazon

The assimilation of satellite estimated precipitation data can be used as an efficient tool to improve the analysis of rainfall generated by numerical models of weather forecast. The system of data assimilation used in this study is cumulus parameterization inversion based on the Kuo scheme. Reanalysis were performed using the field experiment data of the LBA Project (WETAMC and DRYtoWET-AMC), where it was possible to verify an improvement in the simulations results, since the data assimilation corrects the position and the intensity of rainfall in the numerical model. (C) 2012 Elsevier B.V. All rights reserved.

Dynamical aspects of atmospheric data assimilation in the tropics

A faithful depiction of the tropical atmosphere requires three-dimensional sets of observations. Despite the increasing amount of observations presently available, these will hardly ever encompass the entire atmosphere and, in addition, observations have errors. Additional (background) information will always be required to complete the picture. Valuable added information comes from the physical laws governing the flow, usually mediated via a numerical weather prediction (NWP) model. These models are, however, never going to be error-free, why a reliable estimate of their errors poses a real challenge since the whole truth will never be within our grasp. The present thesis addresses the question of improving the analysis procedures for NWP in the tropics. Improvements are sought by addressing the following issues: - the efficiency of the internal model adjustment, - the potential of the reliable background-error information, as compared to observations, - the impact of a new, space-borne line-of-sight wind measurements, and - the usefulness of multivariate relationships for data assimilation in the tropics. Most NWP assimilation schemes are effectively univariate near the equator. In this thesis, a multivariate formulation of the variational data assimilation in the tropics has been developed. The proposed background-error model supports the mass-wind coupling based on convectively-coupled equatorial waves. The resulting assimilation model produces balanced analysis increments and hereby increases the efficiency of all types of observations. Idealized adjustment and multivariate analysis experiments highlight the importance of direct wind measurements in the tropics. In particular, the presented results confirm the superiority of wind observations compared to mass data, in spite of the exact multivariate relationships available from the background information. The internal model adjustment is also more efficient for wind observations than for mass data. In accordance with these findings, new satellite wind observations are expected to contribute towards the improvement of NWP and climate modeling in the tropics. Although incomplete, the new wind-field information has the potential to reduce uncertainties in the tropical dynamical fields, if used together with the existing satellite mass-field measurements. The results obtained by applying the new background-error representation to the tropical short-range forecast errors of a state-of-art NWP model suggest that achieving useful tropical multivariate relationships may be feasible within an operational NWP environment.