945 resultados para Spatial Uniformity Of Rainfall
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This monograph aims to contribute to the understanding and analysis of extreme events and its correlation with anthropogenic actions, in order to understand the levels of human interference in the environment and to identify potential social and environmental damage that such events may result in Ubatuba, located on the northern coast of São Paulo state. Therefore, two strategies were established, on one hand, episodic analysis of extreme weather events, and on the other, the analysis of the impact of atmospheric phenomena in everyday society. In this case we gave greater emphasis to analysis years that had higher total rainfall. In this sense, the research was based on the standard deviation technique and percentages, which supported to characterize the exceptional rainy years, in addition, use of rhythm analysis technique that has helped to identify the active atmospheric systems. From a qualitative point of view, field works were carried out in order to make use of news by the local press and civil defense for years considered extreme (positive standard deviation). From this, it was analyzed how the extreme episodes of rainfall trigger repercussions in geographic space. Also the spatial distribution of rainfall were carried out by means of quantitative analysis of six rain gauges. It was found that the highest occurrences of impacts, are located in the central areas of the city, as well as the highest rainfall totals. In fact, Ubatuba/SP suffers from very high rainfall totals and has a singularity on the climate...
Variabilidade da precipitação na Unidade de Gerenciamento de Recursos Hídricos do médio Paranapanema
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Analysis of variability of rainfall UGRHI-17 is important because it is located in an area of agriculture. This importance is through a better dialogue between research and farmers, who can see this, an analysis of events that impact your direct planting. Noting the periodic occurrence of these events, agriculture can be prevented by protecting your planting and ensuring a good harvest. The analysis and observation of the entire region is through the location of the stations, which allow a more complete analysis if they are well scattered throughout the unit. Through calculations parse wet and dry years, and this work will be given emphasis to the wet years. They presented the climatological average above average extracted for all seasons. These wet years are generally associated with events such as El Niño and the intensification of SACZ. For these years, was also observed the spatial distribution of rainfall through isolines. How to deal with regional data, the Geostatistics was a resource used in this work to make the analysis more complete and closer to the actual data from the wide year-to-interannual scale. Their adoption is in the preparation of contour, making the spatial distribution more accurate.
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The study of variability becomes increasingly important nowadays . Studying the behavior of rainfall before external events is of paramount importance. The region of Vale do Paraíba , it is important to study variability , since the region is influenced by the ocean and constant cold fronts that end causing precipitation during most months of the year . This study aims to analyze the variability in rain UGRHI - 2 by analyzing the interference of ENSO events / Southern Oscillation and the Convergence Zone South Atlantic (SACZ) in the amount and distribution of rainfall. The UGRHI helped were created for distribution and control of water in the state of São Paulo , divided watersheds were avoided so that problems such as poor distribution and water shortages in some areas of the state . To study variability , various software , including Excel , Variowin and R statistical package , the subroutine Climatol were used , with the goal of developing isolines showing the spatial distribution of rainfall anomalies in the years studied also the anomaly index was studied rain (IAC) , noting more effectively the years of positive and negative anomaly , with the purpose of studying the temporal variability of rainfall in the study area.
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L’invarianza spaziale dei parametri di un modello afflussi-deflussi può rivelarsi una soluzione pratica e valida nel caso si voglia stimare la disponibilità di risorsa idrica di un’area. La simulazione idrologica è infatti uno strumento molto adottato ma presenta alcune criticità legate soprattutto alla necessità di calibrare i parametri del modello. Se si opta per l’applicazione di modelli spazialmente distribuiti, utili perché in grado di rendere conto della variabilità spaziale dei fenomeni che concorrono alla formazione di deflusso, il problema è solitamente legato all’alto numero di parametri in gioco. Assumendo che alcuni di questi siano omogenei nello spazio, dunque presentino lo stesso valore sui diversi bacini, è possibile ridurre il numero complessivo dei parametri che necessitano della calibrazione. Si verifica su base statistica questa assunzione, ricorrendo alla stima dell’incertezza parametrica valutata per mezzo di un algoritmo MCMC. Si nota che le distribuzioni dei parametri risultano in diversa misura compatibili sui bacini considerati. Quando poi l’obiettivo è la stima della disponibilità di risorsa idrica di bacini non strumentati, l’ipotesi di invarianza dei parametri assume ancora più importanza; solitamente infatti si affronta questo problema ricorrendo a lunghe analisi di regionalizzazione dei parametri. In questa sede invece si propone una procedura di cross-calibrazione che viene realizzata adottando le informazioni provenienti dai bacini strumentati più simili al sito di interesse. Si vuole raggiungere cioè un giusto compromesso tra lo svantaggio derivante dall’assumere i parametri del modello costanti sui bacini strumentati e il beneficio legato all’introduzione, passo dopo passo, di nuove e importanti informazioni derivanti dai bacini strumentati coinvolti nell’analisi. I risultati dimostrano l’utilità della metodologia proposta; si vede infatti che, in fase di validazione sul bacino considerato non strumentato, è possibile raggiungere un buona concordanza tra le serie di portata simulate e osservate.
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Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.
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Soil erosion is a serious environmental threat in the Mediterranean region due to torrential rainfalls, and it contributes to the degradation of agricultural land. Techniques such as rainwater harvesting may improve soil water storage and increase agricultural productivity, which could result in more effective land usage. Reservoir tillage is an effective system of harvesting rainwater, but it has not been scientifically evaluated like other tillage systems. Its suitability for the conditions in Spain has not been determined. To investigate and quantify water storage from reservoir tillage and how it could be adapted to improve infiltration of harvested rainwater, a laboratory-scale rainfall simulator was developed. Rainfall characteristics, including rainfall intensity, spatial uniformity and raindrop size, confirm that natural rainfall conditions are simulated with sufficient accuracy. The simulator was auto-controlled by a solenoid valve and three pressure nozzles were used to spray water corresponding to five rainfall intensities ranging from 36 to 112 mm h-1 for 3 to 101-year return period with uniformity coefficients between 83 and 94%. In order to assess the reservoir tillage method under surface slopes of 0, 5, and 10%, three soil scooping devices with identical volume were used to make depressions in the following forms: a) truncated square pyramid, b) triangular prism, and c) truncated cone. These depressions were compared to a control soil surface with no depression. For the loam soil used in this study, results show that reservoir tillage was able to reduce soil erosion and surface runoff and significantly increase infiltration. There was significant difference between the depressions and the control. Compared to the control, depression (a) reduced surface runoff by about 61% and the sediment yield concentration by about 79%.
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Soil erosion is a serious environmental threat in the Mediterranean region due to torrential rainfalls, and it contributes to the degradation of agricultural land. Techniques such as rainwater harvesting may improve soil water storage and increase agricultural productivity, which could result in more effective land usage. Reservoir tillage is an effective system of harvesting rainwater, but it has not been scientifically evaluated like other tillage systems. Its suitability for the conditions in Spain has not been determined. To investigate and quantify water storage from reservoir tillage and how it could be adapted to improve infiltration of harvested rainwater, a laboratory-scale rainfall simulator was developed. Rainfall characteristics, including rainfall intensity, spatial uniformity and raindrop size, confirm that natural rainfall conditions are simulated with sufficient accuracy. The simulator was auto-controlled by a solenoid valve and three pressure nozzles were used to spray water corresponding to five rainfall intensities ranging from 36 to 112 mm h− 1 for 3 to 101-year return period with uniformity coefficients between 83 and 94%. In order to assess the reservoir tillage method under surface slopes of 0, 5, and 10%, three soil scooping devices with identical volume were used to make depressions in the following forms: a) truncated square pyramid, b) triangular prism, and c) truncated cone. These depressions were compared to a control soil surface with no depression. For the loam soil used in this study, results show that reservoir tillage was able to reduce soil erosion and surface runoff and significantly increase infiltration. There was significant difference between the depressions and the control. Compared to the control, depression (a) reduced surface runoff by about 61% and the sediment yield concentration by about 79%.
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Satellite information, in combination with conventional point source measurements, can be a valuable source of information. This thesis is devoted to the spatial estimation of areal rainfall over a region using both the measurements from a dense and sparse network of rain-gauges and images from the meteorological satellites. A primary concern is to study the effects of such satellite assisted rainfall estimates on the performance of rainfall-runoff models. Low-cost image processing systems and peripherals are used to process and manipulate the data. Both secondary as well as primary satellite images were used for analysis. The secondary data was obtained from the in-house satellite receiver and the primary data was obtained from an outside source. Ground truth data was obtained from the local Water Authority. A number of algorithms are presented that combine the satellite and conventional data sources to produce areal rainfall estimates and the results are compared with some of the more traditional methodologies. The results indicate that the satellite cloud information is valuable in the assessment of the spatial distribution of areal rainfall, for both half-hourly as well as daily estimates of rainfall. It is also demonstrated how the performance of the simple multiple regression rainfall-runoff model is improved when satellite cloud information is used as a separate input in addition to rainfall estimates from conventional means. The use of low-cost equipment, from image processing systems to satellite imagery, makes it possible for developing countries to introduce such systems in areas where the benefits are greatest.
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Nitrogen variations at different spatial scales and integrated across functional groups were addressed for lowland tropical forests in the Brazilian Amazon as follows: (1) how does N availability vary across the region over different spatial scales (regional x landscape scale); ( 2) how are these variations in N availability integrated across plant functional groups ( legume 9 non-legume trees). Leaf N, P, and Ca concentrations as well the leaf N isotope ratios (delta(15)N) from a large set of legume and non-legume tree species were measured. Legumes had higher foliar N/Ca ratios than non-legumes, consistent with the high energetic costs in plant growth associated with higher foliar P/Ca ratios found in legumes than in non-legumes. At the regional level, foliar delta(15)N decreased with increasing rainfall. At the landscape level, N availability was higher in the forests on clayey soils on the plateau than in forests on sandier soils. The isotope as well as the non-isotope data relationships here documented, explain to a large extent the variation in delta(15)N signatures across gradients of rainfall and soil. Although at the regional level, the precipitation regime is a major determinant of differences in N availability, at the landscape level, under the same precipitation regime, soil type seems to be a major factor influencing the availability of N in the Brazilian Amazon forest.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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In this paper, we develop a data-driven methodology to characterize the likelihood of orographic precipitation enhancement using sequences of weather radar images and a digital elevation model (DEM). Geographical locations with topographic characteristics favorable to enforce repeatable and persistent orographic precipitation such as stationary cells, upslope rainfall enhancement, and repeated convective initiation are detected by analyzing the spatial distribution of a set of precipitation cells extracted from radar imagery. Topographic features such as terrain convexity and gradients computed from the DEM at multiple spatial scales as well as velocity fields estimated from sequences of weather radar images are used as explanatory factors to describe the occurrence of localized precipitation enhancement. The latter is represented as a binary process by defining a threshold on the number of cell occurrences at particular locations. Both two-class and one-class support vector machine classifiers are tested to separate the presumed orographic cells from the nonorographic ones in the space of contributing topographic and flow features. Site-based validation is carried out to estimate realistic generalization skills of the obtained spatial prediction models. Due to the high class separability, the decision function of the classifiers can be interpreted as a likelihood or susceptibility of orographic precipitation enhancement. The developed approach can serve as a basis for refining radar-based quantitative precipitation estimates and short-term forecasts or for generating stochastic precipitation ensembles conditioned on the local topography.
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To provide insight into subgrade non-uniformity and its effects on pavement performance, this study investigated the influence of non-uniform subgrade support on pavement responses (stress and deflection) that affect pavement performance. Several reconstructed PCC pavement projects in Iowa were studied to document and evaluate the influence of subgrade/subbase non-uniformity on pavement performance. In situ field tests were performed at 12 sites to determine the subgrade/subbase engineering properties and develop a database of engineering parameter values for statistical and numerical analysis. Results of stiffness, moisture and density, strength, and soil classification were used to determine the spatial variability of a given property. Natural subgrade soils, fly ash-stabilized subgrade, reclaimed hydrated fly ash subbase, and granular subbase were studied. The influence of the spatial variability of subgrade/subbase on pavement performance was then evaluated by modeling the elastic properties of the pavement and subgrade using the ISLAB2000 finite element analysis program. A major conclusion from this study is that non-uniform subgrade/subbase stiffness increases localized deflections and causes principal stress concentrations in the pavement, which can lead to fatigue cracking and other types of pavement distresses. Field data show that hydrated fly ash, self-cementing fly ash-stabilized subgrade, and granular subbases exhibit lower variability than natural subgrade soils. Pavement life should be increased through the use of more uniform subgrade support. Subgrade/subbase construction in the future should consider uniformity as a key to long-term pavement performance.
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The climate variability between the growth and harvesting of sugar cane is very important because it directly affects yield. The MODIS sensor has characteristics like spatial and temporal resolution that can be applied to monitoring of vegetative vigor variability in the land surface and then, temporal profiles generation. Agro meteorological data from ECMWF model are free and easy to access and have a good representation of reality. In this study, we used the period between sugar cane growth and harvest in the state of Sao Paulo, Brazil, from temporal profiles selecting of NDVI behavior. For each period the precipitation, evapotranspiration, global radiation, length (days) and degree-days were accumulated. The periods were presented in a map format on MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data.