Orientador: Glauco de Souza Rolim / Resumo: Precipitação, em pequenas escalas de tempo, é um fenômeno associado a altos níveis de incerteza e variabilidade. Dada a sua natureza, técnicas tradicionais de previsão são dispendiosas e exigentes em termos computacionais. Este trabalho apresenta um modelo para prever a ocorrência de chuvas em curtos intervalos de tempo por Redes Neurais Artificiais (RNAs) em períodos acumulados de 3 a 7 dias para cada estação climática, mitigando a necessidade de predizer o seu volume. Com essa premissa pretende-se reduzir a variância, aumentar a tendência dos dados diminuindo a responsabilidade do algoritmo que atua como um filtro para modelos quantitativos, removendo ocorrências subsequentes de valores de zero(ausência) de precipitação, o que influencia e reduz seu desempenho. O modelo foi desenvolvido com séries temporais de 10 regiões agricolamente relevantes no Brasil, esses locais são os que apresentam as séries temporais mais longas disponíveis e são mais deficientes em previsões climáticas precisas, com 60 anos de temperatura média diária do ar e precipitação acumulada. foram utilizados para estimar a evapotranspiração potencial e o balanço hídrico; estas foram as variáveis ​​utilizadas como entrada para as RNAs. A precisão média para todos os períodos acumulados foi de 78% no verão, 71% no inverno 62% na primavera e 56% no outono, foi identificado que o efeito da continentalidade, o efeito da altitude e o volume da precipitação normal , tem um impacto direto na precisão das RNAs. Os... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Precipitation, in short periods of time, is a phenomenon associated with high levels of uncertainty and variability. Given its nature, traditional forecasting techniques are expensive and computationally demanding. This paper presents a model to forecast the occurrence of rainfall in short ranges of time by Artificial Neural Networks(ANNs) in accumulated periods from 3 to 7 days for each climatic season, mitigating the necessity of predicting its amount. With this premise it is intended to reduce the variance, rise the bias of data and lower the responsibility of the model acting as a filter for quantitative models by removing subsequent occurrences of zeros values of rainfall which leads to bias the and reduces its performance. The model were developed with time series from 10 agriculturally relevant regions in Brazil, these places are the ones with the longest available weather time series and and more deficient in accurate climate predictions, it was available 60 years of daily mean air temperature and accumulated precipitation which were used to estimate the potential evapotranspiration and water balance; these were the variables used as inputs for the ANNs models. The mean accuracy of the model for all the accumulated periods were 78% on summer, 71% on winter 62% on spring and 56% on autumn, it was identified that the effect of continentality, the effect of altitude and the volume of normal precipitation, have a direct impact on the accuracy of the ANNs. The models have ... (Complete abstract click electronic access below) / Mestre

Le contexte général de l'étude est la caractérisation des variations du régime hydrologique et glaciologique du glacier de Zongo (16°15' de latitude sud en Bolivie) à partir du régime pluviométrique. L'hypothèse de base considère que les caractéristiques et propriétés de la saison des pluies ont une forte influence sur le bilan de masse et sur le régime hydrologique du glacier.Une base de données pluviométriques de 32 ans (données annuelles) et 19 ans (données journalières) a été compilée, critiquée et utilisée pour l'analyse de la précipitation à une échelle locale. Quatre régions climatiquement homogènes sont distinguées : l'Altiplano, la ville de La Paz, la partie haute et moyenne de la vallée du Zongo. Quatre méthodes pour l'identification des propriétés de la saison des pluies sont développées, deux basées sur l'intensité des pluies et deux basées sur l'occurrence des pluies. Finalement, six propriétés de la saison des pluies sont identifiées : la date de démarrage, la date de fin, la durée de la saison des pluies, la précipitation tombée durant cette saison, un indice de concentration et un indice d'intensités des pluies. Les résultats montrent que la variabilité interannuelle de la précipitation est contrôlée par les nombres de jours pluvieux pour le régime altiplanique, et par les intensités pour le régime amazonien (section moyenne de la vallée du Zongo). Une analyse de la variabilité interannuelle de la pluie a été comparée avec l'ENSO et les corrélations sont faibles durant les dernières 32 années entre ces deux variables.En comparant les deux dernières décennies [1992-2000] et [2001-2009] on observe une diminution de l'occurrence et de l'intensité des pluies durant l'installation de la saison des pluies mais une augmentation des intensités durant la saison des pluies.Dans la deuxième partie de cette étude on quantifie l'impact de la saison des pluies sur le bilan de masse et sur le régime hydrologique en tenant en compte chaque propriété. La corrélation entre les propriétés de la saison des pluies et les débits de fonte du glacier est plus forte qu'avec les bilan de masse. De plus, on met en évidence que la date de démarrage, la durée et la quantité de précipitation tombée durant le cœur de la saison des pluies sont les caractéristiques de la saison des pluies qui expliquent le mieux la variabilité interannuelle de la fusion. Finalement, cette étude permet d'avoir des nouveaux outils d'analyse qui pourraient être mise en place dans des modèles hydrologiques appliqués sur des bassins versants englacés. / L'auteur n'a pas fourni de résumé en anglais

Runoff and rainfall data have been taken from three high mountain Utah watersheds and subjected to runoff to rainfall comparisons. The resulting Q./P ratios have been compared to the average volumes of runoff curve numbers (CN) computed from this data for each watershed. Runoff curve numbers were also estimated on the basis of the soils and vegetation data available for the watersheds. An attempt has been made t o estimate the watershed lag characteristics by computing synthetic hydrographs for successively larger values of time to peak estimates until the best fit comparison was achieved between the snythetic and the actual hydrographs. Time lag estimates were also made from the Kirpich method and the Mockus method.

Approximately 60% of New Zealand's electricity is produced from hydro generation. The Waitaki River catchment is located in the centre of the South Island of New Zealand, and produces 35-40% of New Zealand's electricity. Low inflow years in 1992 and 2001 resulted in the threat of power blackouts, and a national demand for electricity that is currently growing at 2 to 5% a year gives strong justification for better management of the hydro resource. Improved seasonal rainfall and inflow forecasts will result in the better management of the water used in hydro generation on a seasonal basis. Seasonal rainfall forecasting has been the focus of much international research in recent years, but seasonal inflow forecasting is in its relative infancy. Researchers have stated that key directions for both fields are to decrease the spatial scale of forecast products, and to tailor forecast products to end user needs, so as to provide more relevant and targeted forecasts, which will hopefully decrease the enormous socio-economic costs of climate fluctuations. This study calibrated several season ahead lake inflow and rainfall forecast models for the Waitaki river catchment, using statistical techniques to quantify relationships between land-ocean-atmosphere state variables and seasonally lagged inflows and rainfall. Techniques included principal components analysis and multiple linear regression, with cross-validation techniques applied to estimate model error. Many of both the continuous and discrete format models calibrated in this study predict anomalously wet and dry seasons better than random chance, and better than the long term mean as a predictor. 95% confidence limits around most model predictions in this study offer significant skill when compared with the range of all probable inflows (based on the 80 year recording history in the catchment). Models predicting winter Lake Pukaki inflows are those with the strongest predictive relationships in this study. Spring and summer predictions were generally less skilful than those for winter and autumn. Inflows could be predicted with some skill in winter and summer, but not rainfall, and rainfall could be predicted with some skill in autumn and spring, but not inflows. Models predicting inflows and rainfall for different seasons in this study use very different sets of predictor variables to accomplish their seasonal predictability. This may be related to the significant seasonal snow storage in the catchment, so that other factors such as temperature and the number of north-westerly storms may have a large part to play in the magnitude of inflows. Similarly, predicting the same dependent variable but for different seasons led to different contributing variables, leading to the conclusion that different wider physical causative mechanisms are behind the predictability in different seasons, and that they too should be studied separately in any future research. SST5 (sea surface temperature to the north of New Zealand) was found to have more relevance than any other predictor in predicting Waitaki river inflows and rainfall in any season. The models calibrated with SOI and IPO included as predictor variables were almost invariably worse in their predictive skill than those without, and the list of the most important predictor variables in all models did not include equatorial sea surface temperatures, sea level pressures, or 700hpa geopotential height variables. The conclusion from these findings is that equatorial ocean-atmosphere state variables do not have significant relationships with season ahead inflows and rainfall in the South Island of New Zealand. Seasonal climate forecasting on single catchment scale, and focussed to end user needs, is possible with some skill, at least in the South Island of New Zealand.

[Abstract]: Australia is one of the driest continents in the world, and over the past decades, severe drought has plagued most of the country. Water security is an important national issue. The ultimate water supply, rainfall, however, is one of the most variable ones in theworld and is complicated by the fact that it is affected by several remote oceanatmospheric teleconnection systems simultaneously, including the El Niño-SouthernOscillation, the Indian Ocean Dipole and Southern Hemisphere oceanic and atmospheric variability. These three systems sometimes conspire to produce a severe impact, whereas sometimes they offset each other to produce a mild influence. The recent severe watershortage has generated a surge of investments with strong regional applications. The present study focuses on areas and issues outside the scope of these regional studies,aiming to provide an Australia-wide assessment of future Australian rainfall under climate change. Firstly, we unravel a process of the Indo-Pacific oceanic teleconnection and examine its role in influencing variability of the Indian Ocean, and hence Australianrainfall variations. An examination of their contribution to the warming structure of the Indian Ocean is carried out. Secondly, we explore dynamics of North West Australianrainfall variability and mechanisms of a rainfall increase over the past decades, and benchmark climate models in terms of their ability to reproduce the observed variability and trends, focusing on the role of increasing northern hemispheric aerosols in the rainfallincrease. Thirdly, we provide a dynamical explanation to the common future of a fast Tasman Sea warming rate under climate change, and identify the impacts of suchwarming on Australian rainfall. Finally, we examine the relative importance of the three systems, in addition to Tasman Sea warming, in driving rainfall changes undergreenhouse conditions. This project contributes to no less than six peer-reviewed journal publications.

The purpose of this dissertation is to enhance the applicability and the accuracy of the Poisson cluster stochastic rainfall generators. Firstly, the 6 parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall simulation model were regionalized across the contiguous United States. Each of the parameters of MBLRP model estimated at 3,444 National Climate Data Center (NCDC) rain gages was spatially interpolated based on the Ordinary Kriging technique to produce the parameter surface map for each of the 12 months of the year. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the statistics of the observed rainfall for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The estimated parameter values were also used to produce the maps of storm and rain cell characteristics. Secondly, the relative importance of the rainfall statistics in the generation of watershed response characteristics was estimated based on regression analyses using the rainfall time series observed at 1099 NCDC rain gages. The result of the analyses was used to weigh the rainfall statistics differently in the parameter calibration process of MBLRP model. It was observed that synthetic rainfall time series generated weighing the precipitation statistics according to their relative importance outperformed those generated weighing all statistics equally in predicting watershed runoff depths and peak flows. When all statistics were given the same weight, runoff depths and peak flows were underestimated by 20 percent and 14 percent, respectively; while, when the statistics were weighed proportionally to their relative importance, the underestimation was reduced to 4 percent and 3 percent, which confirms the advantage of weighing the statistics differently. In general, the value of the weights depends on the hydrologic process being modeled. Lastly, a stochastic rainfall generation model that can integrate year-to-year variability of rainfall statistics is suggested. The new framework consists of two parts. The first part generates the short-term rainfall statistics based on the correlation between the observed rainfall statistics. The second part generates the rainfall time series using the modified Bartlett-Lewis rectangular pulse model based on the simulated rainfall statistics. The new approach was validated at 104 NCDC gages across the United States in its ability to reproduce rainfall and watershed response characteristics. The result indicates that the new framework outperformed the traditional approach in reproducing the distribution of monthly maximum rainfall depths, monthly runoff volumes and monthly peak flows.

Composted biological wastes contain vital plant nutrients that assist in plant growth as well as contain organic matter that promotes good soil conditions; both aid in rangeland restoration. Most importantly, it has the potential to restore water availability through increased infiltration and reduced runoff. In this thesis, local sources of composted dairy manure are utilized for application onto the degraded Fort Hood Western Training Grounds in central Texas in hopes to restore the rangeland for continued military training. Small scale rainfall simulations are applied two and eight months post-application of seven different agronomic rates of composted waste treatment (0, 5, 10, 15, 20, 25, and 30 y^3/acre) in order to determine changes in infiltration rates. July 2004 rainfall simulations, two months post application, indicate that composted wastes have not had sufficient time to incorporate into the soil matrix. Percent organic matter of the parent soil is the only significant variable of impact on maximum infiltration capacity. Composted waste treatments are concluded to have no effect on infiltration rates for any of the application rates in the summer rainfall simulations and are observed to exhibit very high variability in the amount of infiltration by a plot. January 2005 rainfall simulations, eight months post waste application, are observed to continue the trend of high variability across all treatment application rates. This variability is attributed to masking any potential effects from the treatment applications. Overall, this high natural variability disables the detection of potential effects of waste application treatments leading to the conclusion that composted waste applications do not affect infiltration on the Fort Hood Western Training Grounds. Runoff nutrient analysis observed nitrate-N to be well below Texas drinking water standards for all plots and phosphate to be above non-standardized values known to cause problematic algal growth. Natural rainfall events at intensities needed to generate runoff observed in this study are rare; therefore, nutrient pollution concern for local water bodies is low.

Theory and experiment show that the rate and geographic distribution of erosion control the rate and pattern of deformation in collisional mountain belts. Enhanced erosion reduces the mass of material that must be moved up and over ramps and uplifted in large folds. In order to test this and related ideas in a natural example, we have compared modeled rainfall to measured thrust sheet displacement, geometry, and internal deformation in the Appalachian fold and thrust belt. We use mean annual precipitation from a global climate model (GCM) as a proxy for rate of erosion. Deformation measurements were made on a portfolio of regional cross sections from Alabama to New England. During the Carboniferous Allegheny orogeny the Southern Appalachians moved from -30 ° to 0° latitude whereas the Central and Northern Appalachians lay between -15° and 5° latitude. Mean annual precipitation determined from the GENESIS 2 GCM (Grossman, per. comm.) varied from tropical to arid conditions as the collision both moved north and grew in breadth and height. The Southern Appalachians, which experienced more net rainfall than other regions, generally show more displacement, deeper present day exhumation, and shallower ramps than regions to the north. The vicinity of the Pine Mountain thrust sheet in the Southern Appalachians experienced the most displacement (~1.5X the Central Appalachian average) and bulk shortening (~1.6X the Central Appalachians) and produced the most eroded material (~1.5X the Central Appalachians). The latitude of the Pine Mountain thrust sheet in the Southern Appalachians received ~20% more rainfall than the Central Appalachians. Although the number of regional detachments and lithologies change from Southern to Central and Northern Appalachians, the change in rainfall both regionally at any one time and as the collision progressed may explain part of the change in structural style from south to north.

The El Nino event causes the changes of the ocean and atmosphere system that induces the rainfall unusual increasing or reduction in some areas and then cause local lives and economical losses. Previous studies have found that the El Nino actually applies impact on the rainfall, however most of the studies focus on the impact of separated stations but little on regional variation. The study on the other hand focus on the variation of the rainfall based on the climatic classification primarily and the physiographic region position auxiliary during the El Nino event and La Nina events. The main method of this research is the correlation analysis, when the correlation coefficient draws close to +1, it mean that the rainfall is positive relative with the parameter of the El Nino, and when the correlation coefficient draws close to -1, it mean that the rainfall is negativity relative with the parameter of the El Nino event. The analysis parameters of the El Nino event index include the sea water temperature and anomaly of every area in Pacific Ocean, sea water surface temperature difference of two areas opposite, Southern Oscillation index and Multivariate ENSO Index. It is found in the study that the best parameter of the El Nino event is the sea water temperature difference of (Nino1¡Ï2- Nino34). The result showed the most climatic classifications have good relation with the parameter of the El Nino, especially winter-dry climatic classifications is the best. Because the result of the research influence on the season variation, it is not to conclude the relation with the El Nino event. It is need to study deeply for calculating the rainfall of the areas where influenced by the El Nino event.

Two experimental rainfall simulation plots in the Edwards Aquifer region of Texas were established to measure the effects of brush clearing on surface and subsurface water movement pathways. Multi-stage rainfall simulations were carried out at a site with Juniperus ashei (ashe juniper) cover both before and after brush removal, with three replications of a particular rainfall event for each vegetation condition. Similar simulations were carried out on a plot with a longstanding grass cover. Both plots included trenches at their downhill ends for observation of shallow lateral subsurface flow. Canopy interception was found to represent a major water loss, with interception of 32.7 mm for an average 166 mm, 5.25 hr rainfall event. Brush clearing had little impact on surface runoff, with no overland flow occurring at the juniper plot for either vegetation condition, while 31.9 percent of applied rainfall moved as overland flow at the grass plot. This difference was attributed to differences in the structure and permeability of the epikarst. Brush removal caused significant (90 percent confidence level) reduction in shallow lateral subsurface flow into the trench after brush removal, with 56.7 percent of water reaching the surface entering the trench for the pre-cut condition and only 43.4 percent for the post-cut condition. However, subsurface water movement through other pathways increased from 31.0 to 54.1 percent after brush removal. This additional water, due to removal of canopy interception, could either move off-site through conduit and fracture flow or remain on site as storage in conduits, unconsolidated caliche/marl layers, or in soil pockets. Two tracer tests with fluorescent dyes were also conducted using simulated rainfall to assess discrete flow paths discharging into the trench at the downhill end of the juniper plot. Analysis of samples from sixteen outlet locations revealed that not all areas of the plot were connected hydraulically to the trench. Additionally, subsurface flow paths were found to have a high degree of interconnection, linking conduit flow outlets with multiple inlet locations on the plot surface. Conduits showed strong connection with an area surrounding juniper vegetation, with rapid water flow (up to 2.4 m/h) from this area.