90 resultados para SWAT


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O uso inadequado do solo assim como práticas agrícolas incorrectas podem ter como consequência a contaminação dos recursos hídricos por poluição de origem difusa.Na perspectiva de identificar possíveis fontes de poluição, o objectivo deste trabalho é quantificar as cargas de nutrientes de origem natural, urbana e agrícola que chegam à albufeira de Pracana. Pretende-se efectuar a análise das alterações de carga resultantes de diferentes cenários do uso do solo, recorrendo à modelação matemática. Este conhecimento vai contribuir para a compreensão dos processos que dão origem à poluição existente na albufeira e os factores que condicionam o seu estado trófico.A ferramenta utilizada para a realização do estudo foi o modelo SWAT (Soil Water Assessment Tool, USDA Agricultural Research Service).

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Modelling the hydrology of hydrographic basins has shown itself as a useful tool in environment management. The hydrological models can be used for multiple purposes: estimate runoff from sequences of rainfall, access stream water quality, quantify the diffuse pollution that reaches water masses such as estuaries, rivers and lakes, etc. This study has as final objective to simulate and analyse the flow, sediment transport and water quality as a function of landuse and soil type in the basins of Maranhão and Pracana. The modelling system used is SWAT, Soil Water Assessment Tool. In this first phase of the study the hydrodynamic calibration of the model was performed using measurements of average daily flows in five stations. The model compares well with the measurements; the annual average flows are similar and the majority of the measured flow peaks coincide with the model peaks.

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Localizada na parte sul da costa da Galiza, a ria de Arousa, tem um interesse particular devido à sua importante indústria de exploração de marisco, especialmente culturas de bivalves. O crescimento, qualidade e mortalidade destes bivalves não só são afetados por possíveis incidentes de poluição, mas também por episódios de grande run-off, que podem produzir decréscimos sazonais significativos de salinidade. Neste contexto, a presente dissertação pretende contribuir para uma melhor compreensão de como as plumas de água doce provenientes dos rios vão influenciar os gradientes de salinidade e temperatura no estuário da ria de Arousa. O objetivo é proceder a uma melhoria da previsão hidrodinâmica do modelo operacional oceanográfico desta ria, que é executado diariamente pela MeteoGalicia. Para atingir esse objectivo executaram-se simulações numéricas para diferentes cenários de forçamento. Foram escolhidos dois períodos com diferentes condições meteorológicas: um período de inverno, coincidindo com chuvas fortes e um período de verão, coincidindo com a ausência de precipitação. Foi aplicado o modelo hidrodinâmico MOHID (Hydrodynamic Model) para simular os processos físicos da ria de Arousa, utilizando a metodologia de modelos encaixados. O forçamento para a superfície foi imposto através do modelo atmosférico WRF (Weather Regional Forecast), que fornece as variáveis meteorológicas necessárias. Para fronteira terra, uma ferramenta hidrológica foi implementada, o modelo SWAT (Soil water Assessment Tool), este providencia as descargas de água doce para os principais rios da região. É feita neste trabalho uma descrição da implementação deste sistema, assim como a caracterização da área de estudo. Os resultados do modelo foram comparados com medidas provenientes de bóias oceanográficas e perfis de CTDs (Conductivity-Temperature-Depth instrument) em diferentes localizações.

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Numerous studies have proven an effect of a probable climate change on the hydrosphere’s different subsystems. In the 21st century global and regional redistribution of water has to be expected and it is very likely that extreme weather phenomenon will occur more frequently. From a global view the flood situation will exacerbate. In contrast to these discoveries the classical approach of flood frequency analysis provides terms like “mean flood recurrence interval”. But for this analysis to be valid there is a need for the precondition of stationary distribution parameters which implies that the flood frequencies are constant in time. Newer approaches take into account extreme value distributions with time-dependent parameters. But the latter implies a discard of the mentioned old terminology that has been used up-to-date in engineering hydrology. On the regional scale climate change affects the hydrosphere in various ways. So, the question appears to be whether in central Europe the classical approach of flood frequency analysis is not usable anymore and whether the traditional terminology should be renewed. In the present case study hydro-meteorological time series of the Fulda catchment area (6930 km²), upstream of the gauging station Bonaforth, are analyzed for the time period 1960 to 2100. At first a distributed catchment area model (SWAT2005) is build up, calibrated and finally validated. The Edertal reservoir is regulated as well by a feedback control of the catchments output in case of low water. Due to this intricacy a special modeling strategy has been necessary: The study area is divided into three SWAT basin models and an additional physically-based reservoir model is developed. To further improve the streamflow predictions of the SWAT model, a correction by an artificial neural network (ANN) has been tested successfully which opens a new way to improve hydrological models. With this extension the calibration and validation of the SWAT model for the Fulda catchment area is improved significantly. After calibration of the model for the past 20th century observed streamflow, the SWAT model is driven by high resolution climate data of the regional model REMO using the IPCC scenarios A1B, A2, and B1, to generate future runoff time series for the 21th century for the various sub-basins in the study area. In a second step flood time series HQ(a) are derived from the 21st century runoff time series (scenarios A1B, A2, and B1). Then these flood projections are extensively tested with regard to stationarity, homogeneity and statistical independence. All these tests indicate that the SWAT-predicted 21st-century trends in the flood regime are not significant. Within the projected time the members of the flood time series are proven to be stationary and independent events. Hence, the classical stationary approach of flood frequency analysis can still be used within the Fulda catchment area, notwithstanding the fact that some regional climate change has been predicted using the IPCC scenarios. It should be noted, however, that the present results are not transferable to other catchment areas. Finally a new method is presented that enables the calculation of extreme flood statistics, even if the flood time series is non-stationary and also if the latter exhibits short- and longterm persistence. This method, which is called Flood Series Maximum Analysis here, enables the calculation of maximum design floods for a given risk- or safety level and time period.

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Durch die vermehrte Nachfrage von Biomöhren im Lebensmitteleinzelhandel ist die Anbaufläche ökologisch erzeugter Möhren in den letzten zehn Jahren deutlich angestiegen. Der Anbau konzentriert sich auf bestimmte Regionen und erfolgte damit zunehmend auf großen Schlägen in enger räumlicher und zeitlicher Abfolge. Mit der steigenden Wirtspflanzenpräsenz steigt auch der Befallsdruck durch die Möhrenfliege. Während der Schädling im konventionellen Anbau mit Insektiziden kontrolliert wird, stehen dem Ökologischen Landbau bisher keine direkten Regulative zur Verfügung. Ziel der Untersuchungen war es, unter den Praxisbedingungen des ökologischen Möhrenanbaus einzelbetriebliche und überregionale Muster beteiligter Risikofaktoren im Befallsgeschehen zu identifizieren und so Möglichkeiten einer verbesserten Prävention und Regulation aufzuzeigen. Über einen Zeitraum von drei Jahren wurden auf fünf Betrieben in Niedersachsen und Hessen umfangreiche Felddaten erhoben und diese unter Verwendung von GIS – Software und dem Simulationsmodell SWAT analysiert. Untersuchte Einflussgrößen umfassten (1) die Distanz zu vorjährigen Möhrenfeldern, (2) die zeitliche Möhrenanbauperiode, (3) Vegetationselemente und (4) der experimentelle Einsatz von Fangpflanzen zur Unterdrückung der Fliegenentwicklung. Unter der Berücksichtigung deutlicher einzelbetrieblicher Unterschiede sind die wichtigsten Ergebnisse der Studie wie folgt zu benennen: (1) Auf Betrieben mit Befall im zurückliegenden Anbaujahr zeigte sich die Distanz zu vorjährigen Möhrenfeldern als der wichtigste Risikofaktor. Das Ausbreitungsverhalten der 1. Generation Möhrenfliege erwies sich zudem als situationsgebunden anpassungsfähig. Fliegensumme und Befall waren jeweils in dem zu Vorjahresflächen nächstgelegen Feld am größten, während jeweils dahinter liegende Möhrenschläge entsprechend weniger Fliegenzahlen und Befall auswiesen. Aus den Ergebnissen wird als vorrangige Verbreitungskapazität der 1. Generation Möhrenfliegen innerhalb von 1000 m abgeleitet. (2) Betriebe mit kontinuierlicher Möhren - Anbaubauperiode (ca. April – Oktober), die langfristig die Entwicklung sowohl der 1. als auch der 2. Generation Fliegen unterstützten, verzeichneten stärkere Fliegenprobleme. Hinsichtlich einer verbesserten Prävention wird empfohlen mit einer strikten räumlichen Trennung früher und später Sätze ein Aufschaukeln zwischen den Generationen zu vermeiden. (3) Der Einfluss der Vegetation ließ sich weniger eindeutig interpretieren. Einzelbetriebliche Hinweise, dass Kleingehölze (Hecken und Bäume) im Radius zwischen aktueller und vorjähriger Möhrenfläche die Befallswahrscheinlichkeit erhöhen, konnten mit einem berechneten Gesamtmaß für die regionale holzige Vegetation nicht bestätigt werden. Der großräumigen holzigen Vegetation wird im Vergleich zur Feldrandvegetation daher beim Befallsgeschehen eine geringe Bedeutung zugeschrieben. (4) Drei Meter (vier Dämme) breiter Möhren – Fangstreifen auf den vorjährigen Möhrenfeldern eignen sich bereits ab dem Keimblattstadium, um erhebliches Befallspotential zu binden. Eine mechanische Entfernung der Fangpflanzen (Grubbern) mitsamt dem Befallspotential erzielte in 2008 eine 100 %-ige Unterdrückung der Möhrenfliegenentwicklung, in 2009 jedoch nur zu maximal 41 %. Als mögliche Synthese der Ergebnisse zur Ausbreitung der Möhrenfliegen im Frühjahr und zur zeitlichen Koinzidenz mit der Möhrenentwicklung wird als Empfehlung diskutiert, mit Hilfe einer angepassten Flächenwahl die Fliegenausbreitung räumlich an frühen Sätzen zu binden, um entsprechend befallsarme Regionen für entfernt liegende späte (empfindlichere) Möhrensätze zu schaffen.

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The Upper Blue Nile River Basin (UBNRB) located in the western part of Ethiopia, between 7° 45’ and 12° 45’N and 34° 05’ and 39° 45’E has a total area of 174962 km2 . More than 80% of the population in the basin is engaged in agricultural activities. Because of the particularly dry climate in the basin, likewise to most other regions of Ethiopia, the agricultural productivity depends to a very large extent on the occurrence of the seasonal rains. This situation makes agriculture highly vulnerable to the impact of potential climate hazards which are about to inflict Africa as a whole and Ethiopia in particular. To analyze these possible impacts of future climate change on the water resources in the UBNRB, in the first part of the thesis climate projection for precipitation, minimum and maximum temperatures in the basin, using downscaled predictors from three GCMs (ECHAM5, GFDL21 and CSIRO-MK3) under SRES scenarios A1B and A2 have been carried out. The two statistical downscaling models used are SDSM and LARS-WG, whereby SDSM is used to downscale ECHAM5-predictors alone and LARS-WG is applied in both mono-model mode with predictors from ECHAM5 and in multi-model mode with combined predictors from ECHAM5, GFDL21 and CSIRO-MK3. For the calibration/validation of the downscaled models, observed as well as NCEP climate data in the 1970 - 2000 reference period is used. The future projections are made for two time periods; 2046-2065 (2050s) and 2081-2100 (2090s). For the 2050s future time period the downscaled climate predictions indicate rise of 0.6°C to 2.7°C for the seasonal maximum temperatures Tmax, and of 0.5°C to 2.44°C for the minimum temperatures Tmin. Similarly, during the 2090s the seasonal Tmax increases by 0.9°C to 4.63°C and Tmin by 1°C to 4.6°C, whereby these increases are generally higher for the A2 than for the A1B scenario. For most sub-basins of the UBNRB, the predicted changes of Tmin are larger than those of Tmax. Meanwhile, for the precipitation, both downscaling tools predict large changes which, depending on the GCM employed, are such that the spring and summer seasons will be experiencing decreases between -36% to 1% and the autumn and winter seasons an increase of -8% to 126% for the two future time periods, regardless of the SRES scenario used. In the second part of the thesis the semi-distributed, physically based hydrologic model, SWAT (Soil Water Assessment Tool), is used to evaluate the impacts of the above-predicted future climate change on the hydrology and water resources of the UBNRB. Hereby the downscaled future predictors are used as input in the SWAT model to predict streamflow of the Upper Blue Nile as well as other relevant water resources parameter in the basin. Calibration and validation of the streamflow model is done again on 1970-2000 measured discharge at the outlet gage station Eldiem, whereby the most sensitive out the numerous “tuneable” calibration parameters in SWAT have been selected by means of a sophisticated sensitivity analysis. Consequently, a good calibration/validation model performance with a high NSE-coefficient of 0.89 is obtained. The results of the future simulations of streamflow in the basin, using both SDSM- and LARS-WG downscaled output in SWAT reveal a decline of -10% to -61% of the future Blue Nile streamflow, And, expectedly, these obviously adverse effects on the future UBNRB-water availibiliy are more exacerbated for the 2090’s than for the 2050’s, regardless of the SRES.

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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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Esse trabalho tem como objetivo compreender a influência da cultura no estilo de liderança em equipes de operações especiais, usando como referência teórica principal as pesquisas de Geert Hofstede sobre dimensões culturais. Buscamos entender como os elementos da cultura nacional e da cultura organizacional influenciam o estilo de liderança comparando equipes de operações especiais do Brasil e dos Estados Unidos. As unidades brasileiras estudadas foram o Batalhão de Operações Especiais (BOPE) da Polícia Militar do Rio de Janeiro e a Coordenadoria de Recursos Especiais (CORE) da Polícia Civil do Rio de Janeiro. A equipe de operações especiais estudada nos Estados Unidos foi a SWAT. Os resultados apontam para a influência da cultura organizacional, e não da cultura nacional, no estilo de liderança.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Produção Vegetal) - FCAV