La toxoplasmose chez les Inuits : investigation de l'écologie de toxoplasma gondii dans l'Arctique canadien

Toxoplasma gondii, un protozoaire très répandu dans le monde, peut infecter de nombreuses espèces homéothermes incluant les mammifères et les oiseaux qui développent alors une toxoplasmose. L’impact de la toxoplasmose en termes de santé publique est majeur, particulièrement chez les personnes immunodéprimées et les foetus. Les niveaux d’infection humaine dans certaines régions de l’Arctique Canadien sont parmi les plus élevés au monde et ce, malgré l’absence de félidés qui sont les seuls hôtes capables d’excréter T. gondii. Plusieurs études ont suggéré la consommation de viande crue de mammifères marins et notamment de phoques comme source d’infection des Inuits. Notre travail de recherche visait à comprendre les mécanismes de dispersion de T. gondii dans les écosystèmes aquatiques menant à la contamination du milieu marin de l’Arctique par des oocystes, et à évaluer l’importance de cette voie de dispersion dans l’infection des phoques et conséquemment dans celle des Inuits. Notre hypothèse était que les oocystes de T. gondii, excrétés durant l’hiver par des félidés dans le Subarctique et transportés par les rivières pendant la fonte printanière, contaminaient les estuaires de l’Arctique Canadien. Dans un premier temps, une étude transversale de séroprévalence chez les phoques de l’Arctique Canadien a montré que ces populations étaient infectées par T. gondii et pouvaient ainsi a priori constituer une source d’infection pour les Inuit. Des variations spatio-temporelles de la séroprévalence étaient observées suggérant un lien potentiel avec des variations dans la contamination environnementale par les oocystes. Un schéma conceptuel explicitant les mécanismes de transport et de devenir des oocystes de T. gondii, du phénomène de la fonte de la neige jusqu’à l’exposition des organismes marins, a été proposé dans le chapitre suivant. Des interactions entre les différents mécanismes identifiés, qui agissent sur des échelles spatio-temporelles variées, devraient favoriser l’apparition de concentrations relativement élevées aux estuaires permettant ainsi l’exposition et potentiellement l’infection de phoques. Pour évaluer la contamination environnementale par les oocystes excrétés par la population de lynx du bassin versant de l’Arctique Canadien (les seuls félidés majoritairement distribués dans ce vaste territoire), nous avons mené une étude sérologique de type transversale dans cette population. Cette étude a permis de montrer que des lynx étaient infectés par T. gondii et a également suggéré que la dynamique des cycles de populations lynx-lièvres pouvait être un processus important dans la transmission de T. gondii. Finalement, la modélisation du transport hydrique des oocystes a indiqué que les concentrations hypothétiques d’oocystes dans l’eau de la fonte pourraient être suffisantes pour permettre l’exposition au niveau des estuaires de bivalves filtreurs, qui sont des proies pour les phoques et donc potentiellement des sources infectieuses pour ces derniers. Dans des écosystèmes nordiques en pleine mutation, la compréhension des mécanismes de transmission d’agents pathogènes d’origine hydrique comme T. gondii est plus que nécessaire, notamment dans le but de protéger les populations fragilisées de ces régions.

Geostatistical Tools for Validation of Satellite and NWP Model Rainfall

An ensemble approach to uncertainty estimation for satellite-based rainfall estimates

Forecasters priorities for improving probabilistic flood forecasts.

Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general.

Hydropower Energy Simulation Using Mike 11 Model; A Case Study In South Germany's Small Run-Of-River Hydropower Plants

Renewable energy production is a basic supplement to stabilize rapidly increasing global energy demand and skyrocketing energy price as well as to balance the fluctuation of supply from non-renewable energy sources at electrical grid hubs. The European energy traders, government and private company energy providers and other stakeholders have been, since recently, a major beneficiary, customer and clients of Hydropower simulation solutions. The relationship between rainfall-runoff model outputs and energy productions of hydropower plants has not been clearly studied. In this research, association of rainfall, catchment characteristics, river network and runoff with energy production of a particular hydropower station is examined. The essence of this study is to justify the correspondence between runoff extracted from calibrated catchment and energy production of hydropower plant located at a catchment outlet; to employ a unique technique to convert runoff to energy based on statistical and graphical trend analysis of the two, and to provide environment for energy forecast. For rainfall-runoff model setup and calibration, MIKE 11 NAM model is applied, meanwhile MIKE 11 SO model is used to track, adopt and set a control strategy at hydropower location for runoff-energy correlation. The model is tested at two selected micro run-of-river hydropower plants located in South Germany. Two consecutive calibration is compromised to test the model; one for rainfall-runoff model and other for energy simulation. Calibration results and supporting verification plots of two case studies indicated that simulated discharge and energy production is comparable with the measured discharge and energy production respectively.

Reducing The Risk Of Floods In Urban Areas With Combined Inland-River System

With the change of the water environment in accordance with climate change, the loss of lives and properties has increased due to urban flood. Although the importance of urban floods has been highlighted quickly, the construction of advancement technology of an urban drainage system combined with inland-river water and its relevant research has not been emphasized in Korea. In addition, without operation in consideration of combined inland-river water, it is difficult to prevent urban flooding effectively. This study, therefore, develops the uncertainty quantification technology of the risk-based water level and the assessment technology of a flood-risk region through a flooding analysis of the combination of inland-river. The study is also conducted to develop forecast technology of change in the water level of an urban region through the construction of very short-term/short-term flood forecast systems. This study is expected to be able to build an urban flood forecast system which makes it possible to support decision making for systematic disaster prevention which can cope actively with climate change.

Combining Satellite And Gauge Precipitation Data With Co-Kriging Method For Jakarta Region

Jakarta is vulnerable to flooding mainly caused by prolonged and heavy rainfall and thus a robust hydrological modeling is called for. A good quality of spatial precipitation data is therefore desired so that a good hydrological model could be achieved. Two types of rainfall sources are available: satellite and gauge station observations. At-site rainfall is considered to be a reliable and accurate source of rainfall. However, the limited number of stations makes the spatial interpolation not very much appealing. On the other hand, the gridded rainfall nowadays has high spatial resolution and improved accuracy, but still, relatively less accurate than its counterpart. To achieve a better precipitation data set, the study proposes cokriging method, a blending algorithm, to yield the blended satellite-gauge gridded rainfall at approximately 10-km resolution. The Global Satellite Mapping of Precipitation (GSMaP, 0.1⁰×0.1⁰) and daily rainfall observations from gauge stations are used. The blended product is compared with satellite data by cross-validation method. The newly-yield blended product is then utilized to re-calibrate the hydrological model. Several scenarios are simulated by the hydrological models calibrated by gauge observations alone and blended product. The performance of two calibrated hydrological models is then assessed and compared based on simulated and observed runoff.

RWater – A Cyber Enabled Tool For Hydrologic Modeling And Analysis

Existing distributed hydrologic models are complex and computationally demanding for using as a rapid-forecasting policy-decision tool, or even as a class-room educational tool. In addition, platform dependence, specific input/output data structures and non-dynamic data-interaction with pluggable software components inside the existing proprietary frameworks make these models restrictive only to the specialized user groups. RWater is a web-based hydrologic analysis and modeling framework that utilizes the commonly used R software within the HUBzero cyber infrastructure of Purdue University. RWater is designed as an integrated framework for distributed hydrologic simulation, along with subsequent parameter optimization and visualization schemes. RWater provides platform independent web-based interface, flexible data integration capacity, grid-based simulations, and user-extensibility. RWater uses RStudio to simulate hydrologic processes on raster based data obtained through conventional GIS pre-processing. The program integrates Shuffled Complex Evolution (SCE) algorithm for parameter optimization. Moreover, RWater enables users to produce different descriptive statistics and visualization of the outputs at different temporal resolutions. The applicability of RWater will be demonstrated by application on two watersheds in Indiana for multiple rainfall events.

Modelagem hidrológica aplicada ao planejamento dos recursos hídricos na bacia hidrográfica do rio Acre

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Incorporação de incertezas associadas à predição de modelos hidrológicos aos instrumentos de gestão em recursos hídricos

Water management has in the watershed plans an important tool to plan the territory and adjust the activities develop over it to the natural resources availability. The incorporation of uncertainty analysis associated with hydrological modelling predictions is a manner to simulate scenarios and work with chances and probabilities that certain events happens inside these plans. Using stochastic methods is possible to consider uncertainty from estimations and even model it. Stochastic methods developed considerably during the last 30 years, but its applications to real-world problems have been limited, and did not turn into routine in hydrology. This paper brings an overview from eminent hydrologists about this subject and discuss the Brazilian and Paulista situation in the scope of groundwater monitoring.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.