Etude des variations saisonnières des crues par le modèle de dépassement

Cet article présente les résultats d'une étude traitant de deux aspects importants de l'application du modèle de dépassement en hydrologie. Ce modèle a été utilisé pour l'étude des variations saisonnieres des débits des rivières du Québec et du Nouveau-Brunswick. Ces variations ont généralement un effet important sur l'homogénéité des débits dans différentes périodes de l'année. Les modèles de dépassement sont capables de prendre ces variations saisonnières en considération en tenant compte des dépassements qui ne sont pas identiquement distribués lorsqu'ils proviennent de différentes saisons. L'étude traite spécialement le problème du choix de saisons à entrer dans le modèle. Particulièrement, on souligne l'importance de déterminer les saisons en se basant sur les données disponibles au lieu de se limiter aux quatre saisons habituelles: hiver, printemps, été et automne. On propose une procédure graphique qui, associée au modèle de dépassement, permet de délimiter les saisons dans les stations hydrologiques étudiées. La procédure est appliquée, sous deux formes différentes, à des stations de jaugeage dans les provinces du Québec et du Nouveau-Brunswick. Ceci nous a permis de diviser l'année convenablement en saisons dans différentes parties des deux provinces. Cette partition a été basée uniquement sur les débits de crues dans chaque station, et sans donner aucune considération à la location géographique de ces stations, mais il s'est avéré ultérieurement que cette subdivision des deux provinces représente en fait une partition géographique des stations hydrologiques.L'évaluation du débit de base représente un point d'une importance majeure dans l'application du modèle de dépassement. Une estimation du débit de base est proposée dans ce travail en utilisant l'analyse de régression multiple. Une approche basée sur l'ajustement du nombre de dépassements à une loi de Poisson a été suivie pour la détermination de ce niveau de base dans chaque station de jaugeage. Une forte corrélation est détectée entre le débit de base et la surface drainée, impliquant qu'il est possible de calculer le débit de base dans une station qui ne contient pas d'enregistrements.Les résultats de la régionalisation géographique de la saisonnalité sont analysés pour détecter et interpréter les liens entre les régions déterminées et les caractéristiques physiques et climatologiques des zones étudiées dans les deux provinces. Une association est démontrée entre ces deux paramètres qui semble être justifiable du point de vu hydrologique et climatologique. En conclusion, les résultats de cet article montrent la faisabilité technique et l'efficacité du modèle proposé pour l'étude des variations saisonnières des crues.The partial duration series (pds) method for flood frequency estimation analyzes ail flood peaks above a certain base level, or truncation level, QB, along with the times of occurrence of these flood « exceedances ». It has been shown that seasonal trends in river-flow processes have a significant effect on the distribution of flood exceedances. Two pds models have been presented in the literature for studying these seasonal variations in flood magnitude. The first, which can be called the « discrete seasonal pds mode) », divides the year into n seasons and determines n different distribution functions to fit the exceedances in each of these n seasons. The second, which can be called the « continuous seasonal pds model », accounts for seasonal flood variations by modeling flood magnitude as a continuous time-dependent random variable. The discrete seasonal model makes a few assumptions concerning flood characteristics, but the statistical estimation of its parameters is considerably less complex than in the case of the continuous seasonal model. Results of a study using the discrete seasonal pds modal are presented in this paper, along with two important applications of this modal in hydrology.The model is applied to 34 gaging stations in the province of Quebec and 28 stations in the province of New-Brunswick, Canada. Knowing the base level, QB, is essential for applying this model, but there is no universal technique for determining this truncation level. In this study, a technique is proposed that uses multiple regression for estimating QB. Regression equations, using one or more transformed or untransformed independent variables, are derived. Results for the province of Quebec show that the two-year flood estimate QDA explains 92.5 % of the variability of the base flow QB, and the drainage basin area SD explains 83 % of QB variability. The existence of a strong correlation between QB and SD suggests that it is possible to determine the base flow at sites where no historical record is available, by using the physical characteristics of the basin.A graphical procedure associated with the partial duration series model is proposed to study the seasonal trends in flood data at the selected gaging stations. The study deals specifically with the choice of seasons to be entered into the pds model. It is particularly emphasized that the seasons should be determined on the basis of the data on band, instead of taking the four usual seasons (winter, spring, summer, and fall). Two different forms of the graphical procedure are applied to the gaging stations in the provinces of Quebec and New Brunswick. The first, applied to the province of Quebec, consists of plotting the mean number of exceedances A (t) in a lime interval (0, 1•] equal 1a one year, against the lime t, for each station, and for a number of increasing base levels. The behavior of these A (1) plots (change at slope, piecewise linearity, etc.) indicates the significant seasons for each station. The second form of the graphical procedure, applied to stations in the province of New-Brunswick, is slightly different front the procedure mentioned above. For each station of the province, a relatively high base level is selected, corresponding to a mean number of exceedances per year in the order of 0.3 to 1.0. The Limes of occurrence of these exceedances are used to define the significant hydrological seasons in the year, which are then presented in graphical form. Varying the base level gives a fine seasonal partitioning of the year for each station, and allows grouping the stations into geographical regions that are homogeneous In seasonal flood distribution. Both versions of the graphical procedure are based on the same idea, and call far careful graphical examination of the seasonal behavior of floods at different gaging stations.An appropriate partitioning of the year into seasons is obtained for different parts of the two provinces. For bath provinces, and for al' the stations that were investigated, no more than two significant seasons were found necessary for modeling seasonal flood variations. Based on the seasons determined for each station, and the geographical distribution of these stations, a geographical regionalization of seasonality Is obtained for the provinces of Quebec and New-Brunswick. Each province is divided into tour homogeneous regions, and appropriate seasons for each region are proposed.The discrete seasonal model was found adequate and sufficient for the study of the seasonal behavior of floods in the provinces of Quebec and New-Brunswick. However, more detailed studios would be necessary to determine with more certitude if the continuous seasonal model is more appropriate in some cases. In all cases, a graphical examination of the empirical distribution function of flood magnitudes occurring in various periods of the year may help either in identifying homogeneous periods within which flood magnitudes may be considered as identically distributed, or In indicating a need for modeling flood magnitude as a random variable whose distribution varies continuously with time

Estimation de la température de l'eau de rivière en utilisant les réseaux de neurones et la régression linéaire multiple

La température de l'eau en rivière est un paramètre ayant une importance majeure pour la vie aquatique. Les séries temporelles décrivant ce paramètre thermique existent, mais elles sont moins nombreuses et souvent courtes, ou comptent parfois des valeurs manquantes. Cette étude présente la modélisation de la température de l'eau en utilisant des réseaux de neurones et la régression linéaire multiple pour relier la température de l'eau à celle de l'air et le débit du ruisseau Catamaran, situé au Nouveau-Brunswick, Canada. Une recherche multidisciplinaire à long terme se déroule présentement sur ce site. Les données utilisées sont de 1991 à 2000 et comprennent la température de l'air de la journée en cours, de la veille et de l'avant-veille, le débit ainsi que le temps transformé en série trigonométrique. Les données de 1991 à 1995 ont été utilisées pour l'entraînement ou la calibration du modèle tandis que les données de 1996 à 2000 ont été utilisées pour la validation du modèle. Les coefficients de détermination obtenus pour l'entraînement sont de 94,2 % pour les réseaux de neurones et de 92,6 % pour la régression linéaire multiple, ce qui donne un écart-type des erreurs de 1,01 C pour les réseaux de neurones et de 1,05 C pour la régression linéaire multiple. Pour la validation, les coefficients de détermination sont de 92,2 % pour les réseaux de neurones et de 91,6 % pour la régression linéaire multiple, ce qui se traduit en un écart-type des erreurs de 1,10 C pour les réseaux de neurones et de 1,25 C pour la régression linéaire multiple. Durant la période d'étude (1991-2000), le biais a été calculé à +0,11 C pour le modèle de réseaux de neurones et à -0,26 °C pour le modèle de régression. Ces résultats permettent de conclure qu'il est possible de prévoir la température de l'eau de petits cours d'eau en utilisant la température de l'air et le débit, aussi bien avec les réseaux de neurones qu'avec la régression linéaire multiple. Les réseaux de neurones semblent donner un ajustement aux données légèrement meilleur que celui offert par la régression linéaire multiple, toutefois ces deux approches de modélisation démontrent une bonne performance pour la prédiction de la température de l'eau en rivière.Water temperature is a parameter of great importance for water resources. For instance, modifications of the thermal regime of a river can have a significant impact on fish habitat. Therefore, understanding and predicting water temperatures is essential in order to help prevent or forecast high temperature problems. In order to predict water temperatures, data series are necessary. Many data series exist for air temperatures, but water temperature series are relatively scarce and those available are often short or have missing values. This study presents the modelling of water temperature using neural networks and multiple linear regression to relate water temperature to air temperature and discharge in Catamaran Brook, New Brunswick, Canada.Catamaran Brook is a small stream (51 km2) where long-term multidisciplinary habitat research is being carried out. Many variables can impact water temperatures in a river, such as air temperature, solar radiation, wind speed, discharge, groundwater flow, etc. For this study, only air temperature and discharge were used. These were judged to be the most often available parameters for modelling temperatures in rivers, and to have the greatest impact on water temperature. More precisely, input variables included current air temperature (°C), air temperature of the previous day (°C), air temperature two days earlier (°C), discharge (m3 /s) and a trigonometric function of time (days). Data used for the analysis were from 1991 to 2000. Data from 1991 to 1995 were used to calibrate the model while data from 1996 to 2000 were used for validation purposes. Observed and predicted water temperatures for each model were presented for the calibration data and the validation data. The coefficient of determination, R2, was used to compare the efficiency of both models as well as the residual standard deviation and the bias. This is equivalent to basing the comparison on the standard deviation (or variance) of the residuals. Coefficients of determination for calibration were 94.2% for the neural networks and 92.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.01°C for the neural networks and of 1.05°C for the multiple linear regression. For validation, coefficients of determination were 92.2% for the neural networks and 91.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.10°C for the neural networks, and of 1.25°C for the multiple regression. The overall bias during the study period (1991-2000) was calculated at +0.11°C for the neural network model and at -0.26°C for the regression model. Results indicated that it was possible to predict water temperature for a small stream using air temperature, flow and time, as input variables, with neural networks and multiple linear regression. The residual series obtained by both models were very similar. Of the two models, neural networks gave slightly better results in terms of fit, but the small difference in results lets us believe that both approaches are equally good in predicting stream water temperatures

FimH Adhesin of Type 1 Fimbriae Is a Potent Inducer of Innate Antimicrobial Responses Which Requires TLR4 and Type 1 Interferon Signalling

Components of bacteria have been shown to induce innate antiviral immunity via Toll-like receptors (TLRs). We have recently shown that FimH, the adhesin portion of type 1 fimbria, can induce the innate immune system via TLR4. Here we report that FimH induces potent in vitro and in vivo innate antimicrobial responses. FimH induced an innate antiviral state in murine macrophage and primary MEFs which was correlated with IFN-β production. Moreover, FimH induced the innate antiviral responses in cells from wild type, but not from MyD88−/−, Trif−/−, IFN−α/βR−/− or IRF3−/− mice. Vaginal delivery of FimH, but not LPS, completely protected wild type, but not MyD88−/−, IFN-α/βR−/−, IRF3−/− or TLR4−/− mice from subsequent genital HSV-2 challenge. The FimH-induced innate antiviral immunity correlated with the production of IFN-β, but not IFN-α or IFN-γ. To examine whether FimH plays a role in innate immune induction in the context of a natural infection, the innate immune responses to wild type uropathogenic E. coli (UPEC) and a FimH null mutant were examined in the urinary tract of C57Bl/6 (B6) mice and TLR4-deficient mice. While UPEC expressing FimH induced a robust polymorphonuclear response in B6, but not TLR4−/− mice, mutant bacteria lacking FimH did not. In addition, the presence of TLR4 was essential for innate control of and protection against UPEC. Our results demonstrate that FimH is a potent inducer of innate antimicrobial responses and signals differently, from that of LPS, via TLR4 at mucosal surfaces. Our studies suggest that FimH can potentially be used as an innate microbicide against mucosal pathogens

Genital HSV-2 Infection Induces Short-Term NK Cell Memory

NK cells are known as innate immune cells that lack immunological memory. Recently, it has been shown that NK cells remember encounters with chemical haptens that induce contact hypersensitivity and cytomegalovirus infection. Here, we show the existence of NK cell memory following HSV-2 infection. Stimulation with HSV-2 Ags led to higher IFNγ production in NK cells that were exposed 30 days previously to HSV-2, compared to NK cells from naïve mice. More importantly, this increased production of IFNγ in NK cells was independent of B- and T- lymphocytes and specific for the HSV-2 Ags. We also showed that previously exposed NK cells in a B- and T-lymphocyte free environment mediate protection against HSV-2 infection and they are necessary for the protection of mice against HSV-2 infection. Collectively, NK cells remember prior HSV-2 encounters independent of B- and T- lymphocytes leading to protection against HSV-2 mediated morbidity and mortality upon re-exposure

TOXICOLOGICAL AND PHARMACOLOGICAL ASSESSMENT OF GOLD NANORODS IN NORMAL RATS

Objective: assessment of acute, subchronic and chronic toxicity of pegylated gold nanorods (PEG-gold NRs) in Wistar rats of both sex in three routes of administration {intravenous (IV), intramuscular (IM) and subcutaneous (SC)}.Methods: in the acute toxicity study; PEG-gold NRs were injected once by three different routes, blood and tissue samples were collected after 14 d. In the subchronic and chronic studies; PEG-gold NRs were injected via three different routes, at 0.225, 0.45 and 0.9 mg/kg, once daily for 5 consecutive days, followed by a 23-day recovery period, for three and six months in the subchronic and chronic toxicity studies, respectively. Hematology, urinalysis, biochemical and histopathological examinations were conducted at the end of each study.Results: acute toxicity showed a significant decrease in serum triglycerides and cholesterol levels after single IV, IM and SC injection of PEG-gold NRs, while serum creatinine was significantly increased after IV and IM injection. Subchronic results revealed a significant decrease in serum triglycerides and cholesterol levels. The chronic study showed a significant decrease in serum triglycerides, sodium levels, total leukocytes count and significant increase in serum creatinine after IV injection. IM injection resulted in significant decrease in serum alkaline phosphatase, triglycerides, cholesterol, sodium levels and total leukocytes count. SC injection resulted in significant decrease in serum triglycerides, glucose, red blood cell count with increased creatinine and hematocrit.Conclusion: PEG-gold NRs at the three examined doses is apparently safe since no serious signs of toxicity were detected. IM and SC routes of injection were irritating, so we recommend the IV route.Â

Search for dark matter annihilation signals in the H.E.S.S. Inner galaxy survey

The central region of the Milky Way is one of the foremost locations to look for dark matter (DM) signatures. We report the first results on a search for DM particle annihilation signals using new observations from an unprecedented γ-ray survey of the Galactic Center (GC) region, i.e., the Inner Galaxy Survey, at very high energies (≳100  GeV) performed with the H.E.S.S. array of five ground-based Cherenkov telescopes. No significant γ-ray excess is found in the search region of the 2014-2020 dataset and a profile likelihood ratio analysis is carried out to set exclusion limits on the annihilation cross section ⟨σv⟩. Assuming Einasto and Navarro-Frenk-White (NFW) DM density profiles at the GC, these constraints are the strongest obtained so far in the TeV DM mass range. For the Einasto profile, the constraints reach ⟨σv⟩ values of 3.7×10^{-26}  cm^{3} s^{-1} for 1.5 TeV DM mass in the W^{+}W^{-} annihilation channel, and 1.2×10^{-26}  cm^{3} s^{-1} for 0.7 TeV DM mass in the τ^{+}τ^{-} annihilation channel. With the H.E.S.S. Inner Galaxy Survey, ground-based γ-ray observations thus probe ⟨σv⟩ values expected from thermal-relic annihilating TeV DM particles

A deep spectromorphological study of the γ -ray emission surrounding the young massive stellar cluster Westerlund 1

Context. Young massive stellar clusters are extreme environments and potentially provide the means for efficient particle acceleration. Indeed, they are increasingly considered as being responsible for a significant fraction of cosmic rays (CRs) that are accelerated within the Milky Way. Westerlund 1, the most massive known young stellar cluster in our Galaxy, is a prime candidate for studying this hypothesis. While the very-high-energy γ-ray source HESS J1646-458 has been detected in the vicinity of Westerlund 1 in the past, its association could not be firmly identified. Aims. We aim to identify the physical processes responsible for the γ-ray emission around Westerlund 1 and thus to understand the role of massive stellar clusters in the acceleration of Galactic CRs better. Methods. Using 164 h of data recorded with the High Energy Stereoscopic System (H.E.S.S.), we carried out a deep spectromorphological study of the γ-ray emission of HESS J1646-458. We furthermore employed H I and CO observations of the region to infer the presence of gas that could serve as target material for interactions of accelerated CRs. Results. We detected large-scale (~2 diameter) γ-ray emission with a complex morphology, exhibiting a shell-like structure and showing no significant variation with γ-ray energy. The combined energy spectrum of the emission extends to several tens of TeV, and it is uniform across the entire source region. We did not find a clear correlation of the γ-ray emission with gas clouds as identified through H I and CO observations. Conclusions. We conclude that, of the known objects within the region, only Westerlund 1 can explain the majority of the γ-ray emission. Several CR acceleration sites and mechanisms are conceivable and discussed in detail. While it seems clear that Westerlund 1 acts as a powerful particle accelerator, no firm conclusions on the contribution of massive stellar clusters to the flux of Galactic CRs in general can be drawn at this point

The Vanishing of the Primary Emission Region in PKS 1510-089

In 2021 July, PKS 1510-089 exhibited a significant flux drop in the high-energy γ-ray (by a factor 10) and optical (by a factor 5) bands and remained in this low state throughout 2022. Similarly, the optical polarization in the source vanished, resulting in the optical spectrum being fully explained through the steady flux of the accretion disk and the broad-line region. Unlike the aforementioned bands, the very-high-energy γ-ray and X-ray fluxes did not exhibit a significant flux drop from year to year. This suggests that the steady-state very-high-energy γ-ray and X-ray fluxes originate from a different emission region than the vanished parts of the high-energy γ-ray and optical jet fluxes. The latter component has disappeared through either a swing of the jet away from the line of sight or a significant drop in the photon production efficiency of the jet close to the black hole. Either change could become visible in high-resolution radio images