Étude sur le choix du seuil de troncature en analyse des séries de durées partielles : application au Canada

L'estimation des débits de crues est d'une importance majeure pour la conception des ouvrages d'art et la gestion des ressources hydriques. La mauvaise évaluation de ces débits entraîne un surdimensionnement ou sous dimensionnement des ouvrages hydrauliques, induisant ainsi un investissement excessif ou un risque démesuré d'inondations. Un modèle de données chronologiques de durée partielle est retenu pour l'étude des crues. Ce modèle nécessite d'abord l'estimation du seuil de troncature qui définit la série chronologique intermittente à analyser. Ce paramètre joue un rôle majeur dans la solution du problème malgré le peu d'importance que lui reconnaît la littérature. Le but de la présente étude est d'élaborer une méthode graphique comme guide dans le choix du seuil. Par la suite, cette méthode est appliquée à 238 stations hydrométriques au Canada. Une fois le seuil obtenu pour ces stations hydrométriques, une régionalisation utilisant l'analyse de régression a été réalisée. Ces équations régionales peuvent servir à estimer le seuil d'une nouvelle série hydrologique sans avoir à passer par la méthode graphique.Accurate forecasting of flood flows is required for the efficient design and construction of hydraulic structures in rivers as well as for the effective management of water resources. Underestimation of flood flows can result in tragic consequences while overdesigned structures are expensive.One method for estimating flood flows is the partial duration series analysis. In this approach a truncation level defining the intermittent time series is chosen. All flows above this level (exceedances) are analyzed by assuming the time of occurrence of these floods to represent a Poisson distribution. In addition, exceedances are considered to be independent random variables identically distributed over a one-year time interval. The selection of the truncation level is somewhat problematic and not very well defined in the literature. This study presents a truncation level estimation technique based on a series of regional regression equations for 9 distinct regions in Canada, and documents their graphical derivation.According to previous research, the truncation level can be obtained in two ways. First, it is selected in accordance with physical criteria such as the overflowing of a river, the critical flow for flooding of a crop, etc. The second method of truncation level selection is primarily mathematical such as satisfying the analytical fit or the assumptions of the model. In the present study, the truncation level was selected based on the mathematical approach using a graphical technique and using the Chi-square test. The graphical truncation level selection technique is based on the equality of the mean and variance of the Poisson distribution. Given this property of the Poisson distribution, one can study the mean-to-variance ratio as a function of truncation level.Truncation levels were selected graphically from 238 gauging stations across Canada. The Chi-square at a level of significance of 5 % was used for their validation. It was observed, upon examination of the mean-to-variance ratio, that selection of the truncation level was easier in the eastern and western regions of Canada where the ratio varied very little around unity. In the prairies and northern regions, a small variation in the truncation level led to a large variation in the ratio, making the selection of a level more difficult.Following the selection of a truncation level for each hydrometric station, homogeneous regions were selected based on previous countrywide hydrological studies. The regression analysis was then carried out to explain this truncation level using several variables (including bath physiographic variables and streamflow characteristics). Physiographic variables included area of drainage basin (km2); area of lakes and swamps (km2) ; area of forests (km2) ; mean elevation (m) ; slope of drainage basin (%) ; slope of principal watercourse (m/km, %) ; length of principal water course (km) ; area controlled by lakes and swamps (km2) ; and drainage density (km/km2). The Streamflow characteristics included the mean annual flow and mean annual flood. The mean annual flood was included because previous research has shown a strong correlation between the truncation level and the two-year flood estimated by a log-Pearson type III distribution function. For ease of application, the mean annual flood was used as a low return flood estimate as it represents the two-year flood calculated by a normal distribution function. Low return floods of any given distribution function are demonstrated to be similar in magnitude.Multiple regression was carried out using original data and logarithmically transformed data. Equations were derived by selecting one variable, two variables, and so on until all explanatory variables were accounted for in a single equation. Among the selected parameters, the mean annual flood was the best parameter to explain the truncation level for all of the regions across Canada. The coefficient of determination, R2, of the equations calculated using mean annual flood varied between 0.847 and 0.987 from original data, and varied between 0.824 and 0.988 for logarithmically transformed data. In practice, the regional equation can eliminate the graphical estimation technique and a first truncation level can be obtained. This truncation level can be used in the partial duration series analysis with the different tests involved. If this first estimated level does not meet all the statistical tests, a second usually higher level is selected. It is important to note that when the selected level meets the statistical test requirements, the estimation of QT should be relatively insensitive to levels near the selected truncation level

Évaluation du débit réservé par méthodes hydrologiques et hydrobiologiques

Plusieurs méthodes existent pour calculer le débit réservé d'un cours d'eau. Dans la présente étude deux approches sont analysées, soit les approches par méthodes hydrologiques et hydrobiologiques. Cinq méthodes hydrologiques d'évaluation du débit réservé ont été appliquées au ruisseau Catamaran au Nouveau-Brunswick (Canada), ainsi qu'une méthode hydrobiologique. Parmi les méthodes hydrologiques, on retrouve la méthode de Tennant, celle de 25% du débit moyen annuel (DMA), la méthode du débit médian (Q50) mensuel, 90% du débit classé (Q90) et la méthode basée sur l'analyse statistique de fréquence des débits faibles (7Q10). La méthode hydrobiologique utilisée dans la présente étude fut l'application du modèle PHABSIM pour le saumon Atlantique juvénile. Ce modèle est calibré en utilisant les données de vitesse d'écoulement (V), profondeur d'eau (D) et grosseur du substrat (S) pour trois différents débits. L'application des méthodes hydrologiques a démontré que certaines méthodes telle que la méthode Tennant, 25% DMA et la méthode du débit médian, donnent des résultats similaires surtout en période d'étiage. D'autre part, deux méthodes en particulier, soit la méthode de 90% du débit classé et celle basée sur une analyse statistique des débits faibles prédisent un débit réservé très faible en période d'étiage.Une modélisation de l'habitat physique du ruisseau Catamaran démontre que l'habitat disponible maximal se trouve généralement aux environs du débit moyen. De plus, il a été observé qu'en appliquant les modèles hydrologiques, l'habitat disponible était réduit par rapport à l'habitat maximum prédit par PHABSIM. En effet, l'habitat résultant de l'application de Tennant (30% DMA) et du 25% DMA représente environ 70% de l'habitat disponible maximum. Le débit calculé par la méthode du débit médian correspond à un habitat qui n'est que de 50% de l'habitat disponible maximum, tandis que les méthodes basées sur 90% du débit classé et l'analyse statistique des débits faibles ne représentent plus que des habitats de l'ordre de 20% à 40% de l'habitat disponible maximum. L'application de ces deux dernières méthodes laisse beaucoup de doute sur le niveau de protection des habitats aquatiques qu'elles procurent et il a été jugé utile de ne pas les recommander pour l'évaluation du débit réservé dans la région d'étude. Les autres méthodes (Tennant, 25% DMA et Q50) peuvent être utilisées. Cependant, l'application de la méthode du débit médian, qui peut donner des résultats proches de 50% de l'habitat disponible maximum, doit être appliquée avec précaution.Many techniques exist to calculate instream flow requirements. This study considers hydrologically-based techniques and hydrobiological or habitat preference methods. The hydrologically-based techniques use only historical streamflow data, and require little or no field work. Conversely, the habitat preference methods require knowledge of the specific hydraulic conditions of the studied water course and the habitat preferences of the relevant fish species.Five hydrologically-based methods and one habitat preference method were applied to Catamaran Brook, a small drainage basin in New Brunswick, Canada. The hydrologically-based techniques included the Tennant Method, the 25% Mean Annual Flow (MAF), the median monthly flow (Q50), the 90% flow duration method (Q90) and a low-flow frequency method (7Q10). The habitat preference method studied was the PHABSIM model applied for Atlantic salmon.The PHABSIM model was calibrated using the hydraulic characteristics of water depth (D), velocity (V) and substrate (S) for three flows. It was then used to calculate the same physical habitat parameters (D,V,S) for other discharges. The hydraulic results were used with habitat preference (suitability curves) to calculate the potential habitat or weighted usable area (WUA).The application of hydrologically-based in-stream flow techniques showed that methods such as Tennant, 25% MAF and the median monthly flow method provided similar results, especially during low flow periods. The in-stream flow requirement calculated by Tennant Method (30% MAF) was 0.20 m3·s-1, and the 25% MAF represented a value of 0.16 m3·s-1. The application of the Q50 approach yielded results of 0.13 m3·s-1 for the month of August with higher values for other months. In contrast, the 90% flow duration and the low-flow frequency methods established very low discharge for in-stream flow requirements during low-flow periods. The lowest Q90 observed was in September at 0.050 m3·s-1 whereas the months of August, July, October, February and March all showed results slightly higher than September but still lower than 0.10 m3·s-1. The method that calculated the lowest in-stream flow value was the 7Q10 (low-flow frequency) Method with a discharge of only 0.037 m3·s-1. These results (Q90 and 7Q10) represent significantly lower in-stream flow values compared to the Tennant, 25% MAF and the Q50 methods.The application of a habitat model (PHABSIM) at Catamaran Brook showed that the maximum available habitat, expressed as weighted usable area (WUA), was observed at a discharge close to the mean annual flow. Results also showed more habitat for salmon parr than for fry at maximum available habitat (optimal habitat), and this optimal habitat was at a higher flow for parr than for fry. The results from hydrologically-based methods were compared to the maximum value derived from the PHABSIM method. This comparative study showed that habitat was reduced by 30% to 80% of the maximum WUA calculated by PHABSIM depending upon which hydrologically-based in-stream flow technique was applied. Habitat (WUA) resulting from the Tennant and the 25% MAF methods derived flows represents approximately 70% of the maximum available habitat. Results from the application of the median monthly flow method (Q50) showed in-stream flow providing over 50% of maximum available habitat. The 90% flow duration method and low-flow frequency method (7Q10) showed habitat values in the range of 20% to 40% of maximum. The application of these latter two methods clearly limits the available habitat for the protection of aquatic resources and they were therefore not recommended for use in in-stream flow studies in this region. Instead, methods such as Tennant and 25% MAF should be used. The Q50 method may be used with caution as its use results in habitat availability slightly over 50% of maximum WUA

Modélisation stochastique de la température de l'eau en rivière

Cette étude présente l'application d'un modèle stochastique de prédiction de la température de l'eau en rivière. L'analyse porte sur les variations imputables aux conditions naturelles et sur une évaluation des performances du modèle une fois appliqué au ruisseau Catamaran au Nouveau-Brunswick (Canada). Ce modèle stochastique est développé selon l'approche de Box et Jenkins (1976) basée sur les séries temporelles des températures de l'eau et de l'air. Le modèle a été calibré avec des données de 1990. L'évaluation de performance comprend une analyse des séries résiduelles et le calcul des erreurs quadratiques moyennes. Les résultats montrent que l'erreur quadratique mensuelle varie de 0,42 °C en juillet 1990 (année de calibration) jusqu'à 2,96 °C en septembre 1992. Finalement, une discussion est menée pour souligner les avantages et les inconvénients relatifs à cette approche.Water temperature is a very important parameter not only in water quality studies but also in biological studies. For instance, salmonids can be adversely affected by natural high stream water temperatures or by those resulting from anthropogenic sources such as deforestation. To predict stream water temperatures, two different approaches have been used; the deterministic and stochastic approaches. The deterministic approach consists of a physical model based on the energy budget (solar radiation, convection, etc.) and the physical characteristics of the stream (water depth, stream cover, etc.). The stochastic modelling approach consists of studying the structure (autocorrelation) of the stream water temperature time series and its dependence on air temperatures (cross-correlation).The purpose of this study is to develop and test the performanoe of a stream water temperature model using a stochastic approach to predict water temperatures in rivers under natural conditions. The performance of such an approach was tested using data from Catamaran Brook, a small stream in New Brunswick (Canada). It differs from previous studies in that most others were on larger river systems.This stochastic model incorporates the Box and Jenkins method (1976) which relates the time series data to both water and air temperature residuals. To calculate the residuals of both air and water temperatures, a seasonal component was first estimated using Fourier series analysis. This seasonal component better represents the long-term trend in air and water temperatures for the studied period or season (i.e. increasing water temperatures at first, then reaching a maximum during the early part of August and decreasing again later in the season). The Fourier series with one harmonic was chosen for the analysis as it has been shown in previous studies that the first harmonic represents most of the variation within the stream water temperature variable. The model was calibrated using the Box and Jenkins method and Catamaran Brook data from 1990. This analysis consist of determining a transfer function relating present water temperature residuals to past water and air temperature residuals including present air temperature residuals and a random component. The random component (also called « noise series ») of the model is a normally distributed variable with a standard deviation calculated using the calibration period. After the calibration period, subsequent years or post-calibration years were analyzed to predicted stream water temperatures with the model using air temperature data only.A study of residuals between predicted and measured stream water temperatures showed very good results during the calibration year (1990) with a calculated root-mean square error of 0.75°C. The predicted temperatures during post calibration years (i.e. 1991 and 1992) were good and the root-mean-square errors were similar to previous studies (e.g. Marceau et al. 1986) with values of 1.45°C and 2.10°C respectively. The measured stream water temperatures during the post-calibration years were only used to estimate the relative performance of the model as opposed to a forecasting model which utilizes actual measured temperatures.At Catamaran Brook is has been observed that natural variation in air temperatures can have an influence on the performanoe of the model. When air temperatures were recorded higher or lower than the long term values (normal temperatures) calculated by the Fourier series analysis, the predicted water temperatures was not as good. For instance it was observed that during September of 1992, during which time the air temperature was higher that normal, the performance of the model was not as good with a root me an squared error of 2.96°C. However, during July 1992, below normal air temperatures were also recorded and a very good prediction of stream water temperatures in Catamaran Brook was achieved with a root me an square error of 0.98°C. In general, satisfactory prediction of stream water temperatures was achieved using the Box and Jenkins stochastic modelling approach

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

Évaluation de l'applicabilité d'une méthode statistique aux variations saisonnières des relations concentration-débit sur un petit cours d'eau

Les paramètres chimiques jouent un rôle important dans l'équilibre des écosystèmes aquatiques. De nombreuses études ont déjà démontré que les caractéristiques chimiques d'un cours d'eau peuvent changer avec les saisons. Cette étude a pour but de revoir les relations débit- concentration sur un petit cours d'eau, dans le contexte des variations entre deux périodes climatiques. Pour ce faire, une analyse de régression entre le débit et six paramètres de qualité de d'eau (sodium, magnésium, conductivité, pH, azote total et le carbone organique dissous) provenant d'un petit bassin versant forestier (ruisseau Catamaran, N.-B., Canada) a été réalisée afin de déterminer la différence entre la saison sans glace et la saison avec glace. Des échantillons mensuels d'eau ont été récoltés sur le ruisseau Catamaran depuis 1990. Les analyses chimiques faites sur ses échantillons ont permis de déterminer les concentrations des paramètre étudiés. La plupart des variables de qualité ont démontré une relation significative avec le débit, sauf l'azote total. Les coefficients de détermination variaient entre 0.752 et 0.898, exception faite du carbone organique dissous dont le r2 était de 0.294. La conductivité était le paramètre dont le débit expliquait le plus la variance. Une étude des rapports des sommes des carrés des résidus a permis de déterminer que seul le pH requiert un modèle différent pour la période sans glace et la saison avec glace. Les variations saisonnières de la relation débit-pH revêt une importance significative pour les ruisseaux comme celui de Catamaran, qui incluent de nombreux habitats pour le saumon de l'Atlantique. Les résultats des analyses de régressions indiquent que lorsque la géochimie est plus complexe, comme c'est le cas pour le pH, il faut diviser les séries temporelles en sous-composantes saisonnières avant de tenter d'établir une relation débit-concentration.The chemical composition of water is of great importance to ecosystem functioning and in habitat management. Many studies have already shown that the chemical characteristics of a stream change with seasons. These variations have a strong impact on the ecosystem, especially on fish populations. The objective of this study is to quantify the relationship between the logarithm of discharge and six water quality parameters (sodium, magnesium, conductivity, pH, dissolved organic carbon and total nitrogen) for a small forested catchment (Catamaran Brook, N.B., Canada) and to verify the importance of seasonality. Monthly water samples have been gathered at Catamaran Brook since 1990. Detailed water chemistry performed on these samples provided a data base for this project. Various linear regression models were tested to verify if regressions were required for the winter season. The criterion used was the ratio of the squared sum of residuals for each data set, which follows a Fisher distribution. Of the six water quality parameters, all except total nitrogen showed a significant relationship with discharge. On an annual basis, the coefficient of determination (r2) varied between 0.752 and 0.898, except for dissolved organic carbon which showed a r2 of 0.294. Of the studied parameters, conductivity was the parameter for which discharge explained the most variance. Ratios of the squared sum of residuals were analyzed to verify the need for different regression models for the ice-covered and ice-free seasons. Only streamwater pH required 2 different models. This is of specific importance and interest because of an important salmon population in Catamaran Brook. Other researchers have shown that salmonids can be negatively impacted by pH depressions during snowmelt events.These results show that most dissolved ions which follow simple geochemical reactions can be modelled year-round with only one linear regression. When the geochemistry is more complex, such as in the case of pH, linear regression models can sometimes be used, provided that the annual time-series is divided into seasons with relatively homogenous hydrological and geochemical functions

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

The Arab world's contribution to solid waste literature: a bibliometric analysis

BACKGROUND: Environmental and health-related effects of solid waste material are considered worldwide problems. The aim of this study was to assess the volume and impact of Arab scientific output published in journals indexed in the Science Citation Index (SCI) on solid waste. METHODS: We included all the documents within the SCI whose topic was solid waste from all previous years up to 31 December 2012. In this bibliometric analysis we sought to evaluate research that originated from Arab countries in the field of solid waste, as well as its relative growth rate, collaborative measures, productivity at the institutional level, and the most prolific journals. RESULTS: A total of 382 (2.35 % of the overall global research output in the field of solid waste) documents were retrieved from the Arab countries. The annual number of documents published in the past three decades (1982–2012) indicated that research productivity demonstrated a noticeable rise during the last decade. The highest number of articles associated with solid waste was that of Egypt (22.8 %), followed by Tunisia (19.6), and Jordan (13.4 %). the total number of citations over the analysed years at the date of data collection was 4,097, with an average of 10.7 citations per document. The h-index of the citing articles was 31. Environmental science was the most researched topic, represented by 175 (45.8 %) articles. Waste Management was the top active journal. The study recognized 139 (36.4 %) documents from collaborations with 25 non-Arab countries. Arab authors mainly collaborated with countries in Europe (22.5 %), especially France, followed by countries in the Americas (9.4 %), especially the USA. The most productive institution was the American University of Beirut, Lebanon, with 6.3 % of total publications. CONCLUSIONS: Despite the expected increase in solid waste production from Arab world, research activity about solid waste is still low. Governments must invest more in solid waste research to avoid future unexpected problems. Finally, since solid waste is a multidisciplinary science, research teams in engineering, health, toxicology, environment, geology and others must be formulated to produce research in solid waste from different scientific aspects

Hydrologie et environnement

L'estimation des débits de crue est d'une importance majeure pour la conception des ouvrages d'art et la gestion des ressources hydriques. La mauvaise évaluation de ces débits entraîne un sur-dimensionnement ou un sous-dimensionnement des ouvrages hydrauliques, induisant ainsi un investissement excessif ou un risque démesuré d'inondations. Un modèle de données chronologiques de durée partielle est retenu pour l'étude des crues. Ce modèle nécessite d'abord l'estimation du seuil de troncature qui définit la série chronologique intermittente à analyser. Ce paramètre joue un rôle majeur dans la solution du problème malgré le peu d'importance que lui reconnait la littérature. Le but de la présente étude est d'élaborer une méthode graphique comme guide dans le choix du seuil. Par la suite, cette méthode est appliquée à 238 stations hydrométriques au Canada. Une fois le seuil obtenu pour ces stations hydrométriques, une régionalisation utilisant l'analyse de régression a été réalisée. Ces équations régionales peuvent servir à estimer le seuil d'une nouvelle série hydrologique sans avoir à passer par la méthode graphique. (Résumé d'auteur

Rainfall - runoff modelling in Muwaqqar Watershed

French version available in IDRC Digital Library: Modélisation pluie - débit en régions arides et semi-arides : cas du bassin Muwaqqa