Méthodologie d'analyse détaillée de la contamination par tronçon du fleuve Saint-Laurent par modélisation numérique : le cas du lac Saint-Pierre

Dans le cadre du Plan d'Action Saint-Laurent, une méthodologie détaillée d'analyse de la contamination par tronçon faisant appel à la modélisation numérique a été développée. Une méthode de simulation utilisant le mouvement aléatoire de particules a servi à élaborer le logiciel PANACHE. Les concentrations sont obtenues en post-traitement en attribuant une masse de contaminant aux particules du modèle. Les champs de vitesses servant à calculer leurs mouvements sont produits à l'aide d'un modèle bidimensionnel aux éléments finis. Une nouvelle approche pour l'analyse de la contamination est proposée. Celle-ci s'inspire de la méthodologie de modélisation des micro-habitats populaire dans le domaine de l'hydrobiologie. Le résultat apparaît sous la forme d'Aires Pondérées Inutilisables (API), c'est-à-dire, des surfaces où certains critères de qualité de l'eau ne sont pas respectés dans les zones de mélange. Ce système Informatisé a été élaboré sur une plate-forme INTEL/386-486 - OS2/PM.ContextThe St-Lawrence Center, part of Environment Canada, undertook a few years ago the very ambitious project of studying the toxic contamination of the St-Lawrence River. In collaboration with the Institut National de la Recherche Scientifique - Eau, a sub-project based on numerical modeling was defined in order to analyze contaminant propagation from industrial and municipal effluents into the river system.GoalsThe specific goals of the project were the following :1) to provide a precise quantification of contaminant concentrations in the effluent plume al a convenient scale;2) to analyze areas influenced by main tributaries and different water masses entering the river reach;3) to map and quantify areas as compared to water quality criteria ;4) to provide a method to select relevant hydrological events as a significant part of the analysis frameworkMethodologySome basic choices were made at the beginning of the project :1) the analysis framework emphasis the instream water quality instead of the effluent water quality;2) numerical modelling was the main tool used to evaluate the water quality;3) as far as possible references to public regulations were incorporated;4) a strong complementarity of different computer tools was favoured : Geographical Information Systems, Database management systems, simulation models;5) the numerical solution method for the transport diffusion model is typically Lagrangian : the Random Walk Method;6) the contamination analysis uses the so-called « Weighted Unusable Area » method to quantify areas that do not respect some water quality criteria.A typical contamination analysis project based on numerical modelling includes the following steps (fig 2) :1) a preliminary study to determine the main characteristics of the problem and to choose the best strategy to analyze it;2) field measurements essential to the calibration and validation of the computer model;3) hydrodynamic modelling provides the basic data on the flow field; this step includes the calibration and the validation of the model, as well as the prediction of the flow fields corresponding to well-defined and contamination relevant hydrological events;4) hydrological analysis identifies the relevant flow events chat will further be used in the mode) prediction ; this approach allows standardization of this very important input data set and avoids arbitrary choices of flow field;5) transport-diffusion modelling constitutes the main step; it provides the chemical species concentrations downstream from the effluent discharge and affords an estimate of the overall water quality of the reach, as influenced by the main tributaries. This step includes the calibration and the validation of the model which precedes the prediction exercise;6) contamination analysis necessitates the choice of appropriate and relevant water quality criteria ; we propose a new approach, inspired by the Instream Flow Incremental Methodology often used to define the quality and availability of fish habitat in river reaches, to implement this step.Numerical methodsAs previously mentioned, the project included the development of a Lagrangian model to simulate the transport of solutes in a two-dimensional steady-state river flow. We will emphasize this point. The main objective of the software development was to provide an efficient and user-friendly management tool for the public agencies. Many analytical test cases helped in the choice of the best numerical algorithms, non-physical related parameters, and in the validation of the computer code. Furthermore, the results of two dye tracing experiments performed in conjunction with airborne remote sensing techniques provided data to validate the model on the St-Lawrence River (fig. 5, 6, land 8 illustrate different simulation results corresponding to the different tasks mentioned previously). In the next paragraphs, we will summerize the basic mathematical and numerical concepts implemented in the simulations.To simulate solute transport in water media (porous or free surface), one usually uses eulerian methods which lead directly to concentration values. The solution algorithm presented here is rather based on a Lagrangian method which offers an explicit control over the additional numerical diffusion associated with every discretization method. This approach, also called the Random Walk Method (illustrated in fig. 3), or Particle Tracking Method, is more and more often used to solve hyperbolic equations. So far, the literature does not provide many applications of this method to solute transport in free surface flow. Oil spin modeling is a domain where many applications have been reported.The propagation of solute matter in free surface flow is mathematically described with momentum, mass and solute conservation equations. Since the Random Walk solution method of the transport-diffusion equation (equ. 1) requires hydrodynamic data to calculate the mean transport on streamlines along with dispersion, independent simulations providing the necessary flow field data (velocities, diffusivities, depths) have to be performed before undertaking the transport-diffusion tasks. For this purpose, the Navier-Stokes shallow water equations have become a well known tool to represent flow field in shallow waters. However, one should be aware of some often neglected but important aspects of such models, such as moving boundaries and turbulence closure. Solution techniquesTwo main goals were kept in mind during the implementation of the various algorithms : precision of results and fast computation. The following choices were made to achieve these objectives :1) A finite element discretization and solution method provides and carries hydrodynamic Information, but particles are tracked on a finite-difference grid (mixed discretization principle).2) The convective component of the movement is realized by moving the grid instead of the particles (shifted grid principle).3) Computation of concentrations optimizes smoothing while minimizing artificial diffusion (controlled effusive smoothing principle).4) When a section of the plume is described in a steady state « regime », it is mot necessary to continue the simulation on that section to proceed downstream ; the simulation is divided in almost independent sections (convolution principle).5) The particles have an a priori nondimensional weight and a unit concentration is calculated from these (unit plume principle).6) The real concentration is linearly dependent on the pollutant loads introduced into the milieu (linearity principle).The Weighted Unusable Area MethodThe Weighted Unusable Area method provides a convenient means to compare effluent plume water quality to water quality criteria as well as to quantify areas that do not comply to them. A comparable method is widely used to define the quality and availability of fish habitat downstream from regulation reservoirs, with the purpose of establishing minimum guaranteed flow discharge to protect target species (the Instream Flow Incremental Methodology : IFIM). The method consists essentially of computing areas within the analysis domain weighted by a certain factor that represents the exceedence of certain water quality, criteria. Among different options to define the weighting factor, all incorporating the effective contaminant concentration, we defined the following :1) the ratio of the concentration to the water quality criterion without consideration of exceedence or compliance;2) weighting factor equal to 1 only if the concentration exceeds the criterion (non-compliance);3) option #1, but using the concentration results corresponding only to the effluent plumes excluding the ambient water quality of the reach ; this emphasizes individual corporate responsibility (proposed for implementation);4) option 11, but with the ratio increased by a power « n », a procedure that emphasizes the non-linear increase of toxicity related to the exceedence of the criterion (could be useful for academic purposes).We also propose a Global Weighted Unusable Area concept to combine all the different chemical species present in an effluent plume. The combination is made possible using the specific criterion corresponding to each species. This procedure leads to a new state variable that represents Contamination Standard Units

Estimation et évaluation d'incertitude d'indicateurs agrométéorologiques par télédétection en vue de supporter la lutte phytosanitaire

La caractérisation de la variabilité spatiale des conditions agrométéorologiques est essentielle à la prévision des insectes ravageurs et des maladies des cultures (IRMC) et à leur gestion spécifique par site. L’objectif de notre étude a été de modéliser, estimer et spatialiser à l'échelle locale et régionale des indicateurs agrométéorologiques (IAM) ainsi que leurs incertitudes. L'imagerie multispectrale et la thermographie infrarouge aéroportée ont été utilisées pour estimer à l'échelle locale des IAM dont le NDVI (Normalized Difference Vegetation Index), la proportion de couverture végétale (PCV), la température de surface (TS) et l'indice TVDI (Temperature/Vegetation Dryness Index) de l’humidité de surface. Deux nouveaux indicateurs ont été proposés: l’indicateur MTVX (Modified Temperature/Vegetation Index) de la température de l’air près de la surface (TAPS), et l’indice des conditions de stress thermique des cultures (ISTC). Les IAM ont été estimés à l'échelle régionale à l’aide des images satellite AVHRR (Advanced Very High Resolution Radiometer). Les incertitudes résultantes (ICR) des IAM ont été formulées sur la base de la loi de propagation des incertitudes. La spatialisation des IAM a été réalisée selon une approche dynamique basée sur un krigeage multivariable intégrant les facteurs dominants de leur variabilité spatiale. Les IAM ont démontré de fortes variabilités intraparcellaires, locales et régionales. Ils permettent de répondre aux besoins de caractérisation des conditions agrométéorologiques qui régissent les occurrences et le développement des IRMC. Des corrélations élevées ont été observées entre les mesures d'occurrence de plusieurs IRMC des cultures maraîchères et les indicateurs thermiques TS, TVDI, MTVX et ISTC. Celles-ci démontrent que les conditions de température qui prédominent à la surface des champs influencent davantage les IRMC. Ces indicateurs devraient être privilégiés dans la prévision des IRMC et dans la mise en place d’approche de gestion intégrée des ravageurs. Les aspects novateurs de la modélisation des indicateurs MTVX et ISTC, la formulation des ICR et leur estimation en tout point du territoire, la mise en place d'un cadre formel basé sur les ICR et un coefficient de performance globale pour évaluer et comparer différents modèles d'estimation des IAM, ainsi que l’approche de spatialisation dynamique, constituent des apports majeurs de notre étude.The characterization of the spatial variability of agrometeorological conditions is essential to the prediction and site-specific management of crop pests and diseases (CPD). The aim of our study was to model, estimate and spatialize local and regional agrometeorological indicators (AMI) and their uncertainties. Airborne multispectral imaging and infrared thermography were used to estimate AMIs at local scale such as the Normalized Difference Vegetation Index (NDVI), Percent Canopy Cover (PCC), Surface Temperature (ST) and the Temperature/Vegetation dryness index (TVDI), an indicator of surface moisture. Two new indicators were also proposed: the Crop Heat Stress Index (CHSI) and the Modified Temperature/Vegetation Index (MTVX), an indicator of the near-surface air temperature. AMIs were estimated at the regional scale using satellite images from the Advanced Very High Resolution Radiometer (AVHRR). The formulation of resultant uncertainties (RUC) of AMIs was based on the law of propagation of uncertainty. The spatialization of observed AMIs in-field was performed using a dynamic approach based on a multivariate kriging that integrated the dominant factors of their spatial variability. AMIs showed a high spatial variability at intra-site, local, and regional scales. They meet the need of the characterization of agrometeorological conditions under which the CPDs appear and develop. High correlations were observed between measures of the occurrence of several vegetable CPDs and thermal indicators like ST, TVDI, MTVX, and CHSI. These correlations show that surface temperature and near-surface air temperature have the most influence on the occurrence and the development of CPDs. Therefore, these indicators should be used in forecasting and in the implementation of an Integrated Pest Management (IPM) approach. Major contributions of our study are the innovative aspects of the modeling of indicators MTVX and ISTC, the formulation of the RUs of AMIs and their estimation anywhere in the area of interest, the establishment of a formal framework based on RUs and a global performance index to evaluate and compare different models used to estimate AMIs, and the dynamic spatialization approach

Estimation des paramètres biophysiques des cultures agricoles par télédétection aéroportée

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