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Indicateurs géostatistiques de la pollution des cours d'eau

Abstract : In order to assess river quality, different parameters such as nutrients concentrations are measured in different monitoring stations, setting up a very important but heterogeneous database. The French evaluation system of water quality recommends to summarize the information contained in these measurements by a few statistical indicators such as the annual mean of concentrations or the 90% quantile. They are estimated using the classical statistical inference based on hypothesis proved to be incorrect: time correlations and seasonal variations are ignored. Actually, in France, nitrate concentrations are generally higher in winter. Biases and confidence intervals can be reduced by kriging or segments of influence and a linear interpolation of the empirical quantile is proposed. Methods are analyzed theoretically and experimentally on the Loire Bretagne basin. Estimating indicators along a stream network then requires specific models of random functions because usual covariance models are no longer valid on such structures. We propose a global model of random functions along a tree graph introducing the concept of "elementary thin streams", defined by the whole set of paths between sources and outlet. At each point of the network, the river is considered to be the linear combination of these streams on which one dimensional stationary random functions are defined. An application to water discharge on the Moselle Basin (north-east of France) is presented
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Submitted on : Wednesday, September 6, 2006 - 8:00:00 AM
Last modification on : Friday, October 23, 2020 - 4:48:31 PM
Long-term archiving on: : Thursday, September 30, 2010 - 7:31:35 PM

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Caroline Bernard-Michel. Indicateurs géostatistiques de la pollution des cours d'eau. Sciences of the Universe [physics]. École Nationale Supérieure des Mines de Paris, 2006. English. ⟨pastel-00001878⟩

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