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| A Linked EFDC-NN model for risk-based load reduction analysis of Lake Fuxian watershed |
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Abstract This study employed an approach linking the Environmental Fluid Dynamics Code (EFDC) model and a Neural Network (NN) model to conduct risk based TMDL analysis for Lake Fuxian in Southwestern China. The EFDC-NN system was developed based on a three-dimensional hydrodynamic-water quality model of the lake, and NN functional approximators of the EFDC model using the 30-day moving average concentration of target nutrients as predictors. The developed NN functional approximators were then applied to conduct risk based TMDL analysis. To reach the primary water quality standard with 100% probability, the TP and COD loadings from the watershed still had room for increase by 14%~18% and 9%~11% respectively, but TN must be reduced by 13%~14%. If the water quality compliance probability was relaxed by various levels, it was found that the load reduction requirement will be correspondingly relaxed such that in most cases further increase of watershed loadings are allowed. The results of this analysis provided decision makers with risk based load management requirement for guiding their management plan in this lake watershed.
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Received: 15 December 2012
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