The total pollutant load allocation (TPLA) can be transformed into an optimization problem with regards to water quality constraints. The optimization calculation may become very time consuming when the number of water quality constraint equations is great. A Trial and Error Method (TEM) to remove the redundant points was first introduced through iterative calculations under structure and non-structure model grids. The TEM was applied for the TPLA in the Bohai Sea in China. The calculation time was reduced to about 2 min under the condition that 103,433 model grids met the water quality standards. In the best case, the optimization efficiency was improved by 98.9%. The allocation results showed that approximately 90% of total nitrogen (TN) load should be reduced in the 56 pollution sources around the Bohai Sea; of these values, roughly 85% of the reduction could come from 10 pollution sources.
Improving optimization efficiency for the total pollutant load allocation in large two-dimensional water areas: Bohai Sea (China) case study
CRITTO, Andrea;
2017-01-01
Abstract
The total pollutant load allocation (TPLA) can be transformed into an optimization problem with regards to water quality constraints. The optimization calculation may become very time consuming when the number of water quality constraint equations is great. A Trial and Error Method (TEM) to remove the redundant points was first introduced through iterative calculations under structure and non-structure model grids. The TEM was applied for the TPLA in the Bohai Sea in China. The calculation time was reduced to about 2 min under the condition that 103,433 model grids met the water quality standards. In the best case, the optimization efficiency was improved by 98.9%. The allocation results showed that approximately 90% of total nitrogen (TN) load should be reduced in the 56 pollution sources around the Bohai Sea; of these values, roughly 85% of the reduction could come from 10 pollution sources.File | Dimensione | Formato | |
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Deng et al_Marine Pollution Bulletin_2017_114_269-276.pdf
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