Application of Artificial Neural Network for Forecasting the Water Quality in the Watershed and Reservoir
Date Issued
2008
Date
2008
Author(s)
Lin, Sin-Hong
Abstract
Eutrophication and soil deposition problem can affect water quantity and quality in the reservoir. In a heavy rainfall of typhoon, a river with a large number of pollution and nutrient flow into the reservoir, it can reduce the reservoir’s volume and cause eutrophication problem. It will affect water chemistry’s properties and quantity. Certain species of algae cause taste and odor problems in drinking water. These problems become prominent as the water body becomes more eutrophic. The purpose of thesis is using ANN (Artificial Neural Network) to predict the suspended solid、nutrient (nitrogen and phosphorous) and algae in the watershed and reservoir.NN is used in this study to take the place of the BASINS and CE-QUAL-W2 model to real time forecast the water quality in Shi-men watershed and reservoir. In the BASINS, ANN trains Discharge、SS、PO4、NH3-N and NO3-N. The correlation coefficients are all over 0.67. In the CE-QUAL-W2, ANN trains Chl-a、PO4、NH3-N、NO3-N and DO. The correlation coefficients are all over 0.65. This shows ANN can use the continuous data to forecast the water quality at the moment in the watershed and reservoir.
Subjects
eutrophication
water quality
ANN
Shi-men reservoir
Type
thesis
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