| NITRATE CHANGES EVALUATION USING NEURAL NETWORK AND GEOSPATIAL INFORMATION SYSTEM IN THE GOLESTAN PROVINCE |
| Paper ID : 1125-SMPR |
| Authors: |
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Motahare Kolbadinejad *1, Saeed Behzadi2 1The Ministry of Interior of the Islamic Republic of Iran, Tehran, Iran 2Department of Surveying Engineering, Faculty of Civil Engineering |
| Abstract: |
| Recently, one of the problems of human societies is the pollution of groundwater with nitrate. Nitrate has been studied as the best indicator for the chemical contamination of groundwater due to its high water solubility, low absorption and the stability of its composition in water. Nowadays, groundwater contamination is increasing due to chemical and industrial activities. Therefore, it is necessary to identify the vulnerable areas of the region to prevent groundwater contamination. In this research, we have tried to find a method for modelling nitrate pollution for villages of Golestan province using a smart algorithm such as artificial neural network model. In this research, firstly, the factors affecting pollution such as topography, slope, position of wells, geology, etc. are identified. Then, the effect level of each of which variables is calculated using different learning methods. Finally, after determining the extent of the effect, a map of the nitrate pollution is obtained. The results obtained from the nitrogen concentration in the pollution maps show that the accuracy of proposed model is acceptable, and the obtained RMSE is near 0.93. |
| Keywords: |
| Artificial Neural Network, Geospatial Information System, Nitrate, Groundwater pollution |
| Status : Conditional Accept (Poster) |
