Evaluation of groundwater quality in Changping piedmont plain of Beijing based on BP neural network

Groundwater quality is closely related with human health and environmental safety. In the suburb of Beijing, the groundwater quality is heavily concerned. In this study, the groundwater quality in Changping piedmont plain was evaluated based on the single factor evaluation method and comprehensively evaluated based on BP neural network. The Changping district is located was in the northwestern area of Beijing. Considering that the main area affected by human activity was the shallow groundwater, we arranged a total of 12 monitoring wells around the plain area. The depths of wells 1#, 2# and 11# were 130 m, the depth of wells 3#, 4# and 7# were about 125 m, and the depths of wells 5#, 6#, 8#, 9#, 10#, 12# were about 120 m. The groundwater samples were collected on April 16, 2015. A total of 27 indexes were determined including pH value, chloride, sulfide, nitrate nitrogen, ammonia nitrogen, heavy metals, fluoride, and so on. In the single factor evaluation, the groundwater quality was evaluated according to the National Groundwater Quality Standards (GB/T14848-93). Based on the single factor evaluation method, water quality in 5 wells of 1#, 4#, 7#, 9# and 11# exceeded the standards. In the 1# well, the turbidity, total hardness, total dissolved solids and nitrate nitrogen exceeded the standards by 1.67, 1.81, 1.48, and 3.08 times, respectively. In the 4# well, the turbidity was 1.33 times exceeding the standard. In the 7# well, the total hardness and total dissolved solids exceeded the standards by 1.2 and 1.15 times, respectively. In the 9# well, the fluoride exceeded the standard by 1.58 times. The ammonia nitrogen in the 11# well exceeded the standard by 3.25 times. Compared the values in 1999, the area with total hardness exceeding the standard was expanded largely. Among the 27 indexes, we chose 17 indexes for the comprehensive evaluation based on BP neural network, including the turbidity, iron, chloride, sulfate, TDS, total hardness, manganese, zinc, potassium permanganate index, nitrate nitrogen, nitrite nitrogen, ammonia nitrogen, fluoride, and so on. The BP evaluation showed that all the 12 wells had the water quality above III. Among the wells, 1 was V grade, 5 were IV grade and 6 were III grade. Compared with the single evaluation results, the comprehensive evaluation based on BP neural network was reasonable. The 1# well had 4 indexes exceeding the standards and thus the water quality was V grade. Compared with previous study, the pollution of nitrate and ammonia nitrogen might be due to surface pollutants infiltration. In the future, the continuous monitoring of shallow groundwater should be conducted, and the surface pollutants infiltration prevention control should be strengthened. The study may provide valuable information for the management of the groundwater in Beijing. © 2017, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.