The Study Of Slow Sand Filtration Technology On Surface Water Treatment Surrounding Xining

By joining the mentor of the low-cost water purification research projects of Utah- qinghai international alliance of science and technology cooperation projects, have known something of residents of drinking water in the mountainous area of Qinghai, Qinghai mountain residents would like to drink clean, sanitary, safe drinking water as the starting point in this paper,set in the low-cost purification of cellar water in Qinghai mountain area, intended to address the needs of the rural drinking water quality. purification of pit water By slow sand filtration, as well as analyze the changes of water quality; study on slow sand filtration in different regions and different types of pit water, to ensure that the residents of mountainous areas with the most economical, simple, effective, and natural means to ease the use of drinking water.experimental study on water quality of Huangshui River slow sand filtration an d purification. We should be clear aboutthe principle and influencing factors of water purification of slow sand filtration. comparative analysis of water quality in differen t time periods, The results showed that after 4 hours of purification, the water quality standards have reached the standard of drinking water. The removal rates of turbidit y, ammonia nitrogen, total hardness, total dissolved solids, COD and so on were 99.8%, 92.2%, 13%, 32%, 84%, respectively; the acidity, nitrite nitrogen, nitrate nitrogen, metal ions, fluoride ions did not exceed the standard, Purification 8 hours after the best water quality;Take wage plant wastewater as the research object to experiment. CODCr remo val rate was 72% after treatment, the concentration was 28.8 mg/L, the removal rate of ammonia nitrogen was 66%, and the concentration was about 0.7 mg/L, comply w ith the environmental quality standards, the effect is good;According to the spatial distance monitoring indicators of water quality standards and water quality custom evaluation index to evaluate the index as the dependent variable, turbidity, pH, COD, ammonia, nitrate, nitrous, total dissolved solids, fluoride ion multivariate independent variable regression analysis.Regression equation as follows: Y=0.114X1-0.38X2-0.056X3+1.461X4-0.421X5+0.628X6+0.035X7-44.456X8+14.429Multiple correlation coefficient R = 0.985; BP artificial neural network application to monitor indicators of the input layer to customize the evaluation index for the output layer, the BP artificial neural network model, the correlation coefficient R = 0.999. Linear and nonlinear model has good prediction.