Optimization Research On Groundwater Pollution Monitoring Network Of Typical Water Sources In Pinggu District,Beijing

In recent years,due to the rapid development of industry and agriculture and the rapid progress of urbanization in China,the following hydrogeological problems,such as the continuous decline of groundwater level,land subsidence,seawater intrusion,and ecological environment problems,such as water quality deterioration,water pollution,wetland degradation,can not be ignored.It is an important measure to monitor the change of groundwater quantity and water quality under the influence of human activities in real time and to recognize its regularity.However,the construction of groundwater monitoring network in China is still lack of systematic and scientific.In this paper,the monitoring well network from Yukou landfill to Zhongqiao water source in Pinggu District is optimized,and three optimization objectives are established: pollution detection probability,early warning response time and cost.Firstly,the deterministic model of Pinggu District is established by GMS,and the particle tracking of pollution source is carried out by using the software package MODPATH in GMS,so that the early warning response time takes the first place in the optimization objective,and the first optimization scheme is put forward;Moreover,based on the randomness and uncertainty of groundwater system,the parameters of the permeability coefficient K are randomized using the Monte Carlo method,and the stochastic model is established.The probability capture area of the exploitation well in the water source area is obtained by using the risk analysis in the stochastic model,so that the pollution detection probability takes the first place in the optimization objective,and the second optimization scheme is proposed.The conclusion is as follows:(1)Optimization based on particle tracking: determine the location of new monitoring wells according to the location of particle arrival over time.After optimization,it is recommended to add 13 monitoring wells and retain the original 4 monitoring wells,remove 2 redundant wells,a total of 17 monitoring wells.(2)Optimization based on stochastic simulation: add up the probability acquisition areas of the exploitation wells in the water source area with pollution sources in the acquisition area,and optimize the monitoring wells on this basis.After optimization,retain the original 5 monitoring wells,remove 1 monitoring well,and add 5 monitoring wells in the area with high probability in the acquisition area,a total of 10 monitoring wells.(3)The two schemes have different perspectives.The first scheme can know the occurrence of pollutants earlier and has a long warning response time,but the probability of detecting pollutants in some wells is small,and the number of new wells is large and the cost is high.The second scheme basically retains the original five monitoring wells,which can ensure the continuity of monitoring well data,on the basis of only five new monitoring wells Compared with scheme I,the detection probability is larger,which can obtain more data at a limited cost,but the early warning response time is short.