Contaminant Source Identincation Of River Chemical Spills Based On Mobile Platform

Recently, the surface water pollutions caused by chemical and heavy metal were rising dramatically and becoming a big threat to people’s life. When such accidents occurred, the most challenging and significant first step was to identify the source of pollutants immediately and precisely. In order to control the pollution scientifically, the location, total quantity and release time of contaminants need to be found out. However, it took great efforts to get such source information especially at the beginning of pollution issues. Meanwhile, researches, concerning about pollutants source identification, were mainly focused on groundwater so far. Even if a few researchers who focused on surface water, there are seldom cases that calculate the source information directly.This article developed a novel inversion algorithm used to calculate the source information of surface water pollution which combined the theoretical research with mobile water quality monitor platform. It was proved to have three advantages:high precision, easy to apply and strong feasibility based on a series of experiments and numerical analysis:theoretical arithmetic, computer simulation and experiments both in the lab’s scale model and in the real river. It was utility to apply this method into real practice.Main contents of this article:1) Developed a novel algorithm to identify the source of pollution in one-dimension river. Partial derivatives in time-space domain were conducted to calculate the source information directly. The results of some numerical experiments on four main factors indicated that this algorithm had good performance, the relative errors of pollution source location was less than10%approximately;2) Particle swarm optimization algorithm (short for PSO) was introduced in the scenarios of two-dimension lakes with multiple point source pollutions. The outcome of computer simulations showed PSO can satisfy the requirements of source identification with high efficiency and precision. A complete process to apply PSO into real practice with mobile water quality monitor platform was also introduced together with some suggestions to improve the performance of this method;3) An experiment use NaCl as pollutant tracer and conductivity as detection parameters was completed in a scale model in the lab. The results proved that the method developed in this article can work in such environment, the relative error in source location was less than30%;4) An attempt for testing the performance of this method together with mobile water quality monitor platform in real river was made. The reasons why can’t detect useful data during this experiment was analyzed and suggestions for further research in real river was gave out.