Retraction Note to: Groundwater resource pollution detection and home sports training intervention based on image super-resolution processing

Abstract

In the past few years, due to the vigorous development of China’s industry and the rapid increase in urbanization, a series of adverse effects have been produced, such as the decline of groundwater levels, the pollution of groundwater resources, and the degradation of wetlands. Real-time monitoring of changes in groundwater volume and water quality under the influence of human activities is very important in the current era. It is not only of great significance for achieving sustainable development, but also indispensable for future specific planning. This paper mainly optimizes the design of the monitoring well pattern from the Yukou landfill to the water source of Zhongqiao in P District and establishes three optimization goals of pollution detection probability, early warning response time, and cost. Firstly, the deterministic model of P area was established by image super-resolution processing, and the pollution source was tracked by the software package MODPATH in GMS, so that the early warning response time occupies the primary position in the optimization goal. The first optimization plan was proposed, using Monte Carlo. The method randomizes the parameters of the permeability coefficient K and establishes a random model. Using the risk analysis in the random model, the probability capture area of the mining well at the water source is obtained. The probability of pollution detection takes the first place in the optimization objective. Taking the pollution detection probability as the primary position in the optimization objective, the second optimization scheme is proposed. Through the research on groundwater resource pollution detection and home sports training intervention, we will apply it to real life and promote its rapid development in the future.