Quantitative and systems thinking approaches to water contamination in shenzhen: analysing stakeholder impact and correlation of water quality

Abstract

From a quantitative, systems thinking perspective, this study examines the effect of stakeholder activities on water contamination in Shenzhen. The research studies 5 variables, Chemical Oxygen Demand (COD), industrial discharge, agricultural fertilizer use, sewage treatment rate and government monitoring intensity using a multiple linear regression model on a simulated dataset of 1,000 observations. Results show that industrial discharge (p < .001) and fertiliser use (p < .001) increase COD significantly, reflecting strong contributions from manufacturing and agriculture in the water basin. Conversely, COD negatively relates to sewage treatment rate (p < .001) and monitoring intensity (p < .001), suggesting that both play an important negative role in mitigation. The finding is consistent with previous literature on urban water pollution in the Pearl River Delta and also provides empirical evidence of the influence of regulatory infrastructure and environmental governance. The variance explained in COD is 43.2 % (R² = 0.432) indicating that the model explains how stakeholder-related variables influence COD. According to the study, whether this problem is solved using a dual strategy that involves stricter regulation of industrial and agricultural discharges coupled with larger investments in real-time monitoring and expansion of wastewater treatment infrastructure, the impact is much greater. Then, this research offers actionable insights to policymakers and environmental agencies to address water contamination and guarantee safe water access in rapidly urbanising settings like Shenzhen.