Sensitivity analysis and parameter estimation for evaluating the impact of water pollution on aquatic species

Abstract

Aquatic ecosystems are highly sensitive to changes in environmental conditions, making it essential to identify the key factors that influence the dynamics of species populations. This study introduced a nonlinear mathematical model, analyzed it, and identified key sensitive parameters that were used in assessing the impact of water pollution on aquatic ecosystems. Global sensitivity analysis was conducted to determine the parameters significantly impacting aquatic species populations. Parameters were estimated using the least squares method, while sensitivity analysis was performed via Partial Rank Correlation Coefficient (PRCC) and Latin Hypercube Sampling (LHS). Parameters related to organic pollutant growth rates, pollutant absorption rates, and oxygen penetration were identified as positively affecting aquatic species populations by enhancing nutrient availability and metabolic activity. Conversely, competition and inorganic pollutant discharge were found to impact aquatic populations negatively. These findings highlight the critical role of managing sensitive parameters such as pollutants and competitive interactions to maintain and improve the health of aquatic ecosystems.