Abstract ID: 3.8430 | Accepted as Poster | Talk | TBA | TBA

Ecosystem services provisioning, regulating, cultural, and supporting are essential for sustaining life, economies, and policy frameworks. The Payment for Ecosystem Services (PES) incentivizes environmental conservation by rewarding sustainable practices. This study utilizes data analytics to assess the impact, efficiency, and sustainability of the Ganga’s PES initiative in the National Mission of Clean Ganga in the National River Ganga, India. The analysis examined a diverse dataset covering both environmental and socioeconomic factors included water quality indices, carbon emissions, and biodiversity statistics, while socioeconomic data encompassed population density, agricultural usage, and the economic benefits of ecosystem services. Several pre-processing steps were undertaken to ensure data accuracy and reliability. Data cleaning involved removing null values, duplicates, and inconsistencies, as well as standardizing data. Outlier detection and treatment were conducted using quartile-based analysis. Advanced data visualization tools were employed to create interactive dashboards and comprehensive reports, simplifying complex data for stakeholders and enhancing decision-making processes. A range of analytical methods was applied to derive meaningful insights. Comparative analysis identified trends and discrepancies, such as pollution hotspots through regional water quality assessments. Hypothesis testing validated assumptions regarding the relationship between industrial activities and water contamination, using statistical tests like t-tests and ANOVA. Additionally, these models and A/B testing methodologies were employed to evaluate the effectiveness of various PES-supported conservation practices. The integration of SQL and Python streamlined data collection and analysis workflows, reducing manual effort and minimizing errors. Predictive analytics and data-driven strategies highlighted critical pollution hotspots and established significant correlations between industrial discharge and water quality degradation. These insights help to policy framework for regulating the targeted conservation efforts. This study confirms that PES can be a powerful mechanism for balancing ecological sustainability with economic development. However, its long term success depends on data-driven policy refinements, stricter industrial regulations, and sustained investment in monitoring.