Spatiotemporal Evolution of Coastal River Water Quality Based on Dynamic Interactive Visualization

To address the limitations of traditional spatiotemporal water quality analysis methods in dynamic interaction and real-time decision support, a technical framework integrating the Nemerow Index with WebGIS dynamic visualization is constructed. This framework reveals the spatiotemporal evolution patterns of coastal river water quality and its gradient impact on the marine environment, providing scientific support for integrated land-sea pollution management. Based on water quality monitoring data from a coastal river during 2021-2022, the Nemerow Index is employed to assess the comprehensive water quality levels. A data service interface is developed using the Flask framework, and Gaode Map API is integrated to build an interactive WebGIS platform that supports real-time data updates and dynamic classification markers: blue for Class I, red for Class II, yellow for Class III, and black for Classes IV and V. Spatiotemporal analysis reveals that mildly polluted points (originally marked red) in freshwater sections in the 2021 visualization map generally turned blue in the 2022 map, aligning spatially with improved parameter compliance. The system intuitively displays these changes through color gradients: the density of blue markers (Class I) significantly increased, with coverage rising from 90.77 % to 97.79 %, an increase of 7.02 percentage points. Red pollution markers in freshwater sections decreased by 76 %, with the most significant decline observed in historical mild pollution clusters around hospital bridge areas. This visualization method enables decision-makers to quickly identify areas of water quality improvement and residual pollution hotspots through changes in map color blocks, significantly enhancing the efficiency of pollution traceability and response.