MONITORING EUTROPHICATION OF WATER BODIES USING GEOINFORMATION TECHNOLOGIES: A CASE STUDY OF THE KARACHUNIVSKE RESERVOIR
DOI:
https://doi.org/10.32999/ksu2413-7391/2026-24-4Keywords:
eutrophication, satellite data, multispectral indices, geospatial analysis, hydroecological monitoringAbstract
This paper proposes a methodology for monitoring eutrophication of water bodies using geoinformation technologies. The approach is based on the analysis of satellite multispectral indices, including NDCI, FAI, and NDTI, which respectively reflect chlorophyll-a concentration in the water column, the presence of surface phytoplankton accumulations, and turbidity levels. The study was conducted using the Karachunivske Reservoir as a case study. A spatiotemporal analysis of index variations was performed, cartographic models of their distribution were developed, and the features of their dynamics at different stages of eutrophication were identified. It was found that the NDCI index characterizes the diffuse development of phytoplankton within the water column, whereas FAI reflects the formation of surface accumulations with clear spatial localization, primarily in coastal and low-flow areas. It is shown that the highest spatial correspondence between the indices occurs during the peak stage of eutrophication, when a continuous surface biomass layer is formed. At the same time, the NDTI index demonstrates a relatively stable spatial pattern determined by hydrodynamic and morphological characteristics of the reservoir and is less sensitive to biological processes. A spatial correlation analysis revealed an unstable relationship between NDCI and FAI, with a sharp increase during peak eutrophication, as well as a stable negative relationship between indices representing organic and mineral components of turbidity. Based on the obtained results, an approach to identifying eutrophication stages through the integration of spatial characteristics and inter-index relationships is substantiated. The proposed methodology enhances the informativeness of remote monitoring and can be applied for assessing the ecological condition of water bodies and supporting environmental management decision-making.