APPLICATION OF INNOVATIVE APPROACHES IN THE ACQUISITION, ASSESSMENT AND INTERPRETATION OF WATER BODY DATA VIA REMOTE SENSING WITHIN THE CONTEXT OF ENVIRONMENTAL PROTECTION: A CASE STUDY FOR BULGARIA

The objective of the study is to apply innovative methods for monitoring water bodies using remote sensing data and hydrological surveys. This research examines three types of water bodies—reservoirs, wetlands, and rivers within protected areas—over a 10-year period (2015–2025). A methodology has been developed based on an innovative approach for integrating hydrological and ecological parameter assessments within unified analytical boundaries. The study explores the potential of a combined approach that merges field data (hydrological work) with remote sensing methods. Satellite imagery (Sentinel-2 and Landsat) providing high spatio-temporal resolution was utilized, alongside Unmanned Aerial System (UAS) surveys using a DJI Mavic 3M, and available ground-based hydrological and meteorological observations (water levels, discharge, precipitation, and soil moisture/desiccation parameters) used for the verification and interpretation of remote observations. Data regarding indices such as [NDWI, MNDWI, NDVI, AWEI] and hydrological datasets are grouped into multi-year periods to analyze seasonal variations within long-term spatio-temporal dynamics of water body parameters. This represents a key element in assessing the state and conservation of ecosystems and the science-based planning of environmental management and protection measures. Data processing is conducted via Geographic Information Systems (GIS) and specialized remote sensing software.

The study applies spatial analysis methods involving the calibration of remotely sensed and ground-analog information to organize time series and perform statistical processing aimed at identifying trends, anomalies, and correlations between investigated parameters. The results are interpreted within the context of hydrological processes and the ecological status of water bodies, presenting dependencies between changes in water surface area, moisture, soil, and vegetation across the studied sites. In the long term, the developed methodology is expected to contribute to better engineering solutions and management practices in water resource conservation. Addressing the critical scientific and applied problem of data acquisition, processing, and interpretation allows for water management based on high-reliability information. The statistical approach—evaluating randomness, independence, and validity—is further enhanced through spatio-temporal analysis of datasets. By incorporating a temporal parameter, the analytical approach is not transformed into a purely stochastic one but rather into an innovative methodology for providing real-time information and process assessment.