Experience of using a geo-information approach for visualization of hydrological posts data in the Lviv region

This article addresses the urgency of improving hydrological monitoring and effective water resource management, which is particularly crucial for flood prevention and rapid emergency response.The problem lies in the need to develop a tool for efficient collection, processing, and visualization of water level data in the rivers of the Lviv region. The research objective is to develop and implement an interactive web application based on ArcGIS for visualizing and analyzing water level dynamics. This tool is designed to display the location of hydrological posts, provide access to their current status information, and analyze time series of hydrological data. The key feature of this approach is the integration and visualization of data from both automated and manual (gauge) posts, significantly expanding the cover-age of hydrological information.Based on the stated objectives, the geoinformation approach has been implemented for collecting and visualizing hydro-logical post data in the Lviv region using ArcGIS tools. The data source for this system comprises observations provided by the Basin Water Resources Management of the Western Bug and Sian Rivers. As a result, the interactive ArcGIS monitoring dash-board has been developed. It visualizes spatial and temporal water level data, integrating a web map with tabular time series data. This ensures automatic synchronization between selecting a post on the map and displaying dynamic charts and analytical tables. The web application facilitates comprehensive analysis of hydrological data.The proposed solution significantly enhances hydrological monitoring and supports managerial decision-making regarding flood prevention and emergency response. Its practical value lies in its application for water resource management and flood risk assessment, including the visualization of indicators and access to operational information for specialists and au-thorities. Future research will focus on real-time data updates, integration with meteorological indicators, and development of models for forecasting water levels and potential flood zones.