METHODOLOGICAL APPROACH TO DATA INTEGRATION IN TRANSBOUNDARY WATER RESOURCES MANAGEMENT

Abstract

This paper presents a methodological approach to data integration in transboundary water resources management under climate and demographic change. A multi-layer architecture is developed to ensure the collection, standardization, and integration of hydrological, climatic, demographic, and energy data using GIS, satellite monitoring, and machine learning techniques. The WAFLEX, WEAP, and climate-demographic scenario modeling (RCP/SSP) frameworks are applied to assess water balance, forecast deficits, and optimize resource allocation. Central Asian case studies demonstrate the potential of multi-agent modeling to reduce interstate conflicts and enhance socio-economic benefits. The findings indicate that data integration and the use of digital technologies significantly improve adaptive management and the resilience of water systems in a changing climate.