BRIDGING DATA AND MODELS IN WATER DEFICIT ASSESSMENT: INTEGRATING STATE WATER CADASTRE INTO DIGITAL TWIN-BASED MODELLING

Abstract

This study addresses the critical transition from the conventional, descriptive monitoring of water resources to a predictive, model-based management approach in the context of climate instability, increasing anthropogenic pressure and the impacts of war. The research is motivated by the increasing frequency and severity of hydrological extremes in Europe and Ukraine, where water deficits are becoming structural rather than episodic. In this context, the development of reliable forecasting tools is not constrained by a lack of data, but by the absence of systematic integration into hydrological and hydraulic modelling frameworks. This paper demonstrates that effectively assessing water deficits requires integrating verified, spatially consistent and semantically harmonised datasets into physically based models. The State Water Cadastre of Ukraine is identified as a foundational data source containing long-term observations of water quantity, quality, and use. However, its application is currently limited by methodological inconsistencies, spatial fragmentation and incompatibility with European data infrastructures, particularly the Water Information System for Europe (WISE). To address these issues, the paper proposes a structured approach to organising cadastre data based on three functional blocks: hydrometric (time series of discharge and groundwater levels); morphological and engineering (river geometry, hydraulic structures, and drainage systems); and operational (actual water use based on reporting datasets). This data architecture enables the formation of a coherent input layer for digital twin development. We have developed a conceptual framework for a river basin digital twin, integrating hydrological modelling (HEC-HMS) and hydraulic simulation (HEC-RAS) into a unified computational workflow, in particular utilizing multi-station calibration to ensure spatial consistency across sub-basins. The model enables scenario-based simulations of the water balance under different climatic conditions (including RCP-based scenarios) and provides a quantitative assessment of water deficits using a dimensionless index that reflects the ratio of water demand to available resources. The Polissya region is used as a representative case study. Analysis reveals a clear trend towards aridification, significant pressure from human activities on both surface and groundwater resources, and deterioration in water quality due to organic and nutrient pollution. The results confirm that, under low-flow conditions, aquatic ecosystems become much less resilient, which increases the risk of ecological degradation, particularly in wetlands. Special attention is given to the issue of data interoperability. The study demonstrates that harmonising the State Water Cadastre in accordance with WISE and INSPIRE requirements is necessary to ensure data comparability, improve model reliability and enable transboundary water management. Without such harmonisation, the integration of Ukrainian datasets into European assessment frameworks remains technically constrained. The proposed approach provides a methodological basis for bridging the gap between data availability and modelling capability. This approach can be applied to the development of advanced decision support systems for water resources management, facilitating risk-informed planning, optimising the allocation of water resources and enhancing resilience to climate-driven hydrological variability. The research is being conducted as part of the project Climate-Resilient Management for Safe Disinfected and Non-disinfected Water Supply Systems - 101081980 - SafeCREW - Horizon-cl6-2022-zeropollution-01.