Path and Practice of Enhancing the "Four Precautions" Capability for Flood and Drought Disasters in Plain River Network Areas

The hydrological infrastructure in plain river network regions is structurally complex, with sluice gates and pumping stations subject to intensive manual regulation. Conventional frameworks for flood and drought disaster management frameworks in such regions exhibit critical deficiencies in real-time dynamic perception, multi-process coupled simulation, and cross-sectoral coordinated decision-making. To address these limitations, this study employs digital twin technology as a fundamental enabler. It systematically diagnoses mechanistic gaps within the traditional "four-pre" paradigm, namely, prediction, pre-warning, pre-simulation, and pre-planning, and proposes a digitally integrated "four-pre" collaborative response framework that is specifically tailored for plain river network areas. Theoretical pathways for enhancing four core capabilities are further delineated. (1) Prediction accuracy is dynamically refined via model-data assimilation; (2) Pre-warning precision is improved through spatio-temporally adaptive risk thresholds and scenario-correlation analytics; (3) Pre-simulation scheme selection is facilitated by interactive multi-scenario simulation; and (4) Pre-planning is rigorously simulated through executable, rule-based digital plans. Empirical validation was conducted in Huangpi District, Wuhan, employing two contrasting hydrological stressors: extreme rainfall events and prolonged summer-autumn droughts. The implementation achieves full closure of the operational logic loop from real-time perception to adaptive response. Results indicate that the proposed framework significantly enhances systemic resilience to flood and drought risks under complex hydraulic infrastructure regimes, thereby providing a transferable technical blueprint for intelligent water governance in analogous plain river network regions.