Reservoir Operation and Management System

The reservoir operation matrix management system is a modern water conservancy project management model with digital technology as its core support, aiming to enhance reservoir safety management and operational efficiency through systematic and intelligent means. Its core architecture and technical characteristics are as follows:

Core Management Framework

1. "Four Wholes" Management

   Full Coverage: The supervision scope extends to all elements, including the upstream and downstream of the reservoir area, surrounding villages, and population distribution.

   Full Elements: Integrates key indicators such as project overview, water quality monitoring, and dam safety (e.g., seepage flow, deformation, etc.).

   All-Weather: Achieves 24-hour dynamic monitoring through IoT devices, drone inspections, visual robots, and other technologies.

   Full Cycle: Establishes a full-life-cycle digital archive for reservoir construction, operation and maintenance, danger removal, and reinforcement.

2. "Four Governance" System

   Improves the management system and responsibility system.

3. "Four Pre" Measures

   Forecasting: Predicts the impact range of floods by integrating meteorological data with hydrological models.

   Early Warning: Employs a threshold-triggered mechanism to issue alarms through multiple channels, such as text messages and platform pop-ups.

   Simulation: Simulates risk scenarios using professional models, such as dam break analysis and flood evolution.

   Preplan: Dynamically optimizes dispatching rules and emergency response plans.

4. "Four Management" Work

   Implements closed-loop management for danger removal and reinforcement, safety inspections, daily maintenance, and safety guarantees.

Technical Support System

Digital Twin and IoT: Constructs a 3D visualized reservoir model and integrates satellite remote sensing, underwater robots, micro weather stations, and other devices to form a "sky-ground-hydraulic engineering" three-dimensional monitoring network.

AI and Big Data Analysis: Utilizes machine learning to predict risks based on data such as seepage and deformation (e.g., Yubu Reservoir uses AI to achieve proactive hidden danger detection).

Professional Model Integration: Covers more than 20 hydraulic professional algorithms, including slope stability analysis, seepage simulation, and rainstorm resistance evaluation.

Multi-Level Collaborative Platform: Supports provincial-level overall coordination and regional customization.