Time
- Completed (Sep – Nov 2024 at ICMS, Edinburgh)
- Ongoing collaboration for expanded research in 2025–2026
Project Facts
- Duration Sep – Nov 2024 (Phase 1 at ICMS, UK)
- Funding source International Centre for Mathematical Sciences (ICMS), UK
- Principal investigator Assoc. Prof. Dr. Nguyen Ngoc Doanh
- Field sites Nhật Lệ River Basin, Quảng Bình Province, Vietnam
Objectives
- Combine mathematical models and AI techniques to improve flood forecasting accuracy
- Enhance flood early-warning systems using high-performance computing and automation
- Address mathematical challenges linked to climate resilience and disaster mitigation in Southeast Asia
- Propose a scalable modeling framework applicable to other river basins in Vietnam and beyond
Focus areas
- Hybrid Modeling Techniques: Merge partial differential equations (PDEs) with deep learning frameworks to capture river basin dynamics.
- AI for Disaster Forecasting: Utilize neural networks and big data pipelines for short- and mid-term flood prediction.
- Case Study – Nhật Lệ River Basin: Simulate flood events from 2010, 2020, and 2024 to validate model reliability under climate-induced extremes.
- Global Collaboration in Mathematical Sciences: Participate in ICMS’s Mathematics for Humanity program under the theme “Mathematical Challenges for Humanity.”
Methodology
- Model Coupling: Integrate numerical hydrological simulations with AI-based predictive analytics for dynamic warning generation.
- Data Pipeline Design: Incorporate new high-frequency field data, including rainfall, flow rates, and soil saturation levels.
- Collaborative Development: Conduct joint research sessions at ICMS, with cross-institutional peer review and scenario modeling.
Results
- Deployed and tested via mobile application for local communities in Quảng Bình.
- One conference paper accepted at CSoNet 2024 (Dec 2024, Bangkok); two manuscripts in preparation.
- Expanded research networks with Heriot-Watt University, Télécom Paris, Tohoku University, Kyoto University, and Kyushu University.
- Broaden project scope to cover pre-flood (mitigation/preparation), during-flood (logistics/communication), and post-flood (environment/health) phases.
- Embed forecasting results into a mobile app: FloodGuard Quảng Bình
Partners & stakeholders
- Lead Institution: VinUniversity (Vietnam)
- Core Researchers:
- Assoc. Prof. Dr. Nguyễn Ngọc Doanh (VinUni) – Project Lead
- Prof. Dr. Nguyễn Trung Việt, Dr. Đinh Nhật Quang, and PhD candidate Nguyễn Văn Lực (Thuyloi University)
- Dr. Huỳnh Quang Nghi (Can Tho University)
- Prof. Dr. Dương Quang Trung (Queen’s University Belfast, UK)
- Funding & Host: International Centre for Mathematical Sciences (ICMS), UK
- Scientific Collaborators: Heriot-Watt University (UK), Télécom Paris (France), Tohoku University & Kyoto University & Kyushu University (Japan), VIASM (Vietnam Institute for Advanced Study in Mathematics)
Reference
https://apps.apple.com/vn/app/floodguard-quang-binh/id6502816823
