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All Dates (UTC+8)：
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  • 2024-05-27 [Monday]
  • 2024-05-28 [Tuesday]
  • 2024-05-29 [Wednesday]
All Forums：
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  • Opening Ceremony
  • Closing Ceremony
  • Plenary
  • Technical Committee Meeting
  • SS1 From models to Decision Support Systems
  • SS2 Digital twins for watersheds: challenges and advanced Hydroinformatic solutions
  • SS3 Water knowledge platforms and applications
  • SS4 Flash Flood Program: Advanced Hydroinformatic approaches for flash flood defence and prevention
  • SS5 Urban flooding and waterlogging
  • SS6 Extreme Drought and its Impacts in a Changing Environment
  • SS7 New remote sensing methods and new products for hydroinformatics solutions
  • SS9 Modelling and machine learning for understanding flash floods and mitigating their impact on Society
  • SS10 Climate Change Impacts on Urban Flooding: Challenges and Innovative Solutions
  • SS11 Marine and Coastal Hydroinformatics
  • SS12 Data-driven risk management of water-related disasters
  • SS13 High-Performance Computing in Hydrodynamics, Hydrology and Hydroinformatics
  • SS15 River and Lake Protection and Intelligent Management
  • SS16: Hybrid Modeling: Bridging Data-Driven and Mechanistic Approaches for Water Management
  • SS19 Smart Water Management and Technology in the Era of Climate Change
  • SS20 Hydroinformatics of deep tunnel drainage systems
  • SS21 Return on Experience: operational benefits of hydroinformatics for water utilities and cities
  • Hydraulic and hydrological modeling
  • SUEZ
  • Technologies for water management and monitoring
  • Emerging solutions in modelling methods
  • Complex water systems, remote sensing and control
  • Big-data, knowledge, and water data management
  • Climate change impacts
  • Environmental and coastal hydroinformatics
  • Digital transformation of urban water systems
  • Water – Energy – Food nexus
All Rooms：
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  • Ballroom 金源厅
  • Conference Room 1第一会议厅
  • Conference Room 5 第五会议厅
  • Conference Room 6 第六会议厅
  • Conference Room 7 第七会议厅
  • Conference Room 8 第八会议厅
  • Conference Room 9 第九会议厅
  • International Conference Room 国际会议厅

Conference Room 5 第五会议厅

2024-05-27 (UTC+8) Mon

SS9 Modelling and machine learning for understanding flash floods and mitigating their impact on Society

13:30-15:15 (UTC+8) | S5.3 SS9: Modelling and machine learning for understanding flash floods and mitigating their impact on Society

The rapid and destructive inundation from flash floods can cause severe damage to society. Their power is such that they can destroy buildings, uproot trees and move vehicles considerable distances. Not only are they dangerous due to the movement of water, but in many places, they entrain significant amounts of debris and sediment which can increase the damage by several orders of magnitude relative to a flood with just water. The session will especially address the challenges of monitoring of large areas, the model stability, the important role of debris and sediment entrainment, the efficient of early warning systems, the public awareness, the resilience strategies, the urban planning strategy, and consider case studies in several countries.

Moderator：
Mingfu Guan
NO. Beijing Time (UTC+8) Type Presentation Topic Speaker Affiliation / Organization
1 13:30-13:45 Oral Presentation

Hydrologic-hydrodynamic modelling for an early signal of flash flooding in mountainous ungauged areas

 Mingfu Guan The University of Hong Kong
2 13:45-14:00 Oral Presentation

Future Flood Projection and Impact Assessments in the Lancang-Mekong River Basin

 Jie Wang Lanzhou University
3 14:00-14:15 Oral Presentation

Modelling global river flows across ~ 3 million reaches with vector-based river routing and remote sensing

 Peirong Lin Peking University, China
4 14:15-14:30 Oral Presentation

Flash flood forecasting using artificial intelligence: improving prediction accuracy with neural networks

 Thitipoom Chailert University of Leeds
5 14:30-14:45 Oral Presentation

Integrated Hydrodynamic Modelling for Hydrogeological Hazard Chains in High Mountain Areas

 Xilin Xia University of Birmingham
6 14:45-15:00 Oral Presentation

Transboundary Precipitation and Flood Response in the China-Nepal Region: A Case Study of the Strong ENSO Event-2015 in the Karnali River Basin, Nepal

 Tirtha Raj Adhikari Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China
7 15:00-15:15 Oral Presentation

Predicting Flood Classes Using a Novel Class Membership Function and Hydrological Modeling

 Yongyong Zhang Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences

Emerging solutions in modelling methods

15:30-17:15 (UTC+8) | S1.3 Emerging solutions in modelling methods (I)
Moderator：
Masayuki HITOKOTO 丨 Andrea Menapace
NO. Beijing Time (UTC+8) Type Presentation Topic Speaker Affiliation / Organization
1 15:30-15:45 Oral Presentation

Embedded transient hydraulic simulations with machine learning processing for leak detection in water distribution networks

 Andrea Menapace Free University of Bozen-Bolzano
2 15:45-16:00 Oral Presentation

Implementing Liquid Neural Networks for Enhanced Plant-wide Control of a Wastewater Treatment Plant

 Cristian Camilo Gomez Cortes Ghent University
3 16:00-16:15 Oral Presentation

Integrating Twitter and Machine Learning for Enhanced Hydrological Event Detection and Management

 Gerald Corzo IHE Delft Institute for water Education
4 16:15-16:30 Oral Presentation

Research on Predicting Sediment Discharge from Xiaolangdi Reservoir Based on Machine Learning Algorithms

 Xinjie Li Yellow River Conservancy Research Institute, Yellow River Conservancy Commission
5 16:30-16:45 Oral Presentation

New data augmentation method for rainfall-runoff calculation using machine learning and examining it's applicability

 Masayuki HITOKOTO Nippon Koei Co., Ltd.
6 16:45-17:00 Oral Presentation

Uncovering farmers’ daily groundwater use behavior for crop irrigation in the High Plains aquifer

 Yao Hu University of Delaware
7 17:00-17:15 Oral Presentation

Near Real Time Flood Detection Technique using SAR Data and Deep Learning Methods

 Gopi P National Institute of Technology, Trichy

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