2017年-世界发展银行全球_Flood_Risk_Assessment_and_Forecasting_for_the_Ganges-Brahmaputra-Meghna_River_Basins_108页_4mb

Flood Risk Assessment and Forecasting for the Ganges-Brahmaputra-Meghna River Basins Summary

Core Content

This document presents a comprehensive flood risk assessment and forecasting analysis for the Ganges-Brahmaputra-Meghna (GBM) river basins, focusing on the Ganges River basin. It outlines the findings, methodologies, and recommendations for improving flood risk management and early warning systems in the region.

Main Objectives

• To assess flood risk across the Ganges River basin and the GBM basins.
• To develop and evaluate improved flood forecasting systems.
• To support sustainable development and climate resilience through better water management.

Key Components of the Study

1. Flood Risk Assessment

• Exposure: Mapping populations and assets at risk, including buildings, infrastructure, and crops.
• Hazard: Analysis of flood extent and depth, using historical data and flood recurrence maps.
• Vulnerability: Assessment of susceptibility to damage, particularly among the poor and vulnerable.
• Risk: Evaluation of probability and impact of floods across different subbasins and asset classes.

2. Flood Forecasting and Early Warning Systems

• Development of an end-to-end flood forecasting system that integrates data and models for accurate predictions.
• Introduction of a new forecasting scheme that provides probabilistic forecasts rather than deterministic ones.
• Emphasis on lead times for forecasting, which are critical for decision-making and risk mitigation.

Key Findings

• Population and Asset Exposure: The Lower Ganges subbasin is the most severely affected, with high population density and significant economic assets at risk.
• Annual Losses:
  • India: ~US$609 million
  • Bangladesh: ~US$19 million
  • Nepal: ~US$4 million
• Flood Impact:
  • In 2015, floods in South Asia caused nearly two-thirds of global natural disaster fatalities.
  • Floods are the most frequent natural disaster in the region, with severe economic and social consequences.
• Forecasting Benefits:
  • A one-day flood warning can reduce damage by up to 33%.
  • A seven-day lead time can reduce damage by up to 90% in household settings.
  • The 2007 Bangladesh floods could have been mitigated by ~US$208 million with an effective early warning system.
  • Over a decade, the estimated benefits of flood forecasting could reach ~US$1,700 million.

Key Methods and Innovations

• NCAR Flood Forecasting Scheme:
  • Uses a blending approach with multiple data sets and models.
  • Incorporates satellite data and rainfall forecasts from various weather centers.
  • Provides probabilistic forecasts and confidence levels.
• Interactive Flood Risk Atlas:
  • Developed by RMSI for the Ganges basin.
  • Offers detailed, user-friendly maps and data at various levels (national to block level).
• Multi-Model Approach:
  • Increases forecast reliability and skill, especially in areas with large upriver catchments.
  • Allows for locally optimized forecasts, providing up to 16 days of lead time in some locations.

Recommendations

• Improve Data Sharing: Enhance cross-border sharing of hydrometeorological data and technologies.
• Develop Accessible Platforms: Integrate flood forecasting tools into user-friendly platforms with feedback mechanisms.
• Strengthen Regional Cooperation: Support the establishment of a cooperative flood management platform across GBM countries.
• Enhance Early Warning Systems: Focus on real-time monitoring, expert translation of forecasts, and timely dissemination of warnings to communities.
• Build Capacity: Increase technical and institutional capacity for flood risk management, particularly in transboundary contexts.

Supporting Organizations

• World Bank: Led the overall project, including the development of the flood risk atlas and the distillation of technical findings.
• RMSI Private Ltd.: Conducted the flood risk assessment for the Ganges River basin.
• NCAR (National Center for Atmospheric Research): Developed the new flood forecasting scheme.
• ESCAP (United Nations Economic and Social Commission for Asia and the Pacific): Supported regional cooperation and the development of a transboundary flood warning system.
• RIMES: Facilitated regional discussions and cooperation on flood forecasting and early warning.

Future Outlook

• The GBM basins are highly vulnerable to flooding due to their transboundary nature and high population density.
• Continued collaboration among regional stakeholders is essential for effective flood management and resilience.
• The integration of new technologies and data sources will further improve forecasting accuracy and reliability.
• The flood risk atlas and forecasting system serve as models for other river basins in the region and beyond.

Conclusion

Flood risk assessment and forecasting are critical for reducing the impact of flooding on human lives, livelihoods, and economic assets in the GBM basins. The study highlights the importance of transboundary cooperation, data sharing, and the use of advanced forecasting models in enhancing flood preparedness and resilience. The interactive flood risk atlas and forecasting system represent significant advancements in the field, offering tools that can be applied to other river basins and supporting sustainable development in South Asia.